Publication: Some Tests Based on the Profile Likelihood Estimator for Testing Homogeneity of Diagnostic Odds Ratios in Meta-analysis
Issued Date
2016-01-01
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ISSN
18770509
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2-s2.0-84999810274
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Mahidol University
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SCOPUS
Bibliographic Citation
Procedia Computer Science. Vol.86, (2016), 220-223
Suggested Citation
Khanokporn Donjdee, Pratana Satitvipawee, Prasong Kitidamrongsuk, Pichitpong Soontornpipit, Jutatip Sillabutra, Chukiat Viwatwongkasem Some Tests Based on the Profile Likelihood Estimator for Testing Homogeneity of Diagnostic Odds Ratios in Meta-analysis. Procedia Computer Science. Vol.86, (2016), 220-223. doi:10.1016/j.procs.2016.05.098 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/43502
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Title
Some Tests Based on the Profile Likelihood Estimator for Testing Homogeneity of Diagnostic Odds Ratios in Meta-analysis
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Abstract
© 2016 The Authors. This research aims to propose some modified tests "χ2PLE1" and "χ2PLE2" based on the profile likelihood estimator for testing homogeneity of diagnostic odds ratios in meta-analysis and compare their performances with the conventional tests of QWLS, QMH and χ2Con. According to the performance in terms of type I error rates under H0 and power of tests under H1, Monte Carlo simulation with R language was applied. The results found that all of tests cannot control type I error rates when sample sizes are small (nDi, nHi≤5), regardless of study size (k). However, for k ≥ 16 in combination with nDi, nHi ≤ 50, three tests (χ2PLE1, QWLS, χ2Con) can control type I error rates in almost all situations. In addition, the profile test (χ2PLE1) performs best with highest power when nDi, nHi = 50,100 for k ≥ 16, while conventional tests of QWLS and χ2Con perform well with the same power as the profile test (χ2PLE1) when nDi, nHi = 500 for k ≥ 16. Therefore, the χ2PLE1 is recommended to be used when k ≥ 16 in combination with nDi, nHi = 500.