Logistic regression is a simple statistical tool used in binary classification. LR is useful for situations in which we want to predict the presence or absence of a characteristic or outcome based on values of a set of predictor variables. Unlike LR, PCA is another technique used in feature extraction and in dimensionality reduction. This paper puts forth the experimental results of LR model an...

Following a Bayesian statistical inference paradigm, we provide an alternative methodology for analyzing a multivariate logistic regression. We use a multivariate normal prior in the Bayesian analysis. We present a unique Bayes estimator associated with a prior which is admissible. The Bayes estimators of the coefficients of the model are obtained via MCMC methods. The proposed procedure...

The common practice of collapsing inherently continuous or ordinal variables into two categories causes information loss that may potentially weaken power to detect effects of explanatory variables and result in Type II errors in statistical inference. The purpose of this investigation was to illustrate, using a substantive example, the potential increase in power gained from an ordinal instead...