Statistical tests with accurate size and power for balanced linear mixed models.
about
POWERLIB: SAS/IML Software for Computing Power in Multivariate Linear ModelsAvoiding bias in mixed model inference for fixed effects.Evaluating the robustness of repeated measures analyses: the case of small sample sizes and nonnormal data.Separability tests for high-dimensional, low sample size multivariate repeated measures data.Multivariate test power approximations for balanced linear mixed models in studies with missing dataA circular LEAR correlation structure for cyclical longitudinal data.Confidence regions for repeated measures ANOVA power curves based on estimated covariance.Kronecker product linear exponent AR(1) correlation structures for multivariate repeated measures.Chronic pain self-management support with pain science education and exercise (COMMENCE): study protocol for a randomized controlled trial.An R2 statistic for fixed effects in the linear mixed modelA linear exponent AR(1) family of correlation structuresPower calculation for overall hypothesis testing with high-dimensional commensurate outcomes.GLIMMPSE: Online Power Computation for Linear Models with and without a Baseline Covariate.Global hypothesis testing for high-dimensional repeated measures outcomes.Selecting a sample size for studies with repeated measuresApproximating the Geisser-Greenhouse sphericity estimator and its applications to diffusion tensor imaging.Random-effects linear modeling and sample size tables for two special crossover designs of average bioequivalence studies: the four-period, two-sequence, two-formulation and six-period, three-sequence, three-formulation designs.On the analysis of very small samples of Gaussian repeated measurements: an alternative approach.Internal pilot design for balanced repeated measures.Effectiveness of a transdiagnostic individually tailored Internet-based and mobile-supported intervention for the indicated prevention of depression and anxiety (ICare Prevent) in Dutch college students: study protocol for a randomised controlled tr
P2860
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P2860
Statistical tests with accurate size and power for balanced linear mixed models.
description
2007 nî lūn-bûn
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2007年の論文
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2007年学术文章
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2007年学术文章
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2007年学术文章
@zh-hans
2007年学术文章
@zh-my
2007年学术文章
@zh-sg
2007年學術文章
@yue
2007年學術文章
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2007年學術文章
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name
Statistical tests with accurate size and power for balanced linear mixed models.
@en
Statistical tests with accurate size and power for balanced linear mixed models.
@nl
type
label
Statistical tests with accurate size and power for balanced linear mixed models.
@en
Statistical tests with accurate size and power for balanced linear mixed models.
@nl
prefLabel
Statistical tests with accurate size and power for balanced linear mixed models.
@en
Statistical tests with accurate size and power for balanced linear mixed models.
@nl
P2093
P356
P1476
Statistical tests with accurate size and power for balanced linear mixed models.
@en
P2093
Douglas J Taylor
Keith E Muller
Lloyd J Edwards
Sean L Simpson
P2860
P304
P356
10.1002/SIM.2827
P407
P577
2007-08-01T00:00:00Z