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This course introduces principles and analyses related to data with categorical outcomes. This course will consider topics such as probability distributions with categorical data, contingency table analysis, the generalized linear model, logit models and loglinear models. Students are expected to: a) learn to select methods appropriate for a question of(More)
During social interactions, an individual's behavior is largely governed by the subset of signals emitted by others. Discrimination of "self" from "other" regulates the territorial urine countermarking behavior of mice. To identify the cues for this social discrimination and understand how they are interpreted, we designed an olfactory-dependent(More)
In this article, we propose a generalized estimating equations (GEE) approach for correlated ordinal or nominal multinomial responses using a local odds ratios parameterization. Our motivation lies upon observing that: (i) modeling the dependence between correlated multinomial responses via the local odds ratios is meaningful both for ordinal and nominal(More)
Background: Climatic or meteorological condition changes have been implicated in the pathogenesis of Idiopathic Sudden Sensorineural Hearing Loss (ISSHL). We investigated the seasonal distribution of ISSHL and evaluated the influence of meteorological parameters (such as temperature, humidity, and atmospheric pressure), their variation and covariation on(More)
In two-way contingency tables analysis, a popular class of models for describing the structure of the association between the two categorical variables are the so-called “association” models. Such models assign scores to the classification variables which can be either fixed and prespecified or unknown parameters to be estimated. Under the row–column (RC)(More)