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Interpreting Parameters in the Logistic Regression Model with Random Effects
Biometrics, 2000Summary.Logistic regression with random effects is used to study the relationship between explanatory variables and a binary outcome in cases with nonindependent outcomes. In this paper, we examine in detail the interpretation of both fixed effects and random effects parameters.
Esben Budtz-Jørgensen +2 more
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The Validity of Polynomial Regression in the Random Regression Model
Review of Educational Research, 1978Sockloff (1976), in reviewing the appropriateness of fixed and random models in regression analysis, has concluded "that the analysis of nonlinearity via polynomial and product regression should be limited to experimental studies" (p. 288), and that, "[r]egarding the analysis of nonlinearity in observational data under the Random Model, the Random ...
Elliot M. Cramer, Mark I. Appelbaum
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Random effects in ordinal regression models
Computational Statistics and Data Analysis, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gerhard Tutz
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Random Regression Coefficient Models
2020This chapter describes a modification of the nested error regression model having random regression coefficients. We can intuitively expect that the slope parameters of some explanatory variable are not constant and therefore they should take different values in different domains.
Domingo Morales +3 more
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A random‐effects regression model for meta‐analysis
Statistics in Medicine, 1995AbstractMany meta‐analyses use a random‐effects model to account for heterogeneity among study results, beyond the variation associated with fixed effects. A random‐effects regression approach for the synthesis of 2 × 2 tables allows the inclusion of covariates that may explain heterogeneity.
C S, Berkey +3 more
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