12/2/2023 0 Comments Power calculation stataStandard meta-analysis combines estimates of one parameter over several studies. Multivariate random-effects meta-analysis The data in each arm of each study are assumed to be available either as binomial counts (successes/total), or as mean, standard deviation and number of individuals for a quantitative variable.Īuthor / Maintainer: Ian White, META-ANALYSIS Imports data and runs contrast-based network meta-analysis (using MVMETA or METAREG), assesses inconsistency, and graphs the data and results. Suite of programs for network meta-analysis Maintainer: Ian White, Clinical Trials METHODOLOGY The new method is based on creating a weighted data set containing the expected counts per person, and analysing it with 'ologit'.Īuthors: White I, Marley-Zagar E, Morris T, Parmar MKB, Babiker AG The existing method is that of Whitehead (1993). The command implements an existing and a new method. Sample s ize calculation for an ordered categorical outcomeĪRTCAT calculates sample size or power for a clinical trial or similar experiment with an ordered categorical outcome, where analysis is by the proportional odds model. Projections of power and events (ARTPEP) are provided. In November 2021, ARTBIN underwent a major upgrade to provide sample size calculation for a range of trial types, with extended statistical tests and methods available.Īuthors: Babiker A, Bartel S, Royston P, Marley-Zagar E Trend tests over dose levels of a covariate are supported. Multiple treatment groups with joint tests are allowed. ART accommodates complex features including non-proportional hazards, cross-over between treatments, loss to follow-up, staggered entry, flexible patient accrual patterns, and several different 'flavors' of the logrank test. Maintainer: Babak Choodari-Oskooei, Clinical Trials METHODOLOGYĬomplex sample size calculation in randomised trialsĪRT is a menu- and command-driven set of programs to compute sample size or power for randomized controlled trials with a time-to-event (ARTSURV) or binary (ARTBIN) outcome measure. Specify the design (sample size, duration, overall operating characteristics) of a multi-arm, multi-stage (MAMS) trial utilizing an intermediate outcome (I-outcome) at the intermediate stages and a definitive or primary outcome (D-outcome) at the final stage, nstagebin for binary responses.Īuthors: Royston P, Barthel S, Oskooei-Choodari B, Blenkinsop A, Bratton D nstageĭesign of multi-arm,multi-stage (MAMS) trials for time-to-event outcomes Therefore, we often develop user-written code for use with commonly-used statistical software to accompany our work. New methodological solutions need to be straightforwardly demonstrated and implemented We are keenly aware that new methodological solutions need to be straightforwardly demonstrated and implemented, by ourselves and by others, in order to be taken up by the wider research community.
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