Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS.

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Serval ID
serval:BIB_B64BDD5DB9AF
Type
Article: article from journal or magazin.
Collection
Publications
Title
Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS.
Journal
International Review of Social Psychology
Author(s)
Sommet Nicolas, Morselli Davide
ISSN
2397-8570
Publication state
Published
Issued date
2017
Volume
30
Pages
203-218
Language
english
Abstract
This paper aims to introduce multilevel logistic regression analysis in a simple and practical way. First, we introduce the basic principles of logistic regression analysis (conditional probability, logit transformation, odds ratio). Second, we discuss the two fundamental implications of running this kind of analysis with a nested data structure: In multilevel logistic regression, the odds that the outcome variable equals one (rather than zero) may vary from one cluster to another (i.e. the intercept may vary) and the effect of a lower-level variable may also vary from one cluster to another (i.e. the slope may vary). Third and finally, we provide a simplified three-step “turnkey” procedure for multilevel logistic regression modeling:
-Preliminary phase: Cluster- or grand-mean centering variables
-Step #1: Running an empty model and calculating the intraclass correlation coefficient (ICC)
-Step #2: Running a constrained and an augmented intermediate model and performing a likelihood ratio test to determine whether considering the cluster-based variation of the effect of the lower-level variable improves the model fit
-Step #3 Running a final model and interpreting the odds ratio and confidence intervals to determine whether data support your hypothesis
Command syntax for Stata, R, Mplus, and SPSS are included. These steps will be applied to a study on Justin Bieber, because everybody likes Justin Bieber.
Open Access
Yes
Create date
15/03/2018 13:07
Last modification date
21/08/2019 7:10
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