The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 43, No. 3 (September/septembre 2015), pp. 337-357 (21 pages) Multivariate ordinal data are modelled as a finite ...

Ordinal regression and classification methods form a vital branch of statistical learning wherein the outcome variable possesses an inherent order. Unlike conventional classification problems, where ...

Probit ("probability unit") regression is a classical machine learning technique that can be used for binary classification -- predicting an outcome that can only be one of two discrete values. For ...

Introduction: We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) ...

The estimation of empirical models is essential to public policy analysis and social science research. Ordinary Least Squares (OLS) regression analysis is the most frequently used empirical model, and ...

Some of you may have come across a growing number of publications in your field using an alternative paradigm called Bayesian statistics in which to perform their statistical analyses. The goal of ...