Missing Value Estimation in a Nested-Factorial Design with Three Factors

  • Emmanuel W. Okereke Department of Statistics, Michael Okpara University of Agriculture, Umudike
  • Emmanuel J. Ekpenyong Department of Statistics, Michael Okpara University, Umudike, Nigeria
  • Chukwuma Nwaogu Department of Statistics, Michael Okpara University, Umudike, Nigeria

Abstract

When faced with unbalanced data, it is often necessary to estimate the necessary missing
values before the application of the analysis of variance technique. Previous studies have shown
that dierent designs require dierent missing value estimators. With the introduction of some
relatively new statistical designs, it has become expedient to derive missing value estimators
for such designs. In this study, least squares estimators of missing values in a three-factor
nested-factorial design are derived. Properties of the estimators are equally determined. A
numerical example is given to show the application of the theoretical results obtained in this
paper. Our empirical results establish the appropriateness of the missing value estimation
method presented in this study.

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Published
Jul 26, 2018
How to Cite
W. OKEREKE, Emmanuel; J. EKPENYONG, Emmanuel; NWAOGU, Chukwuma. Missing Value Estimation in a Nested-Factorial Design with Three Factors. Trends Journal of Sciences Research, [S.l.], v. 3, n. 1, p. 10-17, july 2018. ISSN 2377-8083. Available at: <http://tjsr.org/journal/index.php/tjsr/article/view/32>. Date accessed: 16 aug. 2018.