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732G21/732G28/732A35 Lecture 9

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25 computer programmers with different experience have performed a test. For each programmer we have recorded whether he or she passed the test (Y = 1) or not (Y = 0). 2 Months of experience (X) Task success (Y)

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Binary Logistic Regression: Task success (Y) versus Months of experi Link Function: Logit Response Information Variable Value Count Task success (Y) 1 11 (Event) 0 14 Total 25 Logistic Regression Table 95% Odds CI Predictor Coef SE Coef Z P Ratio Lower Upper Constant Months of experience (X) Log-Likelihood = Test that all slopes are zero: G = 8.872, DF = 1, P-Value = Goodness-of-Fit Tests Method Chi-Square DF P Pearson Deviance Hosmer-Lemeshow

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5 Binary Logistic Regression: Task success versus Months of ex, Age, Gender Link Function: Logit Response Information Variable Value Count Task success 1 11 (Event) 0 14 Total 25 Logistic Regression Table Odds 95% CI Predictor Coef SE Coef Z P Ratio Lower Upper Constant Months of experience Age Gender Log-Likelihood = Test that all slopes are zero: G = 8.996, DF = 3, P-Value = Goodness-of-Fit Tests Method Chi-Square DF P Pearson Deviance Hosmer-Lemeshow

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Suppose you are a field biologist and you believe that adult population of salamanders in the Northeast has gotten smaller over the past few years. You would like to determine whether any association exists between the length of time a hatched salamander survives and level of water toxicity, as well as whether there is a regional effect. Survival time is coded as 1 if < 10 days, 2 = 10 to 30 days, and 3 = 31 to 60 days. 6

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Ordinal Logistic Regression: Survival versus ToxicLevel Link Function: Logit Response Information Variable Value Count Survival Total 73 Logistic Regression Table Odds 95% CI Predictor Coef SE Coef Z P Ratio Lower Upper Const(1) Const(2) ToxicLevel Log-Likelihood = Test that all slopes are zero: G = , DF = 1, P-Value = Goodness-of-Fit Tests Method Chi-Square DF P Pearson Deviance

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