Transcription of Introduction to log-linear models
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' $. 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.
analyze the simultaneous effects of multiple variables, including mixtures of categorical and continuous variables. For example, the Breslow-Day statistics only works for 2×2×K tables, while log-linear models will allow us to test of homogenous associations in I × J × K and higher-dimensional tables. The structural form of the model ...
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