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Repeated measurements

A repeated-measurements study is one in which subjects (animals, people, plots, etc) are observed on several occasions. Each subject usually receives some randomly allocated treatment, either at the outset or repeatedly through the investigation, and is then observed at successive occasions to see how the treatment effects develop. One way to analyse data sets like this is to use Genstat’s REML facilities to model the correlation structure over time.

    REML fits a variance-component model by residual (or restricted) maximum likelihood
    VCOMPONENTS defines the model for REML
    VSTRUCTURE defines a variance structure for random effects in a REML model

Alternatively, Genstat has procedures for customized plotting of the observations (or profiles) against time, repeated measures analysis of variance, analyses based on ante-dependence structure or generalized estimating equations, and regression or nonlinear modelling of data where the residuals follow an AR1 or power-distance correlation model.

    ANTORDER assesses order of ante-dependence for repeated measures data
    ANTTEST calculates overall tests based on a specified order of ante-dependence
    AREPMEASURES produces an analysis of variance for repeated measurements
    CUMDISTRIBUTION fits frequency distributions to accumulated counts
    DREPMEASURES plots profiles and differences of profiles for repeated measurements
    GEE fits models to longitudinal data by generalized estimating equations
    NLAR1 fits curves with an AR1 or a power-distance correlation model
    RAR1 fits regressions with an AR1 or a power-distance correlation model
    VORTHPOLYNOMIAL calculates orthogonal polynomial time-contrasts for repeated measurements
Updated on May 20, 2019

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