When analyzing multivariate longitudinal binary data, we estimate the effects on the responses of the covariates while accounting for three types of complex correlations present in the data. These ...

Multivariate binary data arise in a variety of settings. In this paper, we propose a practical and efficient computational framework for maximum likelihood estimation of multivariate probit regression ...

main.R: the R file containing codes to implement the proposed method. It shows how to analyze the example datasets stored in "dat.RData". HelperFunctions.R: helper functions that are used in main.R.

Before we learn how to perform multivariate regression in Excel, it is important to have a refresher on regression as a whole and multivariate regression in particular. One of the hallmarks of human ...

In many applications, interest focuses on assessing the relationship between a predictor and a multivariate outcome variable, and there may be prior knowledge about the shape of the regression curves.

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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 ...