Analysis of Variance for Three-Way Unbalanced Mixed Effects Interactive Model
- 1 Department of Statistics, Michael Okpara University of Agriculture Umudike, Umuhia, Nigeria
- 2 Department of Statistics, Michael Okpara University of Agriculture Umudike, Umuhia, Nigeria
- 3 Department of Statistics, Federal College of Agriculture Ishiagu, Ebonyi State, Nigeria
Abstract
In the study, a method of solving ANOVA problems based on an unbalanced three-way mixed effects model with interaction for data when factors A and B are fixed, and factor C is random was presented, and the required EMS was derived. Under each of the appropriate null hypotheses, it was observed that none of the derived EMS was unbiased for the other. Unbiased estimators of the mean squares were determined to test hypotheses. With the unbiased estimators, appropriate F-statistics as well as their corresponding pseudo-degrees of freedom were obtained. The theoretical results presented in the paper w ere illustrated using a numerical example.
- Kherad-Pajouh, S. and Renaud, O. (2010) An Exact Permutation Method for Testing Any Effect in Balanced and Unbalanced Fixed Effect ANOVA. Computational Statistics & Data Analysis, 54, 1881-1893. https://doi.org/10.1016/j.csda.2010.02.015
- Eze, F.C. and Chigbu, P.E. (2012) Unbalanced Two-Way Random Model with Integer-Value Degrees of Freedom. Journal of Natural Sciences Research, 2, 100-107.
- Eze, F.C and Nwankwo, E.U. (2016) Analysis of Variance in an Unbalanced Two-Way Mixed Effect Interactive Model. Open Journal of Statistics, 6, 310-319. https://doi.org/10.4236/ojs.2016.62027
- Sahai, H. and Ageel, M.I. (2000) Analysis of Variance for Fixed Random and Mixed Effect Model. Birkhauser, Boston, Basel, Berlin.
- Sahai, H. and Ojeda M.M. (2004) Analysis of Variance for Random Models: Unbalanced Data. 1st Edition, Birkuhauser, Boston, 480.
- Satterthwaite, F.E. (1946) An Approximate Distribution of Estimates of Variance Components. Biometrics Bulletin, 2, 110-114. https://doi.org/10.2307/3002019