Results 241 to 250 of about 4,435,686 (301)

Fixed-effect Versus Random-effects Models for Meta-analyses: Fixed-effect Models

European Urology Focus, 2023
A fixed-effect model considers a common underlying effect size for all the studies included in a meta-analysis. In the face of appreciable between-study heterogeneity, a fixed-effect model is a valuable tool when precision is the priority.
Hadi Mostafaei, Morteza Ghojazadeh, Sakineh Hajebrahimi   +2 more
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Fixed-effect Versus Random-effects Models for Meta-analyses: Random-effects Models

European Urology Focus, 2023
Random-effects models can account for variability both within and between studies. This makes them suitable for meta-analyses in surgery, where there is often significant heterogeneity between studies or heterogeneity owing to intrinsic differences attributable to patient or population factors.
Alex L.E. Halme, Kristen McAlpine, Alberto Martini   +2 more
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Latent Variable Models with Fixed Effects

Biometrics, 1996
We discuss latent variable models that allow for fixed effect covariates, as well as covariates affecting the latent variable directly. Restricted maximum likelihood and maximum likelihood are used to estimate model parameters. A generalized likelihood ratio test can be used to test significance of the covariates effecting the latent outcomes.
Sammel, Mary Dupuis, Ryan, Louise M.
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Fixed- and Random-Effects Models

2021
Deciding whether to use a fixed-effect model or a random-effects model is a primary decision an analyst must make when combining the results from multiple studies through meta-analysis. Both modeling approaches estimate a single effect size of interest.
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Fixed-Effects Regression Modeling

2020
This chapter presents fixed-effects regression modeling as a family of methods that describe a dependent variable in terms of one or more independent variables. The chapter focuses on multiple linear regression and on binomial logistic regression, discussing examples of regression analyses on the basis of corpus-linguistic data.
Martin Hilpert, Damián E. Blasi
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Fixed Effect Models and Fixed Coefficient Models

1992
As noted in the introductory chapter, the simplest and most intuitive way to account for individual and/or time differences in behaviour, in the context of a panel data regression problem, is to assume that some of the regression coefficients are allowed to vary across individuals and/or through time.
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Fixed and random effects models

WIREs Computational Statistics, 2011
AbstractTraditional linear regression at the level taught in most introductory statistics courses involves the use of ‘fixed effects’ as predictors of a particular outcome. This treatment of the independent variable is often sufficient. However, as research questions have become more sophisticated, coupled with the rapid advancement in computational ...
Matthew J. Gurka, George A. Kelley, Lloyd J. Edwards   +2 more
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