Some Tests Based on the Profile Likelihood Estimator for Testing Homogeneity of Diagnostic Odds Ratios in Meta-analysis Article Swipe
Khanokporn Donjdee
,
Pratana Satitvipawee
,
Prasong Kitidamrongsuk
,
Pichitpong Soontornpipit
,
Jutatip Sillabutra
,
Chukiat Viwatwongkasem
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1016/j.procs.2016.05.098
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1016/j.procs.2016.05.098
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.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.procs.2016.05.098
- OA Status
- diamond
- References
- 3
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2405178317
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2405178317Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.procs.2016.05.098Digital Object Identifier
- Title
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Some Tests Based on the Profile Likelihood Estimator for Testing Homogeneity of Diagnostic Odds Ratios in Meta-analysisWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2016Year of publication
- Publication date
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2016-01-01Full publication date if available
- Authors
-
Khanokporn Donjdee, Pratana Satitvipawee, Prasong Kitidamrongsuk, Pichitpong Soontornpipit, Jutatip Sillabutra, Chukiat ViwatwongkasemList of authors in order
- Landing page
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https://doi.org/10.1016/j.procs.2016.05.098Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.procs.2016.05.098Direct OA link when available
- Concepts
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Homogeneity (statistics), Type I and type II errors, Estimator, Statistics, Computer science, Meta-analysis, Monte Carlo method, Diagnostic odds ratio, Sample size determination, Statistical hypothesis testing, Confidence interval, Mathematics, Medicine, Internal medicineTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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3Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.H1, | 57 |
| abstract_inverted_index.QMH | 36 |
| abstract_inverted_index.The | 66 |
| abstract_inverted_index.all | 70, 116 |
| abstract_inverted_index.and | 9, 26, 37, 52, 143 |
| abstract_inverted_index.are | 82 |
| abstract_inverted_index.can | 108 |
| abstract_inverted_index.for | 17, 92, 134, 161 |
| abstract_inverted_index.nHi | 100, 131, 158, 181 |
| abstract_inverted_index.the | 13, 31, 41, 120, 148, 152, 166 |
| abstract_inverted_index.was | 64 |
| abstract_inverted_index.≤ | 101 |
| abstract_inverted_index.≥ | 94, 136, 163, 175 |
| abstract_inverted_index.(k). | 90 |
| abstract_inverted_index.500. | 183 |
| abstract_inverted_index.QWLS | 142 |
| abstract_inverted_index.This | 0 |
| abstract_inverted_index.aims | 2 |
| abstract_inverted_index.best | 125 |
| abstract_inverted_index.nDi, | 99, 130, 157, 180 |
| abstract_inverted_index.odds | 22 |
| abstract_inverted_index.same | 149 |
| abstract_inverted_index.size | 89 |
| abstract_inverted_index.some | 5 |
| abstract_inverted_index.test | 122, 154 |
| abstract_inverted_index.that | 69 |
| abstract_inverted_index.type | 46, 75, 110 |
| abstract_inverted_index.used | 172 |
| abstract_inverted_index.well | 146 |
| abstract_inverted_index.when | 79, 129, 156, 173 |
| abstract_inverted_index.with | 30, 61, 98, 126, 147, 179 |
| abstract_inverted_index.(nDi, | 84 |
| abstract_inverted_index.Carlo | 59 |
| abstract_inverted_index.Monte | 58 |
| abstract_inverted_index.QWLS, | 35, 106 |
| abstract_inverted_index.based | 11 |
| abstract_inverted_index.error | 48, 77, 112 |
| abstract_inverted_index.found | 68 |
| abstract_inverted_index.power | 53, 128, 150 |
| abstract_inverted_index.rates | 49, 78, 113 |
| abstract_inverted_index.sizes | 81 |
| abstract_inverted_index.small | 83 |
| abstract_inverted_index.study | 88 |
| abstract_inverted_index.terms | 44 |
| abstract_inverted_index.tests | 7, 33, 55, 72, 104, 140 |
| abstract_inverted_index.their | 28 |
| abstract_inverted_index.three | 103 |
| abstract_inverted_index.under | 50, 56 |
| abstract_inverted_index.while | 138 |
| abstract_inverted_index.50,100 | 133 |
| abstract_inverted_index.almost | 115 |
| abstract_inverted_index.cannot | 73 |
| abstract_inverted_index.ratios | 23 |
| abstract_inverted_index.sample | 80 |
| abstract_inverted_index.χ2Con | 144 |
| abstract_inverted_index.compare | 27 |
| abstract_inverted_index.control | 74, 109 |
| abstract_inverted_index.highest | 127 |
| abstract_inverted_index.perform | 145 |
| abstract_inverted_index.profile | 14, 121, 153 |
| abstract_inverted_index.propose | 4 |
| abstract_inverted_index.results | 67 |
| abstract_inverted_index.testing | 18 |
| abstract_inverted_index.χ2Con) | 107 |
| abstract_inverted_index.χ2Con. | 38 |
| abstract_inverted_index.χ2PLE1 | 167 |
| abstract_inverted_index.However, | 91 |
| abstract_inverted_index.applied. | 65 |
| abstract_inverted_index.language | 63 |
| abstract_inverted_index.modified | 6 |
| abstract_inverted_index.performs | 124 |
| abstract_inverted_index.research | 1 |
| abstract_inverted_index."χ2PLE1" | 8 |
| abstract_inverted_index."χ2PLE2" | 10 |
| abstract_inverted_index.(χ2PLE1) | 123, 155 |
| abstract_inverted_index.(χ2PLE1, | 105 |
| abstract_inverted_index.According | 39 |
| abstract_inverted_index.addition, | 119 |
| abstract_inverted_index.estimator | 16 |
| abstract_inverted_index.nHi≤5), | 85 |
| abstract_inverted_index.Therefore, | 165 |
| abstract_inverted_index.diagnostic | 21 |
| abstract_inverted_index.likelihood | 15 |
| abstract_inverted_index.regardless | 86 |
| abstract_inverted_index.simulation | 60 |
| abstract_inverted_index.combination | 97, 178 |
| abstract_inverted_index.homogeneity | 19 |
| abstract_inverted_index.performance | 42 |
| abstract_inverted_index.recommended | 169 |
| abstract_inverted_index.situations. | 117 |
| abstract_inverted_index.conventional | 32, 139 |
| abstract_inverted_index.performances | 29 |
| abstract_inverted_index.meta-analysis | 25 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5080500080 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I25399158 |
| citation_normalized_percentile.value | 0.03811789 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |