Exploring interaction effects in small samples increases rates of false-positive and false-negative findings: results from a systematic review and simulation study
Abstract Objective To give a comprehensive comparison of the performance of commonly applied interaction tests. Methods A literature review and simulation study was performed evaluating interaction tests on the odds ratio (OR) or the risk difference (RD) scales: Cochran Q (Q), Breslow–Day (BD), Taro...
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| Veröffentlicht in: | Journal of clinical epidemiology 2014-07, Vol.67 (7), p.821-829 |
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| creator | Schmidt, Amand F Groenwold, Rolf H.H Knol, Mirjam J Hoes, Arno W Nielen, Mirjam Roes, Kit C.B de Boer, Anthonius Klungel, Olaf H |
| description | Abstract Objective To give a comprehensive comparison of the performance of commonly applied interaction tests. Methods A literature review and simulation study was performed evaluating interaction tests on the odds ratio (OR) or the risk difference (RD) scales: Cochran Q (Q), Breslow–Day (BD), Tarone, unconditional score, likelihood ratio (LR), Wald, and relative excess risk due to interaction (RERI)-based tests. Results Review results agreed with results from our simulation study, which showed that on the OR scale, in small sample sizes (eg, number of subjects ≤ 250) the type 1 error rates of the LR test was 0.10; the BD and Tarone tests showed results around 0.05. On the RD scale, the LR and RERI tests had error rates around 0.05. On both scales, tests did not differ regarding power. When exposure prevented the outcome RERI-based tests were relatively underpowered (eg, N = 100; RERI power = 5% vs. Wald power = 18%). With increasing sample size, difference decreased. Conclusion In small samples, interaction tests differed. On the OR scale, the Tarone and BD tests are recommended. On the RD scale, the LR and RERI-based tests performed best. However, RERI-based tests are underpowered compared with other tests, when exposure prevents the outcome, and sample size is limited. |
| doi_str_mv | 10.1016/j.jclinepi.2014.02.008 |
| format | Article |
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Methods A literature review and simulation study was performed evaluating interaction tests on the odds ratio (OR) or the risk difference (RD) scales: Cochran Q (Q), Breslow–Day (BD), Tarone, unconditional score, likelihood ratio (LR), Wald, and relative excess risk due to interaction (RERI)-based tests. Results Review results agreed with results from our simulation study, which showed that on the OR scale, in small sample sizes (eg, number of subjects ≤ 250) the type 1 error rates of the LR test was 0.10; the BD and Tarone tests showed results around 0.05. On the RD scale, the LR and RERI tests had error rates around 0.05. On both scales, tests did not differ regarding power. When exposure prevented the outcome RERI-based tests were relatively underpowered (eg, N = 100; RERI power = 5% vs. Wald power = 18%). With increasing sample size, difference decreased. Conclusion In small samples, interaction tests differed. On the OR scale, the Tarone and BD tests are recommended. On the RD scale, the LR and RERI-based tests performed best. However, RERI-based tests are underpowered compared with other tests, when exposure prevents the outcome, and sample size is limited.</description><identifier>ISSN: 0895-4356</identifier><identifier>EISSN: 1878-5921</identifier><identifier>DOI: 10.1016/j.jclinepi.2014.02.008</identifier><identifier>PMID: 24768005</identifier><language>eng</language><publisher>New York, NY: Elsevier Inc</publisher><subject>Analysis. Health state ; Biological and medical sciences ; Computer Simulation ; Diagnostic Errors ; Effect modification ; Epidemiologic Methods ; Epidemiology ; False Negative Reactions ; False Positive Reactions ; General aspects ; Heart attacks ; Humans ; Interaction ; Internal Medicine ; Literature reviews ; Medical research ; Medical sciences ; Odds Ratio ; Public health. Hygiene ; Public health. Hygiene-occupational medicine ; Relative excess risk due to interaction ; Review ; Risk ; Risk ratio ; Sample Size ; Simulation ; Statistics ; Statistics as Topic ; Subgroups</subject><ispartof>Journal of clinical epidemiology, 2014-07, Vol.67 (7), p.821-829</ispartof><rights>Elsevier Inc.</rights><rights>2014 Elsevier Inc.