An Evaluation of Weighted Chi-Square Statistics for Clustered Binary Data

Chul Ahn, Sin Ho Jung, Seung Ho Kang

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Clustered binary responses occur frequently in many fields of application. Examples include the development of tumors in one or more animals of a litter, the presence of retinitis in either or both eyes of an AIDS patient, and spontaneous abortion of one or more implanted fetuses. When a binary response is observed in multiple units from each subject, application of the usual Pearson chi-square statistic is invalid since such responses within the same subject are not independent. In estimating the common response probability in clustered binary data, two weighting systems have been most popular: equal weights to units, and equal weights to clusters. We also include an optimal weighting method that minimizes the variance of the response probability. The weighted chi-square statistics using the above three weighting systems are applied to the real data arising from a teratologic study and an ophthalmologic study. We perform the simulation study to evaluate the performance of the three weighted chi-square statistics in terms of empirical type I errors and empirical powers. The simulation study shows that the weighted chi-square statistic using an optimal weight yields higher empirical powers than the other weighted chi-square statistics and produces empirical type I errors close to a nominal value. The wieghted chi-square statistics assigning equal weights to units (XD 2) and optimal weights (XO 2) are slightly anti-conservative when n1 = n2 = n = 10. We recommend using XO 2 when n1 = n2 = n ≥ 20 since the differences in empirical type I errors are negligible among weighted chi-square statistics and XO 2 performs better than the other weighted chi-square test statistics in empirical powers.

Original languageEnglish
Pages (from-to)91-99
Number of pages9
JournalDrug Information Journal
Volume37
Issue number1
DOIs
Publication statusPublished - 2003 Jan 1

Fingerprint

Statistics
Weights and Measures
Retinitis
Spontaneous Abortion
Chi-Square Distribution
Tumors
Acquired Immunodeficiency Syndrome
Animals
Fetus
Neoplasms

All Science Journal Classification (ASJC) codes

  • Pharmacology (nursing)
  • Drug guides
  • Public Health, Environmental and Occupational Health
  • Pharmacology (medical)

Cite this

@article{c767495da31d487f86ecea2ee36ada1d,
title = "An Evaluation of Weighted Chi-Square Statistics for Clustered Binary Data",
abstract = "Clustered binary responses occur frequently in many fields of application. Examples include the development of tumors in one or more animals of a litter, the presence of retinitis in either or both eyes of an AIDS patient, and spontaneous abortion of one or more implanted fetuses. When a binary response is observed in multiple units from each subject, application of the usual Pearson chi-square statistic is invalid since such responses within the same subject are not independent. In estimating the common response probability in clustered binary data, two weighting systems have been most popular: equal weights to units, and equal weights to clusters. We also include an optimal weighting method that minimizes the variance of the response probability. The weighted chi-square statistics using the above three weighting systems are applied to the real data arising from a teratologic study and an ophthalmologic study. We perform the simulation study to evaluate the performance of the three weighted chi-square statistics in terms of empirical type I errors and empirical powers. The simulation study shows that the weighted chi-square statistic using an optimal weight yields higher empirical powers than the other weighted chi-square statistics and produces empirical type I errors close to a nominal value. The wieghted chi-square statistics assigning equal weights to units (XD 2) and optimal weights (XO 2) are slightly anti-conservative when n1 = n2 = n = 10. We recommend using XO 2 when n1 = n2 = n ≥ 20 since the differences in empirical type I errors are negligible among weighted chi-square statistics and XO 2 performs better than the other weighted chi-square test statistics in empirical powers.",
author = "Chul Ahn and Jung, {Sin Ho} and Kang, {Seung Ho}",
year = "2003",
month = "1",
day = "1",
doi = "10.1177/009286150303700111",
language = "English",
volume = "37",
pages = "91--99",
journal = "Drug Information Journal",
issn = "0092-8615",
publisher = "Drug Information Association",
number = "1",

}

An Evaluation of Weighted Chi-Square Statistics for Clustered Binary Data. / Ahn, Chul; Jung, Sin Ho; Kang, Seung Ho.

In: Drug Information Journal, Vol. 37, No. 1, 01.01.2003, p. 91-99.

Research output: Contribution to journalArticle

TY - JOUR

T1 - An Evaluation of Weighted Chi-Square Statistics for Clustered Binary Data

AU - Ahn, Chul

AU - Jung, Sin Ho

AU - Kang, Seung Ho

PY - 2003/1/1

Y1 - 2003/1/1

N2 - Clustered binary responses occur frequently in many fields of application. Examples include the development of tumors in one or more animals of a litter, the presence of retinitis in either or both eyes of an AIDS patient, and spontaneous abortion of one or more implanted fetuses. When a binary response is observed in multiple units from each subject, application of the usual Pearson chi-square statistic is invalid since such responses within the same subject are not independent. In estimating the common response probability in clustered binary data, two weighting systems have been most popular: equal weights to units, and equal weights to clusters. We also include an optimal weighting method that minimizes the variance of the response probability. The weighted chi-square statistics using the above three weighting systems are applied to the real data arising from a teratologic study and an ophthalmologic study. We perform the simulation study to evaluate the performance of the three weighted chi-square statistics in terms of empirical type I errors and empirical powers. The simulation study shows that the weighted chi-square statistic using an optimal weight yields higher empirical powers than the other weighted chi-square statistics and produces empirical type I errors close to a nominal value. The wieghted chi-square statistics assigning equal weights to units (XD 2) and optimal weights (XO 2) are slightly anti-conservative when n1 = n2 = n = 10. We recommend using XO 2 when n1 = n2 = n ≥ 20 since the differences in empirical type I errors are negligible among weighted chi-square statistics and XO 2 performs better than the other weighted chi-square test statistics in empirical powers.

AB - Clustered binary responses occur frequently in many fields of application. Examples include the development of tumors in one or more animals of a litter, the presence of retinitis in either or both eyes of an AIDS patient, and spontaneous abortion of one or more implanted fetuses. When a binary response is observed in multiple units from each subject, application of the usual Pearson chi-square statistic is invalid since such responses within the same subject are not independent. In estimating the common response probability in clustered binary data, two weighting systems have been most popular: equal weights to units, and equal weights to clusters. We also include an optimal weighting method that minimizes the variance of the response probability. The weighted chi-square statistics using the above three weighting systems are applied to the real data arising from a teratologic study and an ophthalmologic study. We perform the simulation study to evaluate the performance of the three weighted chi-square statistics in terms of empirical type I errors and empirical powers. The simulation study shows that the weighted chi-square statistic using an optimal weight yields higher empirical powers than the other weighted chi-square statistics and produces empirical type I errors close to a nominal value. The wieghted chi-square statistics assigning equal weights to units (XD 2) and optimal weights (XO 2) are slightly anti-conservative when n1 = n2 = n = 10. We recommend using XO 2 when n1 = n2 = n ≥ 20 since the differences in empirical type I errors are negligible among weighted chi-square statistics and XO 2 performs better than the other weighted chi-square test statistics in empirical powers.

UR - http://www.scopus.com/inward/record.url?scp=0142246388&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0142246388&partnerID=8YFLogxK

U2 - 10.1177/009286150303700111

DO - 10.1177/009286150303700111

M3 - Article

AN - SCOPUS:0142246388

VL - 37

SP - 91

EP - 99

JO - Drug Information Journal

JF - Drug Information Journal

SN - 0092-8615

IS - 1

ER -