Abstract
The studies of analysis of variance components is one of the important topics in mathematical statistics for this subject of wide application. In this paper given best quadratic unbiased estimator of variance components for balanced data for linear one-way repeated measurement model (RMM). We computed the quadratic unbiased estimator, which has minimum variance (best quadratic unbiased estimate (BQUE)) by using analysis of variance (ANOVA) method of estimating the variance components.
Highlights
The variance component analogue of the best linear unbiased estimator of a function of effects is a best quadratic unbiased estimator (BQUE), that is, a quadratic function of the observations that is unbiased for the variance component and has minimum variance among all such estimators [8]
Repeated measurements is a term used to describe data in which the response variable for each experimental unit is observed on multiple occasions and possibly under different experimental conditions
Within-subject covariates, referred to as within-subject or within-unit factors, repeated measures factors and/or time-dependent covariates, represent variables or experimental conditions which vary over time within subjects or experimental units [9]
Summary
The variance component analogue of the best linear unbiased estimator of a function of effects is a best quadratic unbiased estimator (BQUE), that is, a quadratic function of the observations that is unbiased for the variance component and has minimum variance among all such estimators [8]. Repeated measurements is a term used to describe data in which the response variable for each experimental unit is observed on multiple occasions and possibly under different experimental conditions. Occur frequently in observational studies, which are longitudinal in nature, and in experimental studies incorporating repeated measures designs. In the repeated measurements setting, independent factors or covariates may be classified into one of two categories: within-subject covariates and between-subject covariates. Within-subject covariates, referred to as within-subject or within-unit factors, repeated measures factors and/or time-dependent covariates, represent variables or experimental conditions which vary over time within subjects or experimental units [9]. We consider analysis of variance methods of estimating the variance components linear of the one-way repeated measurement model (RMM) to obtained BQUE for this model
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
