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class="social-profile-avatar-container"><img class="profile-avatar u-positionAbsolute" alt="Stephen Tueller" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/170131/88031/95982/s200_stephen.tueller.jpg" /></div><div class="title-container"><h1 class="ds2-5-heading-sans-serif-sm">Stephen Tueller</h1><div class="affiliations-container fake-truncate js-profile-affiliations"><div><a class="u-tcGrayDarker" href="https://nd.academia.edu/">University of Notre Dame</a>, <a class="u-tcGrayDarker" href="https://nd.academia.edu/Departments/Psychology/Documents">Psychology</a>, <span class="u-tcGrayDarker">Graduate Student</span></div></div></div></div><div class="sidebar-cta-container"><button class="ds2-5-button hidden profile-cta-button grow js-profile-follow-button" data-broccoli-component="user-info.follow-button" 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href="https://kansas.academia.edu/OmriGillath"><img class="profile-avatar u-positionAbsolute" alt="Omri Gillath" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/12229/4074/34123846/s200_omri.gillath.jpg" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://kansas.academia.edu/OmriGillath">Omri Gillath</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">University of Kansas</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a href="https://harvard.academia.edu/StevenPinker"><img class="profile-avatar u-positionAbsolute" alt="Steven Pinker" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = 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class="suggested-user-card__user-info__subheader ds2-5-body-xs">University of the West of England</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a href="https://pennstate.academia.edu/JohnJohnson"><img class="profile-avatar u-positionAbsolute" alt="John Johnson" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/121122/32485/29852/s200_john.johnson.jpg" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://pennstate.academia.edu/JohnJohnson">John Johnson</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">Pennsylvania State University</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a href="https://ualberta.academia.edu/CorBaerveldt"><img class="profile-avatar u-positionAbsolute" alt="Cor Baerveldt" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/127880/34092/31326/s200_cor.baerveldt.jpg" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://ualberta.academia.edu/CorBaerveldt">Cor Baerveldt</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">University of Alberta</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a href="https://herts.academia.edu/KeithLaws"><img class="profile-avatar u-positionAbsolute" alt="Keith Laws" border="0" onerror="if (this.src != 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Wilson" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/4628390/1936769/2291809/s200_kelly.wilson.jpg" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://olemiss.academia.edu/KellyWilson">Kelly G . Wilson</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">University of Mississippi</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a href="https://wellesley.academia.edu/JonathanCheek"><img class="profile-avatar u-positionAbsolute" alt="Jonathan Cheek" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/4742070/2009074/2370028/s200_jonathan.cheek.jpg" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://wellesley.academia.edu/JonathanCheek">Jonathan Cheek</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">Wellesley College</p></div></div></ul></div><div class="ri-section"><div class="ri-section-header"><span>Interests</span></div><div class="ri-tags-container"><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="170131" href="https://www.academia.edu/Documents/in/Psychology"><div id="js-react-on-rails-context" style="display:none" data-rails-context="{"inMailer":false,"i18nLocale":"en","i18nDefaultLocale":"en","href":"https://nd.academia.edu/StephenTueller","location":"/StephenTueller","scheme":"https","host":"nd.academia.edu","port":null,"pathname":"/StephenTueller","search":null,"httpAcceptLanguage":null,"serverSide":false}"></div> <div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Psychology"]}" data-trace="false" data-dom-id="Pill-react-component-b9bd2f9f-125b-4f6b-88e9-a3c7ce20eae2"></div> <div id="Pill-react-component-b9bd2f9f-125b-4f6b-88e9-a3c7ce20eae2"></div> </a></div></div></div></div><div class="right-panel-container"><div class="user-content-wrapper"><div class="uploads-container" id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Stephen Tueller</h3></div><div class="js-work-strip profile--work_container" data-work-id="736585"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736585/Post_Hoc_Comparisons_and_Classification_Accuracy_in_the_Factor_Mixture_Model_and_Taxometric_Procedures"><img alt="Research paper thumbnail of Post-Hoc Comparisons and Classification Accuracy in the Factor Mixture Model and Taxometric Procedures" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736585/Post_Hoc_Comparisons_and_Classification_Accuracy_in_the_Factor_Mixture_Model_and_Taxometric_Procedures">Post-Hoc Comparisons and Classification Accuracy in the Factor Mixture Model and Taxometric Procedures</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Abstract Researchers in the social and behavioral sciences are frequently concerned whether the c...