vars - Explanatory Variables in Logistic Regression

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1 Explanatory Variables in Logistic Regression [explanatory_vars_in_logistic_regr.doc] Part I 1. Graphically & numerically describe the outcome var & potential explanatory vars. 2. List the potential explanatory variables in order of their anticipated, conceptual importance in relation to the outcome variable, briefly noting (a) the dimensions of such importance; (b) the anticipated type of relationship to the outcome variable; & (c) how each explanatory variable relates to each of the other explanatory variables. 2. In delineating the variables in these ways, consider the kinds of outcome var/explanatory var relationships discussed in Agresti & Finlay, chapter 10. Part II 1. Crosscheck the outcome var with potential explanatory vars: at this preliminary stage, select as potential explanatory vars those that have at least a modest association with the outcome var, entering the var names in a table. 2. Check collinearity among the quantitative vars: § graph comparative boxplots & a scatterplot matrix for the quantitative vars § estimate the model in OLS (including only quantitative explanatory vars on the right-hand side) § VIF 3. Explore univariable models with each potential explanatory var: record each coef, se & CI, & p-value. Provisionally select a var if its p-value<=0.25. § Estimate a univariable model for each potential explanatory var as follows, &
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This note was uploaded on 07/11/2011 for the course SYA 6306 taught by Professor Tardanico during the Spring '09 term at FIU.

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vars - Explanatory Variables in Logistic Regression

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