Frailty models are the survival data analog to regression models, which account for heterogeneity and random effects. A frailty is a latent multiplicative effect on the hazard function and is assumed to have unit mean and variance theta, which is estimated along with the other model parameters....

In the past decade, many statistical methods have been proposed for the analysis of case-control genetic data with an emphasis on haplotype-based disease association studies. Most of the methodology has concentrated on the estimation of genetic (haplotype) main effects. Most methods accounted...

With the release of Stata 7, the glm command for fitting generalized linear models underwent a substantial overhaul. Stata 7 glm contains an expanded array of variance estimators, regression diagnostics, and other enhancements. The overhaul took place to coincide with the release of Hardin and...

Local polynomial regression is a generalization of local mean smoothing as described by Nadaraya (1964)andWat s on (1964). Instead of fitting a local mean, one instead fits a local pth-order polynomial. Calculations for local polynomial regression are naturally more complex than those for local...

With the release of Stata 7, the capabilities of glm were greatly enhanced. Among the improvements was the ability for users to program their own custom link and variance functions. Whereas previously glm was used primarily as a platform on which to compare the results of standard regression...

With the release of Stata 7, the capabilities of glm were greatly enhanced. Among the improvements was the ability for users to program their own custom link and variance functions. Whereas previously glm was used primarily as a platform on which to compare the results of standard regression...

Stata’s xtmixed command can be used to fit mixed models, models that contain both fixed and random effects. The fixed effects are merely the coefficients from a standard linear regression. The random effects are not directly estimated but summarized by their variance components, which are...