2. Random-Effects Modeling of Categorical Response Data

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Measurement of women's autonomy according to women and their husbands: Results from five Asian countries (2006, background): “They thus differ from odds-ratios as formed from the marginal distributions of the variables, or the percentages graphed in Figures 1 and 2, which are a population-averaged effect (Agresti et al. 2000).”
Foundations of Linear and Generalized Linear Models (2015, result): “However, maximizing the likelihood with a two-point distribution for ui yields similar results for the fixed effects estimates (Agresti et al. 2000).”
7. Multilevel Latent Class Models (2003, methodology): “*Tilburg University 213 Random-coefficients models can be used to deal with various types of dependent observations (Agresti et al. 2000).”
An EM algorithm for the estimation of parametric and nonparametric hierarchical nonlinear models (2004, methodology): “If the mixed model of interest is a 2-level model, ML estimation can be performed by means of the EM algorithm (Bock and Aitkin, 1981; Agresti et al., 2000), which is a natural approach to estimation problems with missing data (here, the random effects for each case).”
Combining Quantitative and Qualitative Approaches in Poverty Analysis (2002, unknown): “Recent issues of the annual publication of the American Sociological Association, Sociological Methodology, largely contain papers on advanced statistical techniques (e.g., Agresti, Booth, & Hubert, 2000 ).”