Variance estimator for Repeated Measurements Model by iterated bootstrap with an application to Oil industry pollutants in Basrah
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Abstract
The aim of this research deals with the study of the estimators of the variance compounds by the bootstrap approximate method of the one-way repeated measurements (RM) model and the calculation of the amount of bias in the estimators of the variance components. The model contains two fixed factors (one factor within units and one factor between units) and their interactions and two random factors. As an applied aspect, a study was undertaken to measure the air pollutants (CO, CO2, and CH4) in the Al-Shuaiba region – Basrah in Iraq to study the variation in pollutant concentrations in two randomly selected stations from the region with five sections with two directions for each station during the summer and winter seasons 2019-2020. The SPSS statistical analysis program was used to analyze the study data and calculate the amount of bias in the estimators of the variance components.
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