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Serial Correlation and the Fixed Effects Model
The Review of Economic Studies, 1982This paper generalizes the Durbin-Watson type statistics to test the OLS residuals from the fixed effects model for serial independence. Also generalized are the tests proposed by Sargan and Bhargava for the hypothesis that the residuals form a random walk. A method for efficient estimation of the parameters is also developed.
Bhargava, A. +2 more
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Fixed-effect Versus Random-effects Models for Meta-analyses: Fixed-effect Models
European Urology Focus, 2023A 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 +2 more
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Fixed-effect Versus Random-effects Models for Meta-analyses: Random-effects Models
European Urology Focus, 2023Random-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 +2 more
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Latent Variable Models with Fixed Effects
Biometrics, 1996We 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
2021Deciding 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
2020This 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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Currency Unions and Trade: A PPML Re‐Assessment with High‐Dimensional Fixed Effects
Oxford Bulletin of Economics and Statistics, 2018Recent work on the effects of currency unions (CUs) on trade stresses the importance of using many countries and years in order to obtain reliable estimates.
Mario Larch +3 more
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Fixed Effect Models and Fixed Coefficient Models
1992As 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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