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Abstract Researchers in the social and behavioral sciences are frequently concerned whether the constructs they study should be represented as categorical types (classes) or continuous traits (factors). Two approaches to testing such type versus trait hypotheses are Meehlian taxometric procedures and the factor mixture model (FMM). The use of taxometric procedures and the more recently developed FMM has dramatically increased in the last ten years, and initial comparisons have shown that the latent structures that can be detected ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736585"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736585"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736585; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736585]").text(description); $(".js-view-count[data-work-id=736585]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 736585; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='736585']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=736585]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":736585,"title":"Post-Hoc Comparisons and Classification Accuracy in the Factor Mixture Model and Taxometric Procedures","internal_url":"https://www.academia.edu/736585/Post_Hoc_Comparisons_and_Classification_Accuracy_in_the_Factor_Mixture_Model_and_Taxometric_Procedures","owner_id":170131,"coauthors_can_edit":true,"owner":{"id":170131,"first_name":"Stephen","middle_initials":null,"last_name":"Tueller","page_name":"StephenTueller","domain_name":"nd","created_at":"2010-04-14T12:07:32.322-07:00","display_name":"Stephen Tueller","url":"https://nd.academia.edu/StephenTueller"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736586"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/736586/Evaluation_of_structural_equation_mixture_models_parameter_estimates_and_correct_class_assignment"><img alt="Research paper thumbnail of Evaluation of structural equation mixture models: parameter estimates and correct class assignment" class="work-thumbnail" src="https://attachments.academia-assets.com/32380904/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/736586/Evaluation_of_structural_equation_mixture_models_parameter_estimates_and_correct_class_assignment">Evaluation of structural equation mixture models: parameter estimates and correct class assignment</a></div><div class="wp-workCard_item"><span>Structural equation modeling: a …</span><span>, Jan 1, 2010</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Structural Equation Mixture Models(SEMMs) are latent class models that permit the estimation of a...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Structural Equation Mixture Models(SEMMs) are latent class models that permit the estimation of a structural equation model within each class. Fitting SEMMs is illustrated using data from one wave of the Notre Dame Longitudinal Study of Aging. Based on the model used in the illustration, SEMM parameter estimation and correct class assignment are investigated in a large scale simulation study. Design factors of the simulation study are (im)balanced class proportions, (im)balanced factor variances, sample size, and class separation. We compare the fit of models with correct and misspecified within-class structural relations. In addition, we investigate the potential to fit SEMMs with binary indicators. The structure of within-class distributions can be recovered under a wide variety of conditions, indicating the general potential and flexibility of SEMMs to test complex within-class models. Correct class assignment is limited.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ab47eceefb0b24c8fb98e272d27ae22f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":32380904,"asset_id":736586,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/32380904/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736586"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736586"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736586; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736586]").text(description); $(".js-view-count[data-work-id=736586]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 736586; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='736586']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736587"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736587/Mental_health_and_substance_abuse_treatment_stigma_among_soldiers"><img alt="Research paper thumbnail of Mental health and substance abuse treatment stigma among soldiers" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736587/Mental_health_and_substance_abuse_treatment_stigma_among_soldiers">Mental health and substance abuse treatment stigma among soldiers</a></div><div class="wp-workCard_item"><span>Military …</span><span>, Jan 1, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Few studies have compared persons in treatment to those not in treatment with regard to perceived...