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 ?
FEM] is coefficient of the slope in fixed effect model, PREM is coefficient of slope in random effect model and Var is variance symbol.
2] > 50) indicated heterogeneity across studies, and then the random effect model was used for meta-analysis and to account for the possibility of heterogeneity between studies; otherwise, the fixed effect model was used.
When calculating the overall effect, the study showing a weight in random effect model below 5% was regarded as out-layer and not applied to analysis.
Table 4: The Random Effect Model Dependent Variable: LN_DEMO Variable Coefficient Std.
An alternative method of estimation is random effect model which assumes that the constants for each section are not fixed but are random.
01 level in the random effect model and significant at the 0.
Data on major cardiovascular events (death from cardiovascular causes, non-fatal myocardial infarction, nonfatal stroke, and all-cause mortality) were extracted and pooled with a random effect model.
A fixed effect model assumes differences in intercepts across groups or time periods, where as random effect model explores differences in error variances(Gujarati, 2003, Wooldridge, 2000)
We also tested the assumptions underlying the random effect model using a Hausman test.