Transcription of Introduction to log-linear models
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Introduction to log-linear models
' $. Stat 504, Lecture 16 1. Introduction to log-linear models Key Concepts: Benefits of models Two-way log-linear models Parameters Constraints, Estimation and Interpretation Inference for log-linear models Objectives: Understand the structure of the log-linear models in two-way tables Understand the concepts of independence and associations described via log-linear models in two-way tables & %. ' $. Stat 504, Lecture 16 2. Useful Links: The CATMOD procedure in SAS: The GENMOD procedure in SAS: The SAS source on log-linear model analysis #stat_catmod_catmodllma Fitting log-linear models in R. Fitting log-linear models in R via generalized linear models (glm()). Readings: Agresti (2002) Ch. 8, 9. Agresti (1996) Ch. 6, 7. & %. ' $. Stat 504, Lecture 16 3. Benefits of models over significance tests Thus far our focus has been on describing interactions or associations between two or three categorical variables mostly via single summary statistics and with significance testing.
Conservative 382 199 117 698 Total 647 855 274 1774 Are political view and choice independent? You already know how to answer this via chi-square test of independence, but now we want to model the cell counts with the log-linear model of independence and ask if this model fits well.
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