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Few studies have compared persons in treatment to those not in treatment with regard to perceived stigma. We surveyed soldiers to examine differences in stigma perceptions among those in treatment for substance abuse and/or mental health problems (n= 470) and those not in treatment (n= 966). Analyses revealed that soldiers in treatment perceived greater stigma regarding mental health treatment compared with soldiers not in treatment. These findings support the notion that personnel most in need of treatment perceive ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736587"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736587"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736587; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736587]").text(description); $(".js-view-count[data-work-id=736587]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 736587; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='736587']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=736587]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":736587,"title":"Mental health and substance abuse treatment stigma among soldiers","internal_url":"https://www.academia.edu/736587/Mental_health_and_substance_abuse_treatment_stigma_among_soldiers","owner_id":170131,"coauthors_can_edit":true,"owner":{"id":170131,"first_name":"Stephen","middle_initials":null,"last_name":"Tueller","page_name":"StephenTueller","domain_name":"nd","created_at":"2010-04-14T12:07:32.322-07:00","display_name":"Stephen Tueller","url":"https://nd.academia.edu/StephenTueller"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736588"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736588/Abstract_A_Comparison_of_the_Factor_Mixture_Model_and_Taxometric_Procedures"><img alt="Research paper thumbnail of Abstract: A Comparison of the Factor Mixture Model and Taxometric Procedures" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736588/Abstract_A_Comparison_of_the_Factor_Mixture_Model_and_Taxometric_Procedures">Abstract: A Comparison of the Factor Mixture Model and Taxometric Procedures</a></div><div class="wp-workCard_item"><span>Multivariate Behavioral Research</span><span>, Jan 1, 2008</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Taxometric procedures and the Factor Mixture Model (FMM) have a complimentary set of strengths an...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Taxometric procedures and the Factor Mixture Model (FMM) have a complimentary set of strengths and weaknesses. Both approaches purport to detect evidence of a latent class structure. Taxometric procedures, popular in psychiatric and psychopathology literature, make no assumptions beyond those needed to compute means and covariances. However, Taxometric procedures assume that observed items are uncorrelated within a class or taxon. This assumption is violated when there are individual differences in the trait underlying the ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736588"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736588"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736588; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736588]").text(description); $(".js-view-count[data-work-id=736588]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 736588; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='736588']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=736588]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":736588,"title":"Abstract: A Comparison of the Factor Mixture Model and Taxometric Procedures","internal_url":"https://www.academia.edu/736588/Abstract_A_Comparison_of_the_Factor_Mixture_Model_and_Taxometric_Procedures","owner_id":170131,"coauthors_can_edit":true,"owner":{"id":170131,"first_name":"Stephen","middle_initials":null,"last_name":"Tueller","page_name":"StephenTueller","domain_name":"nd","created_at":"2010-04-14T12:07:32.322-07:00","display_name":"Stephen Tueller","url":"https://nd.academia.edu/StephenTueller"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736589"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736589/Maternal_worry_about_infant_health_maternal_anxiety_and_maternal_perceptions_of_child_vulnerability_associated_with_newborn_hearing_screen_results"><img alt="Research paper thumbnail of Maternal worry about infant health, maternal anxiety, and maternal perceptions of child vulnerability associated with newborn hearing screen results" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736589/Maternal_worry_about_infant_health_maternal_anxiety_and_maternal_perceptions_of_child_vulnerability_associated_with_newborn_hearing_screen_results">Maternal worry about infant health, maternal anxiety, and maternal perceptions of child vulnerability associated with newborn hearing screen results</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">UMI, ProQuest ® Dissertations &amp;amp; Theses. The world&amp;#x27;s most comprehensive collectio...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">UMI, ProQuest ® Dissertations &amp;amp; Theses. The world&amp;#x27;s most comprehensive collection of dissertations and theses. Learn more... ProQuest, Maternal worry about infant health, maternal anxiety, and maternal perceptions of child ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736589"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736589"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736589; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736589]").text(description); 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$a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736590"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/736590/Addressing_the_Problem_of_Switched_Class_Labels_in_Latent_Variable_Mixture_Model_Simulation_Studies"><img alt="Research paper thumbnail of Addressing the Problem of Switched Class Labels in Latent Variable Mixture Model Simulation Studies" class="work-thumbnail" src="https://attachments.academia-assets.com/51262002/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/736590/Addressing_the_Problem_of_Switched_Class_Labels_in_Latent_Variable_Mixture_Model_Simulation_Studies">Addressing the Problem of Switched Class Labels in Latent Variable Mixture Model Simulation Studies</a></div><div class="wp-workCard_item"><span>Structural Equation Modeling: …</span><span>, Jan 1, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The discrimination between alternative models and