Median polish techniques for analysing paired data

Median polish is used as a data analysis technique for examining the significance of various factors in single or multi-way models. The main goal of this research is to analyze paired data using median polish technique in order to get information from the data such as difference between the paired d...

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Main Author:	Ajoge, Idris
Format:	Thesis
Language:	English
Published:	2017
Subjects:	Mathematical statistics
Online Access:	http://psasir.upm.edu.my/id/eprint/70805/1/FS%202017%203%20IR.pdf
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id	my-upm-ir.70805
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spelling	my-upm-ir.708052019-08-06T03:35:26Z Median polish techniques for analysing paired data 2017-01 Ajoge, Idris Median polish is used as a data analysis technique for examining the significance of various factors in single or multi-way models. The main goal of this research is to analyze paired data using median polish technique in order to get information from the data such as difference between the paired data through column and row effects. Median polish algorithm is useful in removing any noise in the data by computing medians for various coordinates on the data set. In this research, we will focus on paired data. Some effects such as overall, rows and column were determined using median polish algorithm. In this research, one-way and two-way median polish has been expanded for pairwise scenario. The pairwise median polish criterion addresses the fairness of declaring a difference between a paired data. Paired data involves collection of data prior to the treatment and compare it with after the treatment. We extend the analysis of paired data for the case of missing values. Later, exercising of comparison values in a two-way median polish for paired data was implemented to verifying the association between rows and columns effects. In addition, to determine whether there is need for transformation of data or not. Pairwise median polish model is successfully employed in the analysing the comparison and verification of the difference between paired data of grain yields in classification of contingency table. For the two-way median polish for paired data, comparison values calculated shows there is no association between rows and columns effects and transformation of data is not required in this study. The median polish provides simple estimation of main effects for paired data as well as various factor effects. The findings also have shown that there is a difference in grand effects of both after treatment data without missing values and imputed values using paired median polish procedure. Mathematical statistics 2017-01 Thesis http://psasir.upm.edu.my/id/eprint/70805/ http://psasir.upm.edu.my/id/eprint/70805/1/FS%202017%203%20IR.pdf text en public masters Universiti Putra Malaysia Mathematical statistics
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
topic	Mathematical statistics
spellingShingle	Mathematical statistics Ajoge, Idris Median polish techniques for analysing paired data
description	Median polish is used as a data analysis technique for examining the significance of various factors in single or multi-way models. The main goal of this research is to analyze paired data using median polish technique in order to get information from the data such as difference between the paired data through column and row effects. Median polish algorithm is useful in removing any noise in the data by computing medians for various coordinates on the data set. In this research, we will focus on paired data. Some effects such as overall, rows and column were determined using median polish algorithm. In this research, one-way and two-way median polish has been expanded for pairwise scenario. The pairwise median polish criterion addresses the fairness of declaring a difference between a paired data. Paired data involves collection of data prior to the treatment and compare it with after the treatment. We extend the analysis of paired data for the case of missing values. Later, exercising of comparison values in a two-way median polish for paired data was implemented to verifying the association between rows and columns effects. In addition, to determine whether there is need for transformation of data or not. Pairwise median polish model is successfully employed in the analysing the comparison and verification of the difference between paired data of grain yields in classification of contingency table. For the two-way median polish for paired data, comparison values calculated shows there is no association between rows and columns effects and transformation of data is not required in this study. The median polish provides simple estimation of main effects for paired data as well as various factor effects. The findings also have shown that there is a difference in grand effects of both after treatment data without missing values and imputed values using paired median polish procedure.
format	Thesis
qualification_level	Master's degree
author	Ajoge, Idris
author_facet	Ajoge, Idris
author_sort	Ajoge, Idris
title	Median polish techniques for analysing paired data
title_short	Median polish techniques for analysing paired data
title_full	Median polish techniques for analysing paired data
title_fullStr	Median polish techniques for analysing paired data
title_full_unstemmed	Median polish techniques for analysing paired data
title_sort	median polish techniques for analysing paired data
granting_institution	Universiti Putra Malaysia
publishDate	2017
url	http://psasir.upm.edu.my/id/eprint/70805/1/FS%202017%203%20IR.pdf
_version_	1747812911642836992

Median polish techniques for analysing paired data

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