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class="visually-hidden">Search</label> <input title="Enter the terms you wish to search for." data-drupal-selector="edit-keys" type="search" id="edit-keys--2" name="keys" value="" size="15" maxlength="128" class="form-search" placeholder="What are you looking for?"/> </div> <div data-drupal-selector="edit-actions" class="form-actions js-form-wrapper form-wrapper" id="edit-actions--2"><input data-drupal-selector="edit-submit" type="submit" id="edit-submit--2" value="Search" class="button js-form-submit form-submit" /> </div> </form> </div> </div> </div> </div> </div> <div id="content-wrapper"> <div id="header-separator"> </div> <div id="content"> <div class="container clearfix"> <div class="grid"> <div id="block-nc3rs-breadcrumbs" class="block block-system block-system-breadcrumb-block"> <div class="content"> <div class="breadcrumb"> <h2 class="visually-hidden">Breadcrumb</h2> </div> </div> </div> </div> </div> <div id="content-inside" class="container clearfix"> <div id="main" class="grid_8 narrow" tabindex="-1"> <div id="highlighted"> <div data-drupal-messages-fallback class="hidden"></div> </div>   <div id="block-nc3rs-page-title" class="block block-core block-page-title-block"> <div class="content"> <h1> <span>Example 3</span> </h1> </div> </div> <div id="block-nc3rs-system-main" class="block block-system block-system-main-block"> <div class="content"> <div data-history-node-id="53" about="/index.php/guide-example3"> <div class="content clearfix" > <div><h2>Effect of genotype on plasma glucose</h2> <p><img alt data-entity-type data-entity-uuid 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<p><a href="/eda/modelEditor/index/2737" target="_blank">View experiment diagram</a> | <a href="/eda/modelEditor/index/2767" target="_blank">Use this diagram as a template</a></p> <p>This is a phenotyping experiment, designed to test whether the mice genotype (wild type or knock out) affects plasma glucose levels following a glucose challenge and whether the effect of genotype depends on the sex of the animal. Four groups of mice of all the possible combinations of sex and genotype are used. The experimental unit in this experiment is each animal; this is only indicated for group 1 but the system assumes that the experimental unit is the same for all groups.</p> <p>The independent variables of interest here are sex and genotype. There is no allocation node on this diagram as the genotype and sex for each animal are randomised by Mendelian inheritance prior to the experiment. This is indicated in the properties of the variable nodes for sex and genotype.</p> <p>Mice are fasted for 14h before the start of the experiment, then body weight is measured for all animals. For each mouse, at t=0 plasma glucose is measured. Immediately after, an injection of glucose is administered. Each mouse is individually coded so that the experimenter does not know which group the animals belong to, blinding is however only partial as the experimenter can see the sex of the animals when injecting them. Animals are processed in a random order so that the time of the day does not confound the effect of sex and genotype. At t=15 min, t=30, t=60 and t=120 min, all animals are measured again, in the same random order as before so that the interval between injection and measurements is similar for all animals.</p> <p><em>Note that if measurements were spaced by a larger interval, for example one week instead of one hour, animals could be re-randomised for each measurement as re-ordering the animals would have limited impact on the intervals between measurements.</em></p> <p><span style="line-height: 1.538em;">The analysis uses a summary measure – the area under the curve – to compare plasma glucose over 2h between the four groups. This analysis includes genotype and sex as factors of interest, the experimenter is interested in the overall effect of sex and genotype on blood pressure and plasma glucose between the groups rather than differences between time points, thus the independent variable ‘time of measurement’ is not included in the analysis but a summary measure is used instead. If the data fit parametric assumptions, it can be analysed using a factorial ANOVA (2 way ANOVA with interaction).</span></p> <p>Group sizes are calculated based on the planned analysis method, to ensure that the experiment yields enough power to detect a difference between the groups if there is one. Power calculations for 2 way ANOVA are not available within the EDA so <a href="http://www.gpower.hhu.de/" target="_blank">G*Power</a> is used using the following settings and input parameters:</p> <ul> <li>Test family: F tests</li> <li>Statistical test: ANOVA: fixed effects, special, main effects and interactions</li> <li>Type of power analysis: A priori: compute required sample size – given α, power and effect size</li> <li>Effect size f: 0.4 (large effect by Cohen’s definition)</li> <li>α err prob: 0.05 (this is the <a href="/experimental-design-group#alpha" target="_blank">significance level</a>)</li> <li>Power (1-β err prob): 0.8 (this is the statistical <a href="/experimental-design-group#power" target="_blank">power</a>)</li> <li>Numerator df: 1 (number of categories in each variable minus 1, both variables have 2 categories)</li> <li>Number of groups: 4</li> </ul> <p>The total sample size calculated is 52, which relates to 13 experimental units (13 animals) per group.</p> <p>The outcome measure ‘body weight’ is not included in the analysis as it is measured to calculate the dose of the glucose challenge.</p> <h3>Keywords</h3> <p>Multiple animal characteristics | No randomisation | Data transformation | Multiple time points | Multiple outcome measures | Sex and genotype as factors of interest | Two-way ANOVA with interaction</p> <h3>References</h3> <p>This experiment is loosely based on the <a href="http://www.mousephenotype.org/impress/impress/displaySOP/87" target="_blank">intraperitoneal glucose tolerance test (ipGTT)</a> from the International Mouse Phenotyping Resource of Standardised Screens (IMPReSS).</p> </div> </div> <div class="clearfix"> </div> </div> </div> </div> <div id="sidebar-first" class="grid_4"> </div> <div class="publishedInformation"> <div class="publishedDate">First published 04 April 2014</div> <div class="updatedDate">Last updated 26 September 2023</div> </div> </div> </div> </div> </div> <div id="footer"> <div id="footer-inside" 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