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Royston and Parmar (2002, Statistics in Medicine 21: 2175 – 2197) developed a class of flexible parametric survival models that were programmed in Stata with the stpm command (Royston, 2001, Stata Journal 1:1-28). In this article, we introduce a new command, stpm2, that extends the...
Persistent link: https://www.econbiz.de/10004982802
In this paper, we describe a new Stata command, stlh, which estimates and tests for the significance of the time-varying regression coefficients in Aalen's linear hazards model; see Aalen (1989). We see two potential uses for this command. One may use it as an alternative to a proportional...
Persistent link: https://www.econbiz.de/10005583252
We provide a program to illustrate interactions between treatment and covariates or between two covariates by using forest plots under either the Cox proportional hazards or the logistic regression model. The program is flexible in both the possibility of illustrating more than one interaction...
Persistent link: https://www.econbiz.de/10005748361
Simulation of realistic censored survival times is challenging. Most research studies use highly simplified models, such as the exponential, that do not adequately reflect the patterns of time to event and censoring seen in real datasets. In this article, I present a general method of simulating...
Persistent link: https://www.econbiz.de/10010630742
We present menu- and command-driven Stata programs for the calculation of sample size, number of events, and trial duration for a novel type of clinical trial design with a time-to-event outcome and two or more experimental arms. The approach is based on terminating accrual of patients to...
Persistent link: https://www.econbiz.de/10008474152
We present a menu-driven Stata program for the calculation of sample size or power for complex clinical trials with a survival time or a binary outcome. The features supported include up to six treatment arms, an arbitrary time-to- event distribution, fixed or time-varying hazard ratios, unequal...
Persistent link: https://www.econbiz.de/10005568835
Royston and Babiker (2002) presented a menu-driven Stata program for the calculation of sample size or power for complex clinical trial designs under a survival time or binary outcome. In the present article, the package is updated to Stata 8 under the new name ART. Furthermore, the program has...
Persistent link: https://www.econbiz.de/10005568865