</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2014 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited Jul 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c481t-dfe05df63cdce86a941744643bc869779a2c5c0568a388cc063e6d0726b69e4f3</citedby><cites>FETCH-LOGICAL-c481t-dfe05df63cdce86a941744643bc869779a2c5c0568a388cc063e6d0726b69e4f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0895435614000596$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28696434$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24768005$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Schmidt, Amand F</creatorcontrib><creatorcontrib>Groenwold, Rolf H.H</creatorcontrib><creatorcontrib>Knol, Mirjam J</creatorcontrib><creatorcontrib>Hoes, Arno W</creatorcontrib><creatorcontrib>Nielen, Mirjam</creatorcontrib><creatorcontrib>Roes, Kit C.B</creatorcontrib><creatorcontrib>de Boer, Anthonius</creatorcontrib><creatorcontrib>Klungel, Olaf H</creatorcontrib><title>Exploring interaction effects in small samples increases rates of false-positive and false-negative findings: results from a systematic review and simulation study</title><title>Journal of clinical epidemiology</title><addtitle>J Clin Epidemiol</addtitle><description>Abstract Objective To give a comprehensive comparison of the performance of commonly applied interaction tests. Methods A literature review and simulation study was performed evaluating interaction tests on the odds ratio (OR) or the risk difference (RD) scales: Cochran Q (Q), Breslow–Day (BD), Tarone, unconditional score, likelihood ratio (LR), Wald, and relative excess risk due to interaction (RERI)-based tests. Results Review results agreed with results from our simulation study, which showed that on the OR scale, in small sample sizes (eg, number of subjects ≤ 250) the type 1 error rates of the LR test was 0.10; the BD and Tarone tests showed results around 0.05. On the RD scale, the LR and RERI tests had error rates around 0.05. On both scales, tests did not differ regarding power. When exposure prevented the outcome RERI-based tests were relatively underpowered (eg, N = 100; RERI power = 5% vs. Wald power = 18%). With increasing sample size, difference decreased. Conclusion In small samples, interaction tests differed. On the OR scale, the Tarone and BD tests are recommended. On the RD scale, the LR and RERI-based tests performed best. However, RERI-based tests are underpowered compared with other tests, when exposure prevents the outcome, and sample size is limited.</description><subject>Analysis. Health state</subject><subject>Biological and medical sciences</subject><subject>Computer Simulation</subject><subject>Diagnostic Errors</subject><subject>Effect modification</subject><subject>Epidemiologic Methods</subject><subject>Epidemiology</subject><subject>False Negative Reactions</subject><subject>False Positive Reactions</subject><subject>General aspects</subject><subject>Heart attacks</subject><subject>Humans</subject><subject>Interaction</subject><subject>Internal Medicine</subject><subject>Literature reviews</subject><subject>Medical research</subject><subject>Medical sciences</subject><subject>Odds Ratio</subject><subject>Public health. Hygiene</subject><subject>Public health. Hygiene-occupational medicine</subject><subject>Relative excess risk due to interaction</subject><subject>Review</subject><subject>Risk</subject><subject>Risk ratio</subject><subject>Sample Size</subject><subject>Simulation</subject><subject>Statistics</subject><subject>Statistics as Topic</subject><subject>Subgroups</subject><issn>0895-4356</issn><issn>1878-5921</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFks9u1DAQxiMEokvhFapICIlLFjtxHIcDKqrKH6kSB-BseZ1x5cVxgicp7PP0RTvZ3VKpF6TIsca_-Twzn7PsjLM1Z1y-2663NvgIo1-XjIs1K9eMqSfZiqtGFXVb8qfZiqm2LkRVy5PsBeKWMd6wpn6enZSikYqxepXdXv4dw5B8vM59nCAZO_kh5uAc2AkplmNvQsjR9GOAJWATGKRdMhOtg8udCQjFOKCf_A3kJnbHUIRrsw85Hzu6Ad_nCXAOpOvS0Ocmxx1O0BNk6eTGw599Nvp-DmZfB05zt3uZPdsLvjr-T7Ofny5_XHwprr59_nrx8aqwQvGp6BywunOysp0FJU0reCOEFNXGKtk2TWtKW1tWS2UqpaxlsgLZsaaUG9mCcNVp9vagO6bh9ww46d6jhRBMhGFGzWsaZcVKrgh9_QjdDnOKVN1CCfqUYkTJA2XTgJjA6TH53qSd5kwvNuqtvrdRLzZqVmqykRLPjvLzpofuX9q9bwS8OQIGrQkumWg9PnDUMDUuiDs_cEBzowEnjdZDtND5RAbrbvD_r-XDI4mF8nTrL9gBPvStkRL09-XRLW-OC0aVtrK6A1Hd1wY</recordid><startdate>20140701</startdate><enddate>20140701</enddate><creator>Schmidt, Amand F</creator><creator>Groenwold, Rolf H.H</creator><creator>Knol, Mirjam J</creator><creator>Hoes, Arno W</creator><creator>Nielen, Mirjam</creator><creator>Roes, Kit C.B</creator><creator>de Boer, Anthonius</creator><creator>Klungel, Olaf H</creator><general>Elsevier Inc</general><general>Elsevier</general><general>Elsevier Limited</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7QP</scope><scope>7RV</scope><scope>7T2</scope><scope>7T7</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2O</scope><scope>M7N</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PJZUB</scope><scope>PKEHL</scope><scope>PPXIY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20140701</creationdate><title>Exploring interaction effects in small samples increases rates of false-positive and false-negative findings: results from a systematic review and simulation study</title><author>Schmidt, Amand F ; Groenwold, Rolf H.H ; Knol, Mirjam J ; Hoes, Arno W ; Nielen, Mirjam ; Roes, Kit C.B ; de Boer, Anthonius ; Klungel, Olaf H</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c481t-dfe05df63cdce86a941744643bc869779a2c5c0568a388cc063e6d0726b69e4f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Analysis. 