A significant minimization of Pearson’s X2 statistics in 2x2 contingency tables: preliminary results for small samples
Author(s) -
Nicola Serra
Publication year - 2022
Publication title -
epidemiology biostatistics and public health
Language(s) - English
Resource type - Journals
eISSN - 2282-2305
pISSN - 2282-0930
DOI - 10.2427/12949
Subject(s) - contingency table , statistics , statistic , nonparametric statistics , mathematics , statistical hypothesis testing , chi square test , pearson product moment correlation coefficient , continuity correction , type i and type ii errors , sample size determination , test statistic , value (mathematics) , minification , p value , test (biology) , mathematical optimization , negative binomial distribution , beta binomial distribution , poisson distribution , paleontology , biology
The Pearson’s chi-square test or X 2 test represents a nonparametric test more used in Medicine, Biology and Social Sciences, but it introduces some error for 2x2 contingency tables, therefore Yates introduces a continuity correction. This correction produces a very conservative result of X 2 statistics with overestimation of p-value and consequently a type II error is very likely. The goal of this paper is to define, with a statistical approach, a significant minimization of Pearson’s X 2 statistics for small data sample, based on concept of arithmetic mean, that could be a possible efficient statistic for reducing the type II error in the calculation of p-value.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom