
Symbolic Formulae for Linear Mixed Models
A statistical model is a mathematical representation of an often simplif...
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The correlation structure of mixed effects models with crossed random effects in controlled experiments
The design of experiments in psychology can often be summarized to parti...
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Analysis of Multivariate Data and Repeated Measures Designs with the R Package MANOVA.RM
The numerical availability of statistical inference methods for a modern...
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Some ttests for Nof1 trials with serial correlation
Nof1 trials allow inference between two treatments given to a single i...
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Scale mixture of skewnormal linear mixed models with withinsubject serial dependence
In longitudinal studies, repeated measures are collected over time and h...
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On the Reeb spaces of definable maps
We prove that the Reeb space of a proper definable map in an arbitrary o...
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PC priors for residual correlation parameters in onefactor mixed models
Lack of independence in the residuals from linear regression motivates t...
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A Note on Implementing a Special Case of the LEAR Covariance Model in Standard Software
Repeated measures analyses require proper choice of the correlation model to ensure accurate inference and optimal efficiency. The linear exponent autoregressive (LEAR) correlation model provides a flexible twoparameter correlation structure that accommodates a variety of data types in which the correlation withinsampling unit decreases exponentially in time or space. The LEAR model subsumes three classic temporal correlation structures, namely compound symmetry, continuoustime AR(1), and MA(1), while maintaining parsimony and providing appealing statistical and computational properties. It also supplies a plausible correlation structure for power analyses across many experimental designs. However, no commonly used statistical packages provide a straightforward way to implement the model, limiting its use to those with the appropriate programming skills. Here we present a reparameterization of the LEAR model that allows easily implementing it in standard software for the special case of data with equally spaced temporal or spatial intervals.
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