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Effect of Bias on the Pearson Chi-squared Test for Two Population Homogeneity Test

원문정보

Sunyeong Heo

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초록

영어

Categorical data collected based on complex sample design is not proper for the standard Pearson multinomial-based chi-squared test because the observations are not independent and identically distributed. This study investigates effects of bias of point estimator of population proportion and its variance estimator to the standard Pearson chi-squared test statistics when the sample is collected based on complex sampling scheme. This study examines the effect under two population homogeneity test. The standard Pearson test statistic can be partitioned into two parts; the first part is the weighted sum of ?? with eigenvalues of design matrix as their weights, and the additional second part which is added due to the biases of the point estimator and its variance estimator. Our empirical analysis shows that even though the bias of point estimator is small, Pearson test statistic is very much inflated due to underestimate the variance of point estimator. In the connection of design-based variance estimator and its design matrix, the bigger the average of eigenvalues of design matrix is, the larger relative size of which the first component part to Pearson test statistic is taking.

목차

Abstract
 1. Introduction
 2. Homogeneity Test
  2.1. Pearson Chi-squared Test
  2.2. Wald Test
  2.3. Bias of Pearson Test
 3. Empirical Analysis
  3.1. Empirical Data
  3.2. Empirical Analysis
 4. Conclusion
 References

저자정보

  • Sunyeong Heo Department of statistics, Changwon National University

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자료제공 : 네이버학술정보

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