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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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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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Fixed and random effects models
WIREs Computational Statistics, 2011AbstractTraditional 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 +2 more
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Modelling Clustered Heterogeneity: Fixed Effects, Random Effects and Mixtures
International Statistical Review, 2016SummaryAlthough each statistical unit on which measurements are taken is unique, typically there is not enough information available to account totally for its uniqueness. Therefore, heterogeneity among units has to be limited by structural assumptions.
Tutz, Gerhard, Oelker, Margret-Ruth
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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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Grouped effects estimators in fixed effects models
Journal of Econometrics, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bester, C. Alan, Hansen, Christian B.
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Fixed Effects Logistic Regression Model
2015If a researcher wants to know whether watching violent television has an impact on juvenile delinquency, that researcher could compare a student’s delinquency rate when he/she is watching violent television with his/her delinquency rate when not watching.
Jeffrey R. Wilson, Kent A. Lorenz
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Regression analysis: Fixed effects models
2016AbstractThis chapter discusses linear regression models with intercepts differing between individuals and/or periods. These differences, representing unobserved spatial and temporal heterogeneity, are represented by fixed parameters. The first part considers models with only fixed individual-specific heterogeneity, the second part also time-specific ...
Erik Biørn, Erik Biørn, Erik Biørn
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Estimating Autocorrelations in Fixed-Effects Models. [PDF]
, 1983 This paper discusses the estimation of serial correlation in fixed effects models for longitudinal data. Like time series data, longitudinal data often contain serially correlated error terms, but the autocorrelation estimators commonly used for time series, which are consistent as the length of the time series goes to infinity, are not consistent for ...
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