When analyzing a response variable at the presence of both factors and covariates, with potentially correlated responses and violated assumptions of the normal residual or the linear relationship between the response and the covariates, rank-based tests can be an option for inferential procedures instead of the parametric repeated measures analysis of covariance (ANCOVA) models. This article derives a rank-based method for multi-way ANCOVA models with correlated responses. The generalized estimating equations (GEE) technique is employed to construct the proposed rank tests. Asymptotic properties of the proposed tests are derived. Simulation studies confirmed the performance of the proposed tests.
机构:
Penn State Univ, Dept Human Dev & Family Studies, University Pk, PA 16802 USA
Penn State Univ, Methodol Ctr, University Pk, PA 16802 USAPenn State Univ, Dept Human Dev & Family Studies, University Pk, PA 16802 USA
Rovine, Michael J.
Molenaar, Peter C. M.
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Univ Amsterdam, Dept Dev Psychol, NL-1012 WX Amsterdam, NetherlandsPenn State Univ, Dept Human Dev & Family Studies, University Pk, PA 16802 USA
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US FDA, Ctr Drug Evaluat & Res, Off Biostat, Div Biostat 4, Rockville, MD 20857 USAUS FDA, Ctr Drug Evaluat & Res, Off Biostat, Div Biostat 4, Rockville, MD 20857 USA
Rashid, M. Mushfiqur
McKean, Joseph W.
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Western Michigan Univ, Dept Stat, Kalamazoo, MI 49008 USAUS FDA, Ctr Drug Evaluat & Res, Off Biostat, Div Biostat 4, Rockville, MD 20857 USA
McKean, Joseph W.
Kloke, John D.
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Univ Wisconsin, Dept Stat & Med Informat, Madison, WI 53706 USAUS FDA, Ctr Drug Evaluat & Res, Off Biostat, Div Biostat 4, Rockville, MD 20857 USA