Logisticpr - STA 6127 PRACTICE PROBLEM 3 These problems deal with logistic regression and related issues 1 This problem studies remission in cancer

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Unformatted text preview: STA 6127 PRACTICE PROBLEM 3 These problems deal with logistic regression and related issues. 1. This problem studies remission in cancer patients (1=remission, 0=not successful) as a function of the explanatory variable called labelling index (LI). Following is a part ofthe SAS output obtained:------------------------------------------------------------------- Intercept Intercept and Criterion Only Covariates-2 Log L 34.372 26.073 Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio * 1 0.0040 Parameter Estimate Standard Error Chi-Square Pr > ChiSq Intercept-3.7771 1.3786 7.5064 0.0061 li 0.1449 0.0593 * 0.0146 Obs li remiss n pi_hat lower upper 1 8 2 0.06797 0.01121 0.31925 2 10 2 0.08879 0.01809 0.34010-------------------------------------------------------------------- (a) State the fitted model in terms of ˆ π . 1 (b) If a patient has labeling index value 15, predict the odds of that patient having successful remission as opposed to not having successful remission.successful remission as opposed to not having successful remission....
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This note was uploaded on 07/08/2011 for the course STA 6127 taught by Professor Mukherjee during the Fall '08 term at University of Florida.

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Logisticpr - STA 6127 PRACTICE PROBLEM 3 These problems deal with logistic regression and related issues 1 This problem studies remission in cancer

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