Research Article Open Access

On the Comparison of Methods of Estimating Missing Values in Rectangular Lattice Designs

Abimibola V. Oladugba1, Emmanuel O. Ossai1 and Tobias E. Ugah1
  • 1 University of Nigeria, Nigeria

Abstract

Missing values occur in almost all research which lead to ambiguity in data analysis. It becomes necessary that appropriate consideration is made in order to provide an efficient and valid analysis. Researchers have developed and compared a variety of methods of estimating missing values in experimental designs; however, no research work has derived and compared methods of estimating missing values, particularly for rectangular lattice designs. In this study, the Least Square Method (LSM) and the Analysis of Covariance (ANCOVA) method for estimating missing value in rectangular lattice designs, with and without repetitions, were derived and compared based on four (4) statistical criteria: estimated values, standard errors, p-values and coefficients of determination respectively. Results from the comparison between the derived LSM and the ANCOVA methods showed that the estimates of the LSM appeared more approximate and better than the ANCOVA method in terms of their estimated values, standard errors, p-values and coefficients of determination.

Journal of Mathematics and Statistics
Volume 14 No. 1, 2018, 201-208

DOI: https://doi.org/10.3844/jmssp.2018.201.208

Submitted On: 25 May 2018 Published On: 11 October 2018

How to Cite: Oladugba, A. V., Ossai, E. O. & Ugah, T. E. (2018). On the Comparison of Methods of Estimating Missing Values in Rectangular Lattice Designs. Journal of Mathematics and Statistics, 14(1), 201-208. https://doi.org/10.3844/jmssp.2018.201.208

  • 3,707 Views
  • 2,023 Downloads
  • 2 Citations

Download

Keywords

  • Rectangular Lattice Design
  • Missing at Random
  • Coefficient of Determination
  • Missing Data
  • Estimated Value