the detection of latent classes in the context ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The discrimination between alternative models and the detection of latent classes in the context of latent variable mixture modeling depends on sample size, class separation, and other aspects that are related to power. Prior to a mixture analysis it is useful to investigate model performance in a simulation study that reflects the research settings. Multiple data sets are generated under 1 or more models, and alternative models are fitted to the data. The aggregation of results over multiple data sets is complicated by the fact that mixture models are only identified up to a permutation of the class labels. Estimated class labels are arbitrary, with the effect that the estimated parameters for Class 1 could be incorrectly labeled as Class 2, Class 3, and so forth, relative to their data generating labels. In a simulation study, the detection of switched labels needs to be automated. Switched class labels are not necessarily simple to detect. This article describes different possible scenarios of switched class labels, and develops an algorithm implemented in R that (a) detects switched labels, and (b) provides information that can be used to either correct class labels or to discard a particular data set from a simulation if class labels are ambivalent. The algorithm is useful in Monte Carlo simulations involving latent variable mixture models.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="46db68018b1eb30dbd5c0f34877dfc36" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":51262002,"asset_id":736590,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/51262002/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736590"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736590"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736590; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736591"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736591/Latent_Class_Detection_and_Class_Assignment_A_Comparison_of_the_MAXEIG_Taxometric_Procedure_and_Factor_Mixture_Modeling_Approaches"><img alt="Research paper thumbnail of Latent Class Detection and Class Assignment: A Comparison of the MAXEIG Taxometric Procedure and Factor Mixture Modeling Approaches" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736591/Latent_Class_Detection_and_Class_Assignment_A_Comparison_of_the_MAXEIG_Taxometric_Procedure_and_Factor_Mixture_Modeling_Approaches">Latent Class Detection and Class Assignment: A Comparison of the MAXEIG Taxometric Procedure and Factor Mixture Modeling Approaches</a></div><div class="wp-workCard_item"><span>Structural Equation Modeling: A …</span><span>, Jan 1, 2010</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class c...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class clustering, but they have very different sets of strengths and weaknesses. Taxometric procedures, popular in psychiatric and psychopathology applications, do not rely on distributional assumptions. Their sole purpose is to detect the presence of latent classes. The procedures capitalize on the assumption that, due to mean differences between two classes, item covariances within class are smaller than item covariances between the classes. FMM goes beyond class detection and permits the specification of hypothesis-based within-class covariance structures ranging from local independence to multidimensional within-class factor models. In principle, FMM permits the comparison of alternative models using likelihood-based indexes. These advantages come at the price of distributional assumptions. In addition, models are often highly parameterized and susceptible to misspecifications of the within-class covariance structure. Following an illustration with an empirical data set of binary depression items, the MAXEIG procedure and FMM are compared in a simulation study focusing on class detection and the assignment of subjects to the latent classes. FMM generally outperformed MAXEIG in terms of class detection and class assignment. Substantially different class sizes negatively impacted the performance of both approaches, whereas low class separation was much more problematic for MAXEIG than for the FMM.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736591"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736591"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736591; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); 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</script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="87248" id="papers"><div class="js-work-strip profile--work_container" data-work-id="736585"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736585/Post_Hoc_Comparisons_and_Classification_Accuracy_in_the_Factor_Mixture_Model_and_Taxometric_Procedures"><img alt="Research paper thumbnail of Post-Hoc Comparisons and Classification Accuracy in the Factor Mixture Model and Taxometric Procedures" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736585/Post_Hoc_Comparisons_and_Classification_Accuracy_in_the_Factor_Mixture_Model_and_Taxometric_Procedures">Post-Hoc Comparisons and Classification Accuracy in the Factor Mixture Model and Taxometric Procedures</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Abstract Researchers in the social and behavioral sciences are frequently concerned whether the c...