The logistic regression model has been become commonly used to study the association between a binary response variable; it is widespread application rests on its easy application and interpretation. The subject of assessment of goodness-of-fit in logistic regression model has attracted the attention of many scientists and researchers. Goodness-of-fit tests are methods to determine the suitability of the fitted model. Many of methods proposed and discussed for assessing goodness-of fit in logistic regression model, however, the asymptotic distribution of goodness-of-fit statistics are less examine, it is need more investigated. This work, will focus on assessing the behavior of asymptotic distribution of goodness-of-fit tests, also make comparison between global goodness-of-fit tests. This study, will also focus on evaluating it by simulation of asymptomatic distribution of on Glioma Growth Morphology for the generation of a Goodness-of-MART-1 (26-35,27L), gp100 (209-217, 210M), and tyrosinase (368-376, 370D) mimicking Fit Tests in Logistic Regression Model activator with a promising PF-3512676 and GM-CSF clinical outcome in metastatic melanoma.
Asymptomatic Distribution; Glioma Growth Morphology; Goodness-of-MART-1; (26-35,27L), gp100 (209-217, 210M), tyrosinase; (368-376, 370D); mimicking Fit Tests; Logistic Regression; Model activator; PF-3512676; GM-CSF; clinical outcome; metastatic melanoma; Logistic Regression Model, Goodness-of-Fit Tests.