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Hygiene-occupational medicine</topic><topic>Relative excess risk due to interaction</topic><topic>Review</topic><topic>Risk</topic><topic>Risk ratio</topic><topic>Sample Size</topic><topic>Simulation</topic><topic>Statistics</topic><topic>Statistics as Topic</topic><topic>Subgroups</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Schmidt, Amand F</creatorcontrib><creatorcontrib>Groenwold, Rolf H.H</creatorcontrib><creatorcontrib>Knol, Mirjam J</creatorcontrib><creatorcontrib>Hoes, Arno W</creatorcontrib><creatorcontrib>Nielen, Mirjam</creatorcontrib><creatorcontrib>Roes, Kit C.B</creatorcontrib><creatorcontrib>de Boer, Anthonius</creatorcontrib><creatorcontrib>Klungel, Olaf H</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>ProQuest Health Management</collection><collection>Medical Database</collection><collection>ProQuest Research Library</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of clinical epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Schmidt, Amand F</au><au>Groenwold, Rolf H.H</au><au>Knol, Mirjam J</au><au>Hoes, Arno W</au><au>Nielen, Mirjam</au><au>Roes, Kit C.B</au><au>de Boer, Anthonius</au><au>Klungel, Olaf H</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exploring interaction effects in small samples increases rates of false-positive and false-negative findings: results from a systematic review and simulation study</atitle><jtitle>Journal of clinical epidemiology</jtitle><addtitle>J Clin Epidemiol</addtitle><date>2014-07-01</date><risdate>2014</risdate><volume>67</volume><issue>7</issue><spage>821</spage><epage>829</epage><pages>821-829</pages><issn>0895-4356</issn><eissn>1878-5921</eissn><abstract>Abstract Objective To give a comprehensive comparison of the performance of commonly applied interaction tests. Methods A literature review and simulation study was performed evaluating interaction tests on the odds ratio (OR) or the risk difference (RD) scales: Cochran Q (Q), Breslow–Day (BD), Tarone, unconditional score, likelihood ratio (LR), Wald, and relative excess risk due to interaction (RERI)-based tests. Results Review results agreed with results from our simulation study, which showed that on the OR scale, in small sample sizes (eg, number of subjects ≤ 250) the type 1 error rates of the LR test was 0.10; the BD and Tarone tests showed results around 0.05. On the RD scale, the LR and RERI tests had error rates around 0.05. On both scales, tests did not differ regarding power. When exposure prevented the outcome RERI-based tests were relatively underpowered (eg, N = 100; RERI power = 5% vs. Wald power = 18%). With increasing sample size, difference decreased. Conclusion In small samples, interaction tests differed. On the OR scale, the Tarone and BD tests are recommended. On the RD scale, the LR and RERI-based tests performed best. However, RERI-based tests are underpowered compared with other tests, when exposure prevents the outcome, and sample size is limited.</abstract><cop>New York, NY</cop><pub>Elsevier Inc</pub><pmid>24768005</pmid><doi>10.1016/j.jclinepi.2014.02.008</doi><tpages>9</tpages></addata></record> |
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| subjects | Analysis. Health state Biological and medical sciences Computer Simulation Diagnostic Errors Effect modification Epidemiologic Methods Epidemiology False Negative Reactions False Positive Reactions General aspects Heart attacks Humans Interaction Internal Medicine Literature reviews Medical research Medical sciences Odds Ratio Public health. Hygiene Public health. Hygiene-occupational medicine Relative excess risk due to interaction Review Risk Risk ratio Sample Size Simulation Statistics Statistics as Topic Subgroups |
| title | Exploring interaction effects in small samples increases rates of false-positive and false-negative findings: results from a systematic review and simulation study |
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