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Full-Text Articles in Statistical Models
Using R To Create Synthetic Discrete Response Regression Models, Joseph Hilbe
Using R To Create Synthetic Discrete Response Regression Models, Joseph Hilbe
Joseph M Hilbe
The creation of synthetic models allows a researcher to better understand models as well as the bias that can occur when the assumptions upon which a model is based is violated. This article provides R code that can be used or amended to create a variety of discrete response regression models.
Creation Of Synthetic Discrete Response Regression Models, Joseph Hilbe
Creation Of Synthetic Discrete Response Regression Models, Joseph Hilbe
Joseph M Hilbe
The development and use of synthetic regression models has proven to assist statisticians in better understanding bias in data, as well as how to best interpret various statistics associated with a modeling situation. In this article I present code that can be easily amended for the creation of synthetic binomial, count, and categorical response models. Parameters may be assigned to any number of predictors (which are shown as continuous, binary, or categorical), negative binomial heterogeneity parameters may be assigned, and the number of levels or cut points and values may be specified for ordered and unordered categorical response models. I …
Log-Negative Binomial Regression As A Generalized Linear Model, Joseph Hilbe
Log-Negative Binomial Regression As A Generalized Linear Model, Joseph Hilbe
Joseph M Hilbe
The negative binomial (NB) is a member of the exponential family of discrete probability distributions. The nature of the distribution is itself well understood, but its contribution to regression modeling, in particular as a generalized linear model (GLM), has not been appreciated. The mathematical properties of the negative binomial are derived and GLM algorithms are developed for both the canonical and log form. Geometric regression is seen as an instance of the NB. The log forms of both may be effectively used to model types of POisson-overdispersed count data. A GLM-type algorithm is created for a general log-negative binomial regression …