fixed-effects modelrandom-effects modelstructural equation modelingThis study compared fixed-effects (FE) and random-effects (RE) models in meta-analysis for synthesizing multivariate effect sizes under the framework of structural equation modeling. Monte Carlo simulations were conducted to examine the ...
Fixed- versus random-effects models in meta-analysis: model properties and an empirical comparison of differences in results. Today most conclusions about cumulative knowledge in psychology are based on meta-analysis. We first present an examination of the important statistical di... DFL Schmidt,IS ...
Next, fixed effects and random effects methods will be used in combining the effect size estimates when effect size estimates can be calculated. 55 Randomised Controlled Trials (RCTs) on Tamoxifen treatment for early breast cancer patients are observed according to recurrences and mortality cases, ...
In the present paper we empirically assess the quality of several small-area estimators in the setting in which the area effects are treated as fixed. We consider two settings: one that draws samples from a theoretical population, and another that draws samples from an empirical population of a...
re RE options Conditional fixed-effects (FE) model xtpoisson depvar indepvars if in weight , fe FE options Population-averaged (PA) model xtpoisson depvar indepvars if in weight , pa PA options 1 2 xtpoisson — Fixed-effects, random-effects, and population-averaged Poisson models RE option...
Extenions of the model incorporate both fixed-effect and random-effect models of population sampling at multiple hierarchical levels with multiple alleles per... Kent,E.,Holsinger - 《Hereditas》 被引量: 232发表: 2004年 Comparison of hierarchical and marginal likelihood estimators for binary outcomes...
and the remainingS−Rparameters are assumed to be fixed. We also propose an extended version of the model that includes effects of covariates on MPT model parameters. Because the likelihood functions of both versions of the model are too complex to be tractable, we propose three numerical metho...
Comparison of statistical inferences from the DerSimonian–Laird and alternative random‐effects model meta‐analyses – an empirical assessment of 920 Coc... In random-effects model meta-analysis, the conventional DerSimonian鈥揕aird (DL) estimator typically underestimates the between-trial variance....
When some of the regressors in a panel data model are correlated with the random individual effects, the random effect (RE) estimator becomes inconsistent while the fixed effect (FE) estimator is consistent. Depending on the various degree of such correlation, we can combine the RE estimator and...
A second set of methods has the goal of quantifying GCE in comparison to fixed effects. One simple approach, which we call Individual Outcome Measures (IOM), involves calculating intervals for the mean outcome (e.g. probability) as the cluster random effect ranges across its (usually normal) ...