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Abstract Researchers in the social and behavioral sciences are frequently concerned whether the constructs they study should be represented as categorical types (classes) or continuous traits (factors). Two approaches to testing such type versus trait hypotheses are Meehlian taxometric procedures and the factor mixture model (FMM). The use of taxometric procedures and the more recently developed FMM has dramatically increased in the last ten years, and initial comparisons have shown that the latent structures that can be detected ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736585"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736585"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736585; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736585]").text(description); $(".js-view-count[data-work-id=736585]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 736585; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='736585']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=736585]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":736585,"title":"Post-Hoc Comparisons and Classification Accuracy in the Factor Mixture Model and Taxometric Procedures","internal_url":"https://www.academia.edu/736585/Post_Hoc_Comparisons_and_Classification_Accuracy_in_the_Factor_Mixture_Model_and_Taxometric_Procedures","owner_id":170131,"coauthors_can_edit":true,"owner":{"id":170131,"first_name":"Stephen","middle_initials":null,"last_name":"Tueller","page_name":"StephenTueller","domain_name":"nd","created_at":"2010-04-14T12:07:32.322-07:00","display_name":"Stephen Tueller","url":"https://nd.academia.edu/StephenTueller"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736586"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/736586/Evaluation_of_structural_equation_mixture_models_parameter_estimates_and_correct_class_assignment"><img alt="Research paper thumbnail of Evaluation of structural equation mixture models: parameter estimates and correct class assignment" class="work-thumbnail" src="https://attachments.academia-assets.com/32380904/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/736586/Evaluation_of_structural_equation_mixture_models_parameter_estimates_and_correct_class_assignment">Evaluation of structural equation mixture models: parameter estimates and correct class assignment</a></div><div class="wp-workCard_item"><span>Structural equation modeling: a …</span><span>, Jan 1, 2010</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Structural Equation Mixture Models(SEMMs) are latent class models that permit the estimation of a...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Structural Equation Mixture Models(SEMMs) are latent class models that permit the estimation of a structural equation model within each class. Fitting SEMMs is illustrated using data from one wave of the Notre Dame Longitudinal Study of Aging. Based on the model used in the illustration, SEMM parameter estimation and correct class assignment are investigated in a large scale simulation study. Design factors of the simulation study are (im)balanced class proportions, (im)balanced factor variances, sample size, and class separation. We compare the fit of models with correct and misspecified within-class structural relations. In addition, we investigate the potential to fit SEMMs with binary indicators. The structure of within-class distributions can be recovered under a wide variety of conditions, indicating the general potential and flexibility of SEMMs to test complex within-class models. Correct class assignment is limited.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ab47eceefb0b24c8fb98e272d27ae22f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":32380904,"asset_id":736586,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/32380904/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736586"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736586"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736586; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736586]").text(description); $(".js-view-count[data-work-id=736586]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 736586; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='736586']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ab47eceefb0b24c8fb98e272d27ae22f" } } $('.js-work-strip[data-work-id=736586]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":736586,"title":"Evaluation of structural equation mixture models: parameter estimates and correct class assignment","internal_url":"https://www.academia.edu/736586/Evaluation_of_structural_equation_mixture_models_parameter_estimates_and_correct_class_assignment","owner_id":170131,"coauthors_can_edit":true,"owner":{"id":170131,"first_name":"Stephen","middle_initials":null,"last_name":"Tueller","page_name":"StephenTueller","domain_name":"nd","created_at":"2010-04-14T12:07:32.322-07:00","display_name":"Stephen Tueller","url":"https://nd.academia.edu/StephenTueller"},"attachments":[{"id":32380904,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/32380904/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/32380904/download_file","bulk_download_file_name":"Evaluation_of_structural_equation_mixtur.