Showing 1 - 8 of 8
Competing-risks survival regression provides a useful alternative to Cox regression in the presence of one or more competing risks. For example, say that you are studying the time from initial treatment for cancer to recurrence of cancer in relation to the type of treatment administered and...
Persistent link: https://www.econbiz.de/10008487870
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...
Persistent link: https://www.econbiz.de/10005101316
Persistent link: https://www.econbiz.de/10005101339
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...
Persistent link: https://www.econbiz.de/10005103066
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...
Persistent link: https://www.econbiz.de/10005103077
Frailty models are used to model survival times in the presence of overdispersion or group-specific random effects. The latter are distinguished from the former by the term "shared" frailty models. With the release of Stata 7, estimation of parametric non-shared frailty models is now possible,...
Persistent link: https://www.econbiz.de/10005053283
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...
Persistent link: https://www.econbiz.de/10005053297
Stata’s approach to the analysis of data from complex surveys is unique in that it clearly separates the declaration of the design aspects of the survey (accomplished by svyset) from the actual analysis. Such an arrangement is ideal because the design characteristics of the data do not change...
Persistent link: https://www.econbiz.de/10005053601