We present the new laplace command for estimating Laplace regression, which models quantiles of a possibly censored outcome variable given covariates. We illustrate laplace with an example from a clinical trial on survival in patients with metastatic renal carcinoma. We also report the results...

We present a set of Stata commands for the estimation, prediction, and graphical representation of logistic quantile regression described by Bottai, Cai, and McKeown (2010, Statistics in Medicine 29: 309–317). Logistic quantile regression models the quantiles of outcome variables that take on...

A common aim of epidemiological research is to assess the association between a particular exposure and a particular outcome, controlling for a set of additional covariates. This is often done by using a regression model for the outcome, conditional on exposure and covariates. A commonly used...

The use of flexible models for the relationship between a quantitative covariate and the response variable can be limited by the difficulty in interpret- ing the regression coefficients. In this article, we present a new postestimation command, xblc, that facilitates tabular and graphical...

In this article, I review Flexible Parametric Survival Analysis Using Stata: Beyond the Cox Model, by Patrick Royston and Paul C. Lambert (2011 [Stata Press]). Copyright 2013 by StataCorp LP.

A significant aspect of data modeling with categorical predictors is the definition of a saturated model. In fact, there are different ways of specifying it—the casewise, the contingency table, and the collapsing approaches—and they strictly depend on the unit of analysis considered. The...

Multiple-source data are often collected to provide better information of some underlying construct that is difficult to measure or likely to be missing. In this article, we describe regression-based methods for analyzing multiple-source data in Stata. We use data from the BROMS Cohort Study, a...