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/32380904/pdf-libre.pdf?1391622008=\u0026response-content-disposition=attachment%3B+filename%3DEvaluation_of_structural_equation_mixtur.pdf\u0026Expires=1740868815\u0026Signature=endTeAi7w-4UpjIpYL-StFpMsb0-N9TwUfjpo8snWlsBxOeaYFFnYptMode3di-hyoP8dk2-Ck4nXkTYHsymJq~-yVrCjZ5viPg9gH0cBG3xXmCURb1V1~sKEROhaJn77EboUTkxVEt6fChWjTYdP1T6DjgG3K75BxodsVsEr2MDO2JWhAWHODQFM6PrXAOLxzWAUHRgvq5kv2jTBYqkLy2mqK~CLBqQdr9PDkowSzXqAY50SQaP93QP3Bi9trsfXh7CsClVK1Z5xz0ruHj118TfUT3cAhiJ03ZGp0xaIPe2D4mO5bn93GUhCH9qFuHMW5T7EKHLhy4V6ZYC7aXypw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736587"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736587/Mental_health_and_substance_abuse_treatment_stigma_among_soldiers"><img alt="Research paper thumbnail of Mental health and substance abuse treatment stigma among soldiers" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736587/Mental_health_and_substance_abuse_treatment_stigma_among_soldiers">Mental health and substance abuse treatment stigma among soldiers</a></div><div class="wp-workCard_item"><span>Military …</span><span>, Jan 1, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Few studies have compared persons in treatment to those not in treatment with regard to perceived...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Few studies have compared persons in treatment to those not in treatment with regard to perceived stigma. We surveyed soldiers to examine differences in stigma perceptions among those in treatment for substance abuse and/or mental health problems (n= 470) and those not in treatment (n= 966). Analyses revealed that soldiers in treatment perceived greater stigma regarding mental health treatment compared with soldiers not in treatment. These findings support the notion that personnel most in need of treatment perceive ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736587"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736587"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736587; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736587]").text(description); $(".js-view-count[data-work-id=736587]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 736587; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='736587']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=736587]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":736587,"title":"Mental health and substance abuse treatment stigma among soldiers","internal_url":"https://www.academia.edu/736587/Mental_health_and_substance_abuse_treatment_stigma_among_soldiers","owner_id":170131,"coauthors_can_edit":true,"owner":{"id":170131,"first_name":"Stephen","middle_initials":null,"last_name":"Tueller","page_name":"StephenTueller","domain_name":"nd","created_at":"2010-04-14T12:07:32.322-07:00","display_name":"Stephen Tueller","url":"https://nd.academia.edu/StephenTueller"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736588"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736588/Abstract_A_Comparison_of_the_Factor_Mixture_Model_and_Taxometric_Procedures"><img alt="Research paper thumbnail of Abstract: A Comparison of the Factor Mixture Model and Taxometric Procedures" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736588/Abstract_A_Comparison_of_the_Factor_Mixture_Model_and_Taxometric_Procedures">Abstract: A Comparison of the Factor Mixture Model and Taxometric Procedures</a></div><div class="wp-workCard_item"><span>Multivariate Behavioral Research</span><span>, Jan 1, 2008</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Taxometric procedures and the Factor Mixture Model (FMM) have a complimentary set of strengths an...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Taxometric procedures and the Factor Mixture Model (FMM) have a complimentary set of strengths and weaknesses. Both approaches purport to detect evidence of a latent class structure. Taxometric procedures, popular in psychiatric and psychopathology literature, make no assumptions beyond those needed to compute means and covariances. However, Taxometric procedures assume that observed items are uncorrelated within a class or taxon. This assumption is violated when there are individual differences in the trait underlying the ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736588"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736588"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736588; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736588]").text(description); $(".js-view-count[data-work-id=736588]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 736588; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='736588']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=736588]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":736588,"title":"Abstract: A Comparison of the Factor Mixture Model and Taxometric Procedures","internal_url":"https://www.academia.edu/736588/Abstract_A_Comparison_of_the_Factor_Mixture_Model_and_Taxometric_Procedures","owner_id":170131,"coauthors_can_edit":true,"owner":{"id":170131,"first_name":"Stephen","middle_initials":null,"last_name":"Tueller","page_name":"StephenTueller","domain_name":"nd","created_at":"2010-04-14T12:07:32.322-07:00","display_name":"Stephen Tueller","url":"https://nd.academia.edu/StephenTueller"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736589"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736589/Maternal_worry_about_infant_health_maternal_anxiety_and_maternal_perceptions_of_child_vulnerability_associated_with_newborn_hearing_screen_results"><img alt="Research paper thumbnail of Maternal worry about infant health, maternal anxiety, and maternal perceptions of child vulnerability associated with newborn hearing screen results" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736589/Maternal_worry_about_infant_health_maternal_anxiety_and_maternal_perceptions_of_child_vulnerability_associated_with_newborn_hearing_screen_results">Maternal worry about infant health, maternal anxiety, and maternal perceptions of child vulnerability associated with newborn hearing screen results</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">UMI, ProQuest ® Dissertations &amp;amp; Theses. The world&amp;#x27;s most comprehensive collectio...