Logistic Regression: A Self-learning Text, Third Edition (Statistics in the Health Sciences)

Objectives Upon completing this chapter, the learner should be able to: State or recognize when to use unconditional vs. condit ...

Presentation I. Overview FOCUS How ML methods work Two alternative ML approaches Guidelines for choice of ML approach Overview o ...

Discriminant function analysis:  Previously used for logistic model  Restrictive normality assumptions  Gives biased results ...

The Choice: Unconditional – preferred if the number of parameters issmall relative to the number of subjects Conditional – prefe ...

REFERENCE Chapter 11: Analysis of Matched Data Using Logistic Regression In contrast, consider a case-control study involving 10 ...

Guidelines:  Useconditionalif matching  Useunconditionalif no matching and number of variables not too large Safe rule: Usecon ...

R-to-1 matching unconditional is overestimate of (correct) conditional estimate IV. The Likelihood Function and Its Use in t ...

L¼L(u) ¼joint probability of observing the data ML method maximizes the like- lihood functionL(u) ^u¼ð^y 1 ;^y 2 ;...;^yqÞ¼ML es ...

Maximizing L(u) is equivalent to maximizing lnL(u) Solve: @lnLðuÞ @yj ¼0,j¼1, 2,...,q qequations inqunknowns require iterativeso ...

Two alternatives: Unconditional algorithm (LU) vs. Conditional algorithm (LC) likelihoods Formula forLis built into computer alg ...

The conditional formula: LC¼ Prðobserved dataÞ Prðall possible configurationsÞ m 1 cases: (X 1 ,X 2 ,...,Xm 1 ) nm 1 noncases: ...

LC¼ Qm^1 l¼ 1 exp ~ k i¼ 1 biXli  ~ u Qm^1 l¼ 1 exp ~ k i¼ 1 biXlui  Note:adrops out ofLC Conditional algorithm:  Estimat ...

Matching: Unconditional) biased estimates ofbs Conditional )unbiased estimates ofbs V. Overview on Statistical Inferences for Lo ...

Importance ofV^ð^uÞ: inferences require accounting for variability and covariability (3) Variable listing Variable ML Coefficien ...

We now consider how to use the information provided to obtain an estimated odds ratio for the fitted model. Because this model c ...

dORs¼point estimators Variability ofdOR considered for statistical inferences Two types of inferences: (1) Testing hypotheses (2 ...

Large samples: both procedures give approximately the same results Small or moderate samples:different results possible; likelih ...

Detailed Outline Abbreviated Outline I. Overview(page 106) Focus:  How ML methods work  Two alternative ML approaches  Guidel ...

G. Conditional algorithm estimatesbs but nota (nuisance parameter). H. Matched data: unconditional gives biased estimates, where ...

Practice Exercises Exercises True or False (Circle T or F) T F 1. When estimating the parameters of the logistic model, least sq ...