1 PH 240A: Chapter 14 Nicholas P. Jewell University of California Berkeley November 15, 2005.

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Presentation transcript:

1 PH 240A: Chapter 14 Nicholas P. Jewell University of California Berkeley November 15, 2005

2 Logistic Regression: Assessment of Confounding

3  Consider two risk factors for CHD incidence (eg. serum cholesterol, X 1, and body weight, X 2 )  Two models: 

4 Coding for WCGS Variables

5 WCGS: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (1)a < (2)abab < (3)ab1b2b3b4ab1b2b3b < < (4)abab < (5)abab < (6)abab <

6 WCGS: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (7)abc1c2c3c4abc1c2c3c < < (8)abcabc < (9)abcabc < (10)abcabc <

7 Logistic Regression: Introducing Interaction

8 Coding for Pancreatic Cancer Example

9 Pancreatic Cancer: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (1)a (2)abab < (3)ab1b2b3ab1b2b < (4)abab

10 Pancreatic Cancer: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (5)abcabc < (6)abcdabcd

11 Pancreatic Cancer: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (7)ab1b2b3cab1b2b3c < (8)ab1b2b3cd1d2d3ab1b2b3cd1d2d

12 Pancreatic Cancer: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (9)abcabc (10)abcdabcd

13 Pancreatic Cancer: Fitted Logistic Regression Models

14 Coding for WCGS Variables

15 WCGS: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (7)abc1c2c3c4abc1c2c3c < < (8)abcabc < (9)abcabc < (10)abcabc <

16 WCGS: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (11)abc1c2c3c4d1d2d3d4abc1c2c3c4d1d2d3d <

17 WCGS: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (12)abc1c2c3c4dabc1c2c3c4d < (13)abcdabcd <

18 WCGS: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (14)abcdabcd < (15)abcdabcd < collinearity

19 CHD Incidence Versus Body Weight

20 WCGS: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (5)abab < (6)abab < Background: quadratic models & collinearity

21 WCGS: Fitted Logistic Regression Models (#) ModelParam.EstimateSDORp-valueMax. log lik. (16)abcabc (17)abcabc < (18)abab < (19)abcabc < quadratic models & collinearity