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">UMI, ProQuest ® Dissertations &amp;amp; Theses. The world&amp;#x27;s most comprehensive collection of dissertations and theses. Learn more... ProQuest, Maternal worry about infant health, maternal anxiety, and maternal perceptions of child ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736589"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736589"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736589; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=736589]").text(description); 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$a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736590"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/736590/Addressing_the_Problem_of_Switched_Class_Labels_in_Latent_Variable_Mixture_Model_Simulation_Studies"><img alt="Research paper thumbnail of Addressing the Problem of Switched Class Labels in Latent Variable Mixture Model Simulation Studies" class="work-thumbnail" src="https://attachments.academia-assets.com/51262002/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/736590/Addressing_the_Problem_of_Switched_Class_Labels_in_Latent_Variable_Mixture_Model_Simulation_Studies">Addressing the Problem of Switched Class Labels in Latent Variable Mixture Model Simulation Studies</a></div><div class="wp-workCard_item"><span>Structural Equation Modeling: …</span><span>, Jan 1, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The discrimination between alternative models and the detection of latent classes in the context ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The discrimination between alternative models and the detection of latent classes in the context of latent variable mixture modeling depends on sample size, class separation, and other aspects that are related to power. Prior to a mixture analysis it is useful to investigate model performance in a simulation study that reflects the research settings. Multiple data sets are generated under 1 or more models, and alternative models are fitted to the data. The aggregation of results over multiple data sets is complicated by the fact that mixture models are only identified up to a permutation of the class labels. Estimated class labels are arbitrary, with the effect that the estimated parameters for Class 1 could be incorrectly labeled as Class 2, Class 3, and so forth, relative to their data generating labels. In a simulation study, the detection of switched labels needs to be automated. Switched class labels are not necessarily simple to detect. This article describes different possible scenarios of switched class labels, and develops an algorithm implemented in R that (a) detects switched labels, and (b) provides information that can be used to either correct class labels or to discard a particular data set from a simulation if class labels are ambivalent. The algorithm is useful in Monte Carlo simulations involving latent variable mixture models.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="46db68018b1eb30dbd5c0f34877dfc36" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":51262002,"asset_id":736590,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/51262002/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="736590"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="736590"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 736590; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="736591"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/736591/Latent_Class_Detection_and_Class_Assignment_A_Comparison_of_the_MAXEIG_Taxometric_Procedure_and_Factor_Mixture_Modeling_Approaches"><img alt="Research paper thumbnail of Latent Class Detection and Class Assignment: A Comparison of the MAXEIG Taxometric Procedure and Factor Mixture Modeling Approaches" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/736591/Latent_Class_Detection_and_Class_Assignment_A_Comparison_of_the_MAXEIG_Taxometric_Procedure_and_Factor_Mixture_Modeling_Approaches">Latent Class Detection and Class Assignment: A Comparison of the MAXEIG Taxometric Procedure and Factor Mixture Modeling Approaches</a></div><div class="wp-workCard_item"><span>Structural Equation Modeling: A …</span><span>, Jan 1, 2010</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class c...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class clustering, but they have very different sets of strengths and weaknesses. Taxometric procedures, popular in psychiatric and psychopathology applications, do not rely on distributional assumptions. Their sole purpose is to detect the presence of latent classes. The procedures capitalize on the assumption that, due to mean differences between two classes, item covariances within class are smaller than item covariances between the classes. FMM goes beyond class detection and permits the specification of hypothesis-based within-class covariance structures ranging from local independence to multidimensional within-class factor models. In principle, FMM permits the comparison of alternative models using likelihood-based indexes. These advantages come at the price of distributional assumptions. In addition, models are often highly parameterized and susceptible to misspecifications of the within-class covariance structure. Following an illustration with an empirical data set of binary depression items, the MAXEIG procedure and FMM are compared in a simulation study focusing on class detection and the assignment of subjects to the latent classes. FMM generally outperformed MAXEIG in terms of class detection and class assignment. 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