On scoping a test that addresses the wrong objective

The Department of Defense test and evaluation community uses power as a key metric for sizing test designs. Power depends on many elements of the design, including the selection of response variables, factors and levels, model formulation, and sample size. The experimental objectives are expressed a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Quality engineering 2019-04, Vol.31 (2), p.230-239
Hauptverfasser: Johnson, Thomas H., Medlin, Rebecca M., Freeman, Laura J., Simpson, James R.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 239
container_issue 2
container_start_page 230
container_title Quality engineering
container_volume 31
creator Johnson, Thomas H.
Medlin, Rebecca M.
Freeman, Laura J.
Simpson, James R.
description The Department of Defense test and evaluation community uses power as a key metric for sizing test designs. Power depends on many elements of the design, including the selection of response variables, factors and levels, model formulation, and sample size. The experimental objectives are expressed as hypothesis tests, and power reflects the risk associated with correctly assessing those objectives. Statistical literature refers to a different, yet equally important, type of error that is committed by giving the right answer to the wrong question. If a test design is adequately scoped to address an irrelevant objective, one could say that a Type III error occurs. In this paper, we focus on a specific Type III error that on some occasions test planners commit to reduce test size and resources. We provide a case study example that shows how reparameterizing a factor space from fewer factors with more levels per factor to a space that has more factors with fewer levels per factor fundamentally changes the hypothesis tests, and hence may no longer be aligned with the original objectives of the experiment. Despite the perceived increase in power and decrease in test resources that comes from this reparameterization, we conclude, it is not a prudent way to gain test efficiency. Through the case study example, we highlight the information that is lost in this decision and its implications on test objectives.
doi_str_mv 10.1080/08982112.2018.1479035
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2228911034</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2228911034</sourcerecordid><originalsourceid>FETCH-LOGICAL-c286t-e3517ff9a19e562ebd3cf1de993b2db5203af045d246a39becc694a2cc3e226b3</originalsourceid><addsrcrecordid>eNp9kE1LAzEQhoMoWKs_QVjwvDWZJNvkphS_oNCLnkM2H7pLu6lJaum_N0vr1dMwzPO-M_MidEvwjGCB77GQAgiBGWAiZoTNJab8DE0Ip1AzADhHk5GpR-gSXaXU40IKSSeIrYYqmbDths9KV9mlXOUvnSttbXQpuVRaV-1jKPPQ9s7k7sddowuv18ndnOoUfTw_vS9e6-Xq5W3xuKwNiCbXjnIy915qIh1vwLWWGk-sk5K2YFsOmGqPGbfAGk1l64xpJNNgDHUATUun6O7ou43he1duU33YxaGsVOUrIQnBlBWKHykTQ0rRebWN3UbHgyJYjQGpv4DUGJA6BVR0D0ddN_gQN3of4tqqrA_rEH3Ug-mSov9b_AJCWmvM</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2228911034</pqid></control><display><type>article</type><title>On scoping a test that addresses the wrong objective</title><source>EBSCOhost Business Source Complete</source><creator>Johnson, Thomas H. ; Medlin, Rebecca M. ; Freeman, Laura J. ; Simpson, James R.</creator><creatorcontrib>Johnson, Thomas H. ; Medlin, Rebecca M. ; Freeman, Laura J. ; Simpson, James R.</creatorcontrib><description>The Department of Defense test and evaluation community uses power as a key metric for sizing test designs. Power depends on many elements of the design, including the selection of response variables, factors and levels, model formulation, and sample size. The experimental objectives are expressed as hypothesis tests, and power reflects the risk associated with correctly assessing those objectives. Statistical literature refers to a different, yet equally important, type of error that is committed by giving the right answer to the wrong question. If a test design is adequately scoped to address an irrelevant objective, one could say that a Type III error occurs. In this paper, we focus on a specific Type III error that on some occasions test planners commit to reduce test size and resources. We provide a case study example that shows how reparameterizing a factor space from fewer factors with more levels per factor to a space that has more factors with fewer levels per factor fundamentally changes the hypothesis tests, and hence may no longer be aligned with the original objectives of the experiment. Despite the perceived increase in power and decrease in test resources that comes from this reparameterization, we conclude, it is not a prudent way to gain test efficiency. Through the case study example, we highlight the information that is lost in this decision and its implications on test objectives.