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Analysis of longitudinal data: Random coefficient regression modelling
Author(s) -
Rutter Carolyn M.,
Elashoff Robert M.
Publication year - 1994
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780131204
Subject(s) - statistics , regression analysis , longitudinal data , regression , random effects model , econometrics , cross sectional regression , computer science , mathematics , data mining , polynomial regression , medicine , meta analysis
We review random coefficient regression (RCR) models and methods for fitting these models from an applications perspective. Methods for data with exponential family distributions are presented with the Gaussian distribution as a special case. Attention is given to interpretation of fixed effects and the correlation structures implied by RCR models. Estimation methods are presented with computational approaches. Problems associated with testing fixed effects include accurate variance estimation and robustness to misspecification of the covariance structure. Methods for model selection and assessment are presented. An example is used to demonstrate recommended approaches.