The Chi-square test of independence
The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not...
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Croatian Society of Medical Biochemistry and Laboratory Medicine
2013
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900058/ |
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pubmed-39000582014-01-23 The Chi-square test of independence McHugh, Mary L. Lessons in Biostatistics The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not require equality of variances among the study groups or homoscedasticity in the data. It permits evaluation of both dichotomous independent variables, and of multiple group studies. Unlike many other non-parametric and some parametric statistics, the calculations needed to compute the Chi-square provide considerable information about how each of the groups performed in the study. This richness of detail allows the researcher to understand the results and thus to derive more detailed information from this statistic than from many others. Croatian Society of Medical Biochemistry and Laboratory Medicine 2013-06-15 /pmc/articles/PMC3900058/ /pubmed/23894860 http://dx.doi.org/10.11613/BM.2013.018 Text en ©Copyright by Croatian Society of Medical Biochemistry and Laboratory Medicine This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
McHugh, Mary L. |
| spellingShingle |
McHugh, Mary L. The Chi-square test of independence |
| author_facet |
McHugh, Mary L. |
| author_sort |
McHugh, Mary L. |
| title |
The Chi-square test of independence |
| title_short |
The Chi-square test of independence |
| title_full |
The Chi-square test of independence |
| title_fullStr |
The Chi-square test of independence |
| title_full_unstemmed |
The Chi-square test of independence |
| title_sort |
chi-square test of independence |
| description |
The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not require equality of variances among the study groups or homoscedasticity in the data. It permits evaluation of both dichotomous independent variables, and of multiple group studies. Unlike many other non-parametric and some parametric statistics, the calculations needed to compute the Chi-square provide considerable information about how each of the groups performed in the study. This richness of detail allows the researcher to understand the results and thus to derive more detailed information from this statistic than from many others. |
| publisher |
Croatian Society of Medical Biochemistry and Laboratory Medicine |
| publishDate |
2013 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900058/ |
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1612050567318732800 |