Literature DB >> 7973237

The application of REML in clinical trials.

H K Brown1, R A Kempton.   

Abstract

Residual maximum likelihood (REML) is a technique for estimating variance components in multi-classified data. In contrast to analysis of variance it can be routinely applied to unbalanced data and avoids some of the problems of biased variance estimates found with standard maximum likelihood estimation. The full REML method is of particular value for the analysis of unbalanced clinical trials as it allows recovery of all the available information on treatment effects which can lead to significant improvements in their precision. The use of REML has until recently been limited by heavy computational requirements and lack of readily available software. This is no longer such a restriction, however, as REML procedures are now available in several widely-used statistical packages, including BMDP, Genstat and SAS. This paper describes the REML technique and discusses its application to three common types of clinical trial: crossover, repeated measures and multicentre.

Mesh:

Year:  1994        PMID: 7973237     DOI: 10.1002/sim.4780131602

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  6 in total

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Authors:  S H Alusi; A Macerollo; Colum D MacKinnon; John C Rothwell; Peter G Bain
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2.  Comparing methods to estimate treatment effects on a continuous outcome in multicentre randomized controlled trials: a simulation study.

Authors:  Rong Chu; Lehana Thabane; Jinhui Ma; Anne Holbrook; Eleanor Pullenayegum; Philip James Devereaux
Journal:  BMC Med Res Methodol       Date:  2011-02-21       Impact factor: 4.615

3.  Basal cell carcinoma of the face: surgery or radiotherapy? Results of a randomized study.

Authors:  M F Avril; A Auperin; A Margulis; A Gerbaulet; P Duvillard; E Benhamou; J C Guillaume; R Chalon; J Y Petit; H Sancho-Garnier; M Prade; J Bouzy; D Chassagne
Journal:  Br J Cancer       Date:  1997       Impact factor: 7.640

4.  One-stage random effects meta-analysis using linear mixed models for aggregate continuous outcome data.

Authors:  Katerina Papadimitropoulou; Theo Stijnen; Olaf M Dekkers; Saskia le Cessie
Journal:  Res Synth Methods       Date:  2019-01-08       Impact factor: 5.273

5.  Sensitivity of methods for analyzing continuous outcome from stratified cluster randomized trials - an empirical comparison study.

Authors:  Sayem Borhan; Rizwana Mallick; Mershen Pillay; Harsha Kathard; Lehana Thabane
Journal:  Contemp Clin Trials Commun       Date:  2019-07-05

Review 6.  Effects of ocean acidification on Antarctic marine organisms: A meta-analysis.

Authors:  Alyce M Hancock; Catherine K King; Jonathan S Stark; Andrew McMinn; Andrew T Davidson
Journal:  Ecol Evol       Date:  2020-04-16       Impact factor: 2.912

  6 in total

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