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Estimation of missing data in analysis of covariance: A least-squares approach
Authors:Chibueze E Ogbonnaya  Emeka C Uzochukwu
Institution:1. Department of Statistics, Faculty of Physical Sciences, University of Nigeria, Nsukka, Enugu, Nigeriachibueze.emmanuelo@yahoo.com;3. Department of Statistics, Faculty of Physical Sciences, University of Nigeria, Nsukka, Enugu, Nigeria
Abstract:Abstract

A method is proposed for the estimation of missing data in analysis of covariance models. This is based on obtaining an estimate of the missing observation that minimizes the error sum of squares. Specific derivation of this estimate is carried out for the one-factor analysis of covariance, and numerical examples are given to show the nature of the estimates produced. Parameter estimates of the imputed data are then compared with those of the incomplete data.
Keywords:Analysis of covariance  Covariate  Dependent variable  Error sum of squares  Least squares  Missing data
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