</description><identifier>ISSN: 0898-2112</identifier><identifier>EISSN: 1532-4222</identifier><identifier>DOI: 10.1080/08982112.2018.1479035</identifier><language>eng</language><publisher>Milwaukee: Taylor &amp; Francis</publisher><subject>Case studies ; design of experiments ; Errors ; Hypotheses ; hypothesis testing ; Measurement techniques ; Objectives ; sample size determination ; Statistical power ; Type III error ; unified effect size</subject><ispartof>Quality engineering, 2019-04, Vol.31 (2), p.230-239</ispartof><rights>2018 Taylor &amp; Francis Group, LLC 2018</rights><rights>2018 Taylor &amp; Francis Group, LLC</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c286t-e3517ff9a19e562ebd3cf1de993b2db5203af045d246a39becc694a2cc3e226b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><creatorcontrib>Johnson, Thomas H.</creatorcontrib><creatorcontrib>Medlin, Rebecca M.</creatorcontrib><creatorcontrib>Freeman, Laura J.</creatorcontrib><creatorcontrib>Simpson, James R.</creatorcontrib><title>On scoping a test that addresses the wrong objective</title><title>Quality engineering</title><description>The Department of Defense test and evaluation community uses power as a key metric for sizing test designs. Power depends on many elements of the design, including the selection of response variables, factors and levels, model formulation, and sample size. The experimental objectives are expressed as hypothesis tests, and power reflects the risk associated with correctly assessing those objectives. Statistical literature refers to a different, yet equally important, type of error that is committed by giving the right answer to the wrong question. If a test design is adequately scoped to address an irrelevant objective, one could say that a Type III error occurs. In this paper, we focus on a specific Type III error that on some occasions test planners commit to reduce test size and resources. We provide a case study example that shows how reparameterizing a factor space from fewer factors with more levels per factor to a space that has more factors with fewer levels per factor fundamentally changes the hypothesis tests, and hence may no longer be aligned with the original objectives of the experiment. Despite the perceived increase in power and decrease in test resources that comes from this reparameterization, we conclude, it is not a prudent way to gain test efficiency. Through the case study example, we highlight the information that is lost in this decision and its implications on test objectives.</description><subject>Case studies</subject><subject>design of experiments</subject><subject>Errors</subject><subject>Hypotheses</subject><subject>hypothesis testing</subject><subject>Measurement techniques</subject><subject>Objectives</subject><subject>sample size determination</subject><subject>Statistical power</subject><subject>Type III error</subject><subject>unified effect size</subject><issn>0898-2112</issn><issn>1532-4222</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LAzEQhoMoWKs_QVjwvDWZJNvkphS_oNCLnkM2H7pLu6lJaum_N0vr1dMwzPO-M_MidEvwjGCB77GQAgiBGWAiZoTNJab8DE0Ip1AzADhHk5GpR-gSXaXU40IKSSeIrYYqmbDths9KV9mlXOUvnSttbXQpuVRaV-1jKPPQ9s7k7sddowuv18ndnOoUfTw_vS9e6-Xq5W3xuKwNiCbXjnIy915qIh1vwLWWGk-sk5K2YFsOmGqPGbfAGk1l64xpJNNgDHUATUun6O7ou43he1duU33YxaGsVOUrIQnBlBWKHykTQ0rRebWN3UbHgyJYjQGpv4DUGJA6BVR0D0ddN_gQN3of4tqqrA_rEH3Ug-mSov9b_AJCWmvM</recordid><startdate>20190403</startdate><enddate>20190403</enddate><creator>Johnson, Thomas H.</creator><creator>Medlin, Rebecca M.</creator><creator>Freeman, Laura J.</creator><creator>Simpson, James R.