Multilevel Modeling of Periodontal Data (V)

5 Logistic Models for Binary and Binomial Responses

In the previous chapters, continuous response variables had been considered in various variance components, random intercept, random coefficient, time series, and multivariate time series multilevel models. In this chapter, we want to look at binary or binomial (proportion) responses. We will mainly focus on the logit link function. As usual, we start with a single-level model and extend this to appropriately consider the three-level hierarchical structure. We also explore contextual effects here. Significance testing and model interpretation using odds ratios and variance partition coefficients are discussed.


5.1 Description of the Example Data Set

The data for an example are stored in an EXCEL file (bop_pli01.xlsx). The binary response variable here is presence or absence of bleeding on probing (BOP) at gingival units in 50 students at Kuwait University. All had plaque-induced gingival disease.

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29 October 2014 @ 6:17 am.

Last modified Otober 29, 2014.


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