random effects model

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random effects model

A statistical model that may be used in meta-analysis, in which both within-study sampling error (variance) and between-studies variation are included in assessing the uncertainty or confidence interval of the results of the meta-analysis.
References in periodicals archive ?
The fixed- or random-effects models were used for combining the calculated eradication rate values according to heterogeneity in the meta-analysis.
The researchers found that VGV was related to aggression using both fixed- and random-effects models. There was no evidence of publication bias.
Data were analyzed using both fixed-effects and random-effects models by Review Manager.
A high heterogeneity among the included studies was present; thus the random-effects models were applied.
Aspects of our analytic approach also reduced concerns about confounding, such as the use of spatial random-effects models. The standard Cox model yielded smaller estimates of the standard error for [PM.sub.2.5] than those produced by the spatial random-effects model, suggesting that there was unexplained spatial variation in mortality within the cohort.
"Flexible Random-Effects Models Using Bayesian Semi Parametric Models: Applications to Institutional Comparisons." Statistics in Medicine 26 (9): 2088-112.
If significant heterogeneity is present in the reported/included data, one may proceed with the following options: reporting a summary of reported/included data without further MA, subgroup and sensitivity analyses, and analyses using random-effects models (versus a fixed-effects model, which is appropriate for a homogeneous group of study results).
This article introduces the classical fixed-effects and random-effects models in MA and uses a meta-analysis about the use of lamotrigine in bipolar disorder [6] as an example to illustrate the step-by-step implementation of MA using R, an open source statistical software package that can be freely accessed from http://www.r-project.org.
Meta-analyses were performed with fixed-or random-effects models according to heterogeneity of studies.
I used it as an excuse to develop two spreadsheets for reliability analyses that could be checked with mixed models, which would be straightforward pure random-effects models to start with, but could then lead to more interesting mixtures of random and fixed effects.
Differences between the studies necessitated the use of random-effects models to pool estimates of effect.
Fixed-effects or random-effects models were used to pool the data according to heterogeneity.