<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/5284" mdate="2012-07-23 00:00:00"> <author>Entisar A. Elgmati</author> <title>A Martingale Residual Diagnostic for Logistic Regression Model</title> <pages>719 - 723</pages> <year>2012</year> <volume>6</volume> <number>7</number> <journal>International Journal of Mathematical and Computational Sciences</journal> <ee>https://publications.waset.org/pdf/5284</ee> <url>https://publications.waset.org/vol/67</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>Martingale model diagnostic for assessing the fit of logistic regression model to recurrent events data are studied. One way of assessing the fit is by plotting the empirical standard deviation of the standardized martingale residual processes. Here we used another diagnostic plot based on martingale residual covariance. We investigated the plot performance under several types of model misspecification. Clearly the method has correctly picked up the wrong model. Also we present a test statistic that supplement the inspection of the two diagnostic. The test statistic power agrees with what we have seen in the plots of the estimated martingale covariance. </abstract> <index>Open Science Index 67, 2012</index> </article>