</creator><general>Taylor &amp; Francis</general><general>Taylor &amp; Francis Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>U9A</scope></search><sort><creationdate>20190403</creationdate><title>On scoping a test that addresses the wrong objective</title><author>Johnson, Thomas H. ; Medlin, Rebecca M. ; Freeman, Laura J. ; Simpson, James R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c286t-e3517ff9a19e562ebd3cf1de993b2db5203af045d246a39becc694a2cc3e226b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Case studies</topic><topic>design of experiments</topic><topic>Errors</topic><topic>Hypotheses</topic><topic>hypothesis testing</topic><topic>Measurement techniques</topic><topic>Objectives</topic><topic>sample size determination</topic><topic>Statistical power</topic><topic>Type III error</topic><topic>unified effect size</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Johnson, Thomas H.</creatorcontrib><creatorcontrib>Medlin, Rebecca M.</creatorcontrib><creatorcontrib>Freeman, Laura J.</creatorcontrib><creatorcontrib>Simpson, James R.</creatorcontrib><collection>CrossRef</collection><jtitle>Quality engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Johnson, Thomas H.</au><au>Medlin, Rebecca M.</au><au>Freeman, Laura J.</au><au>Simpson, James R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>On scoping a test that addresses the wrong objective</atitle><jtitle>Quality engineering</jtitle><date>2019-04-03</date><risdate>2019</risdate><volume>31</volume><issue>2</issue><spage>230</spage><epage>239</epage><pages>230-239</pages><issn>0898-2112</issn><eissn>1532-4222</eissn><abstract>The Department of Defense test and evaluation community uses power as a key metric for sizing test designs. Power depends on many elements of the design, including the selection of response variables, factors and levels, model formulation, and sample size. The experimental objectives are expressed as hypothesis tests, and power reflects the risk associated with correctly assessing those objectives. Statistical literature refers to a different, yet equally important, type of error that is committed by giving the right answer to the wrong question. If a test design is adequately scoped to address an irrelevant objective, one could say that a Type III error occurs. In this paper, we focus on a specific Type III error that on some occasions test planners commit to reduce test size and resources. We provide a case study example that shows how reparameterizing a factor space from fewer factors with more levels per factor to a space that has more factors with fewer levels per factor fundamentally changes the hypothesis tests, and hence may no longer be aligned with the original objectives of the experiment. Despite the perceived increase in power and decrease in test resources that comes from this reparameterization, we conclude, it is not a prudent way to gain test efficiency. Through the case study example, we highlight the information that is lost in this decision and its implications on test objectives.</abstract><cop>Milwaukee</cop><pub>Taylor &amp; Francis</pub><doi>10.1080/08982112.2018.1479035</doi><tpages>10</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0898-2112
ispartof Quality engineering, 2019-04, Vol.31 (2), p.230-239
issn 0898-2112
1532-4222
language eng
recordid cdi_proquest_journals_2228911034
source EBSCOhost Business Source Complete
subjects Case studies
design of experiments
Errors
Hypotheses
hypothesis testing
Measurement techniques
Objectives
sample size determination
Statistical power
Type III error
unified effect size
title On scoping a test that addresses the wrong objective
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T01%3A01%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=On%20scoping%20a%20test%20that%20addresses%20the%20wrong%20objective&rft.jtitle=Quality%20engineering&rft.au=Johnson,%20Thomas%20H.&rft.date=2019-04-03&rft.volume=31&rft.issue=2&rft.spage=230&rft.epage=239&rft.pages=230-239&rft.issn=0898-2112&rft.eissn=1532-4222&rft_id=info:doi/10.1080/08982112.2018.1479035&rft_dat=%3Cproquest_cross%3E2228911034%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2228911034&rft_id=info:pmid/&rfr_iscdi=true