Analyzing the factorial experiments variances with the repeated values in a practical application

Document Type : Research Paper

Authors

Department of Business Administration, Al-Kut University College, Wasit, Iraq

Abstract

With the repeated values, that the factorial experiments will be in three nested factors. And, the third factor is presented by experimental units (subjects). The repeated values or the experimental unit treatments definitely can be taken. These treatments can be dealt with as a fourth factor. Actually, these kinds of experiments have been analyzed in factorial ways, which are presented by the F test. That can be taken place in the condition of variance analysis to the repeated values experiments and in case there is no condition fitting in, we may use non-factorial ways which are presented by shifting into ranks. Therefore, the aim of this research is to make an analyzed study for this kind of factorial ways or non-factorial. This kind of experiment can be applied to Thalassemia in Thi-Qar province.

Keywords

[1] M. Audibert, Y. He and J. Mathonnat, Income growth, price variation and health care Demand: A mixed Logit model applied to tow-period comparison in rural China, CERDI, Etudes et Documents (2011) 1-31.
[2] M.J. Crowder and D.J. Hand, Analysis of repeated measures, Routledge, JASA 89 (2017) 680–686.
[3] J. Feys, New nonparametric rank tests for interactions in factorial designs with repeated measures, J. Modern Appl. Stat. Meth., 15 (2016) 6–12.
[4] W. Hager, Some common features and some differences between the parametric ANOVA for repeated measures and the Friedman ANOVA for ranked data, Psychol. Sci. 49 (2007) 209–222.
[5] H. Khodaei and T. M. Rassias, Approximately generalized additive functions in several variables, Int. J. Nonlinear Anal. Appl. 1 (2010) 22–41.
[6] G. Shukla and V. Kumar, Different methods of analyzing multiple samples repeated measures data, J. Reliab. Stat. Stud. 5 (2012) 83-93.
[7] G.L. Lacroix and G. Gigu`ere, Formatting data files for repeated-measures analyses in SPSS: Using the Aggregate and Restructure procedures, Tutor. Quant. Meth. Psych. 2 (2006) 20–25.
[8] P.Y. Lin and Z. Ying, Semiparametric and Non-parametric Regression analysis of longitudinal data, JASA, 96 (2001).
[9] K. Noguchi, Y.R. Gel, E. Brunner and F. Konietschke, an R software package for the nonparametric analysis of longitudinal data in factorial experiments, J. Stat. Software 50(2012) 1–23.
[10] A. Bodaghi, T.M. Rassias and A. Zivari-Kazempour, A fixed point approach to the stability of additive-quadraticquartic functional equations, Int. J. Nonlinear Anal. Appl. 11 (2020) 17–28.
[11] J. M. Weinberg and S. W. Lagakos, Efficiency comparison of rank and permutation test based on summary statistics computed from repeated measures data, Stat. 20 (2001) 705–731.
Volume 13, Issue 1
March 2022
Pages 921-936
  • Receive Date: 10 March 2021
  • Revise Date: 15 April 2021
  • Accept Date: 28 May 2021