Meta-Regression in Stata

Robust Regression in Stata

In regression analysis, the presence of outliers in the data set can strongly distort the classical least squares estimator and lead to unreliable results. To deal with this, several robust-to-outliers methods have been proposed in the statistical literature. In Stata, some of these methods are available through the commands rreg and qreg. Unfortunately, these methods only resist to some specif...

Meta-analysis in Stata using gllamm.

There are several user-written programs for performing meta-analysis in Stata (Stata Statistical Software: College Station, TX: Stata Corp LP). These include metan, metareg, mvmeta, and glst. However, there are several cases for which these programs do not suffice. For instance, there is no software for performing univariate meta-analysis with correlated estimates, for multilevel or hierarchica...

Graphical Tools for Network Meta-Analysis in STATA

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The eva...

Regression models for categorical dependent variables using Stata, 2nd Edition

Boosted Regression (Boosting): An introductory tutorial and a Stata plugin

Boosting, or boosted regression, is a recent data mining technique that has shown considerable success in predictive accuracy. This article gives an overview over boosting and introduces a new Stata command, boost, that implements the boosting algorithm described in Hastie et al. (2001, p. 322). The plugin is illustrated with a Gaussian and a logistic regression example. In the Gaussian regress...