TY - JOUR
T1 - A unified approach to rank tests for mixed models
AU - Akritas, Michael G.
AU - Brunner, Edgar
N1 - Funding Information:
* Corresponding author. l Part of this paper was prepared during the second author's visit to the Department of Statistics, Pennsylvania State University, State College. He likes to thank the Department of Statistics for its hospitality and support. The collaboration was supported in part by NATO grant CRG 950178. The authors are grateful to the referees and to the associate editor for their helpful comments which improved the first draft of the paper considerably.
PY - 1997/6/16
Y1 - 1997/6/16
N2 - The nonparametric version of the classical mixed model is considered and the common hypotheses of (parametric) main effects and interactions are reformulated in a nonparametric setup. To test these nonparametric hypotheses, the asymptotic distributions of quadratic forms of rank statistics are derived in a general framework which enables the derivation of the statistics for the nonparametric hypotheses of the fixed treatment effects and interactions in an arbitrary mixed model. The procedures given here are not restricted to semiparametric models or models with additive effects. Moreover, they are robust to outliers since only the ranks of the observations are needed. They are also applicable to pure ordinal data and since no continuity of the distribution functions is assumed, they can also be applied to data with ties. Some approximations for small sample sizes are suggested and analyzed in a simulation study. The application of the statistics and the interpretation of the results is demonstrated in several worked-out examples where some data sets given in the literature are re-analyzed.
AB - The nonparametric version of the classical mixed model is considered and the common hypotheses of (parametric) main effects and interactions are reformulated in a nonparametric setup. To test these nonparametric hypotheses, the asymptotic distributions of quadratic forms of rank statistics are derived in a general framework which enables the derivation of the statistics for the nonparametric hypotheses of the fixed treatment effects and interactions in an arbitrary mixed model. The procedures given here are not restricted to semiparametric models or models with additive effects. Moreover, they are robust to outliers since only the ranks of the observations are needed. They are also applicable to pure ordinal data and since no continuity of the distribution functions is assumed, they can also be applied to data with ties. Some approximations for small sample sizes are suggested and analyzed in a simulation study. The application of the statistics and the interpretation of the results is demonstrated in several worked-out examples where some data sets given in the literature are re-analyzed.
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U2 - 10.1016/s0378-3758(96)00177-2
DO - 10.1016/s0378-3758(96)00177-2
M3 - Article
AN - SCOPUS:0031575047
SN - 0378-3758
VL - 61
SP - 249
EP - 277
JO - Journal of Statistical Planning and Inference
JF - Journal of Statistical Planning and Inference
IS - 2
ER -