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Journal of the American Statistical Association Volume 95, 2000 - Issue 449
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Theory and Method

Asymptotics for Analysis of Variance When the Number of Levels is Large

Michael Akritas Department of Statistics, The Pennsylvania State University, State College, PA, 16802
&
Steven Arnold Department of Statistics, The Pennsylvania State University, State College, PA, 16802
Pages 212-226 | Received 01 Jun 1997, Published online: 17 Feb 2012

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Xiaoli Kong & Solomon W. Harrar. (2020) High-dimensional rank-based inference. Journal of Nonparametric Statistics 32:2, pages 294-322.
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Chun-Lung Su. (2017) Asymptotic posterior distributions for balanced nested multi-way models with a large number of main effect levels. Communications in Statistics - Theory and Methods 46:19, pages 9425-9440.
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Solomon W. Harrar & John Z. Hossler. (2016) Methods for high-dimensional multivariate and multi-group repeated measures data under non-normality. Statistics 50:5, pages 1056-1074.
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Bilgehan Güven. (2014) Testing for random effect in the Fuller–Battese model. Statistics 48:4, pages 802-814.
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Trent Gaugler & MichaelG. Akritas. (2012) Mixed Effects Designs: The Symmetry Assumption and Missing Data. Journal of the American Statistical Association 107:499, pages 1230-1238.
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Haiyan Wang & Michael G. Akritas. (2009) Rank tests in heteroscedastic multi-way HANOVA. Journal of Nonparametric Statistics 21:6, pages 663-681.
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Lan Wang, Michael G. Akritas & Ingrid Van Keilegom. (2008) An ANOVA-type nonparametric diagnostic test for heteroscedastic regression models. Journal of Nonparametric Statistics 20:5, pages 365-382.
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Bilgehan Güven. (2006) The limiting distribution of the F-statistic from nonnormal universes. Statistics 40:6, pages 545-557.
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Haiyan Wang & Michael G. Akritas. (2004) Rank tests for anova with large number of factor levels. Journal of Nonparametric Statistics 16:3-4, pages 563-589.
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