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Power of Models in Longitudinal Study: Findings From a Full-Crossed Simulation Design
by
Fang, Hua
, Barcikowski, Robert S.
, Brooks, Gordon P.
, Rizzo, Maria L.
, Espy, Kimberly Andrews
in
Clinical trials
/ Comparative Analysis
/ Correlation
/ Covariance
/ Covariance matrices
/ covariance structure
/ Data analysis
/ Drug abuse
/ Economic models
/ Educational research
/ Growth models
/ hierarchical multivariate linear models
/ Linear models
/ Longitudinal data
/ Longitudinal Studies
/ longitudinal study
/ Mathematical Models
/ Measurement
/ MEASUREMENT, STATISTICS, AND RESEARCH DESIGN
/ Modeling
/ Monte Carlo Methods
/ Multilevel models
/ Multivariate Analysis
/ power analysis
/ Sample size
/ Simulation
/ Simulations
/ Statistical Analysis
/ Studies
/ Substance abuse treatment
/ traditional repeated measures
2009
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Power of Models in Longitudinal Study: Findings From a Full-Crossed Simulation Design
by
Fang, Hua
, Barcikowski, Robert S.
, Brooks, Gordon P.
, Rizzo, Maria L.
, Espy, Kimberly Andrews
in
Clinical trials
/ Comparative Analysis
/ Correlation
/ Covariance
/ Covariance matrices
/ covariance structure
/ Data analysis
/ Drug abuse
/ Economic models
/ Educational research
/ Growth models
/ hierarchical multivariate linear models
/ Linear models
/ Longitudinal data
/ Longitudinal Studies
/ longitudinal study
/ Mathematical Models
/ Measurement
/ MEASUREMENT, STATISTICS, AND RESEARCH DESIGN
/ Modeling
/ Monte Carlo Methods
/ Multilevel models
/ Multivariate Analysis
/ power analysis
/ Sample size
/ Simulation
/ Simulations
/ Statistical Analysis
/ Studies
/ Substance abuse treatment
/ traditional repeated measures
2009
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Do you wish to request the book?
Power of Models in Longitudinal Study: Findings From a Full-Crossed Simulation Design
by
Fang, Hua
, Barcikowski, Robert S.
, Brooks, Gordon P.
, Rizzo, Maria L.
, Espy, Kimberly Andrews
in
Clinical trials
/ Comparative Analysis
/ Correlation
/ Covariance
/ Covariance matrices
/ covariance structure
/ Data analysis
/ Drug abuse
/ Economic models
/ Educational research
/ Growth models
/ hierarchical multivariate linear models
/ Linear models
/ Longitudinal data
/ Longitudinal Studies
/ longitudinal study
/ Mathematical Models
/ Measurement
/ MEASUREMENT, STATISTICS, AND RESEARCH DESIGN
/ Modeling
/ Monte Carlo Methods
/ Multilevel models
/ Multivariate Analysis
/ power analysis
/ Sample size
/ Simulation
/ Simulations
/ Statistical Analysis
/ Studies
/ Substance abuse treatment
/ traditional repeated measures
2009
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Power of Models in Longitudinal Study: Findings From a Full-Crossed Simulation Design
Journal Article
Power of Models in Longitudinal Study: Findings From a Full-Crossed Simulation Design
2009
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Overview
Because the power properties of traditional repeated measures and hierarchical multivariate linear models have not been clearly determined in the balanced design for longitudinal studies in the literature, the authors present a power comparison study of traditional repeated measures and hierarchical multivariate linear models under 3 variance-covariance structures. The results from a full-crossed simulation design suggest that traditional repeated measures have significantly higher power than do hierarchical multivariate linear models for main effects, but they have significantly lower power for interaction effects in most situations. Significant power differences are also exhibited when power is compared across different covariance structures.
Publisher
Heldref,Heldref Publications,Taylor & Francis Inc
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