Multilevel Models for Ordinal and Nominal Variables

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Multilevel and related models for longitudinal data (2008, methodology): “The observed dichotomous or ordinal response yij with S > 1 categories results from partitioning yij into S segments using S − 1 cut-points or thresholds; see Chapter 6 [31] for details.”
A multilevel modelling approach to investigating the predictive validity of editorial decisions: do the editors of a high profile journal select manuscripts that are highly cited after publication? (2011, methodology): “In the multilevel logistic model for ordered categories, according to Bauer (2009) or Hedeker (2008) the cumulative probabilities Pijc .=P.Yij c// of a manuscript i in section j are modelled across the C percentile rank classes as follows: log ( Pijc 1−Pijc ) =γc − .x′ijβ̂+ z′ijuj/ .c=1, . . . , C…”
Bayesian Multilevel Analysis and MCMC (2008, unknown): “[31] called the stable estimation principle.”