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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.
Larsen, Klaus +3 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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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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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 regression model for multivariate random length data
Statistics in Medicine, 1999Multivariate random length data occur when we observe multiple measurements of a quantitative variable and the variable number of these measurements is also an observed outcome for each experimental unit. For example, for a patient with coronary artery disease, we may observe a number of lesions in that patient's coronary arteries, along with ...
H X, Barnhart +2 more
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Prediction in Random Coefficient Regression Models
Biometrical Journal, 1990AbstractMuch attention has been given to the problem of predicting future observations for some individual within a random coefficient regression (RCR) model, using the previous observations on that individual as well as the information from the rest of the data material.
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-optimal designs in random coefficient regression models
Statistics & Probability Letters, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Liu, Xin +2 more
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Random effects in ordinal regression models
Computational Statistics & Data Analysis, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tutz, Gerhard, Hennevogl, Wolfgang
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Drop-outs and a random regression model
Journal of Biopharmaceutical Statistics, 1997The implications of drop-outs for power of random regression model (RRM) tests of significance for differences in the rate of change produced by two treatments in a randomized parallel-groups design were investigated by Monte Carlo simulation methods. The two-stage RRM fitted a least squares linear regression equation to all of the available data for ...
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