The impact of non-normality, sample size and estimation technique on goodness-of-fit measures in structural equation modeling: evidence from ten empirical models of travel behavior
Ten empirical models of travel behavior are used to measure the variability of structural equation model goodness-of-fit as a function of sample size, multivariate kurtosis, and estimation technique. The estimation techniques are maximum likelihood, asymptotic distribution free, bootstrapping, and t...
Gespeichert in:
| Veröffentlicht in: | Quality & quantity 2010-04, Vol.44 (3), p.427-445 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 445 |
|---|---|
| container_issue | 3 |
| container_start_page | 427 |
| container_title | Quality & quantity |
| container_volume | 44 |
| creator | Ory, David T. Mokhtarian, Patricia L. |
| description | Ten empirical models of travel behavior are used to measure the variability of structural equation model goodness-of-fit as a function of sample size, multivariate kurtosis, and estimation technique. The estimation techniques are maximum likelihood, asymptotic distribution free, bootstrapping, and the M
plus
approach. The results highlight the divergence of these techniques when sample sizes are small and/or multivariate kurtosis high. Recommendations include using multiple estimation techniques and, when sample sizes are large, sampling the data and reestimating the models to test both the robustness of the specifications and to quantify, to some extent, the large sample bias inherent in the
χ
2
test statistic. |
| doi_str_mv | 10.1007/s11135-008-9215-6 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_758120965</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>758120965</sourcerecordid><originalsourceid>FETCH-LOGICAL-c379t-a9ba3977fda9ca141e5e2331d685679154419c4f9195c3753fff9d7f8ce4a5f43</originalsourceid><addsrcrecordid>eNqNkcGKFDEURYMo2LZ-gLvgxo0Zk0pSqbiTYXSEATfjOmRSL90ZqpKaJNUwfpcfaNoSBEFw9Qicc8l7F6HXjF4wStX7whjjklA6EN0xSfonaMek4kQNQj5FO0o5J5Ip9Ry9KOWe0mYJtUM_bo-Aw7xYV3HyOKZIYsqznUJ9fIeLnZcJcAnfAds4Yig1zLaGFHEFd4zhYQXcHoeUxgilkOSJDxXPYMuaoeAQcal5dXXNdsLwsG7ynEaYQjx8wHAKI0QH2Oc0t9CIYV5CDq7hv6hy_lbN9gQTvoOjPYWUX6Jn3k4FXv2ee_Tt09Xt5TW5-fr5y-XHG-K40pVYfWe5VsqPVjvLBAMJHeds7AfZK82kEEw74TXTshmSe-_1qPzgQFjpBd-jt1vuklPbtFQzh-JgmmyEtBaj5MA6qnv5HyQfOiEFb-Sbv8j7tObY1jAd5X0_dG3sEdsgl1MpGbxZcjt8fjSMmnPfZuvbtL7NuW_TN6fbnNLYeID8J_jf0k_wgbEy</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>203668220</pqid></control><display><type>article</type><title>The impact of non-normality, sample size and estimation technique on goodness-of-fit measures in structural equation modeling: evidence from ten empirical models of travel behavior</title><source>Sociological Abstracts</source><source>SpringerLink Journals - AutoHoldings</source><creator>Ory, David T. ; Mokhtarian, Patricia L.</creator><creatorcontrib>Ory, David T. ; Mokhtarian, Patricia L.</creatorcontrib><description>Ten empirical models of travel behavior are used to measure the variability of structural equation model goodness-of-fit as a function of sample size, multivariate kurtosis, and estimation technique. The estimation techniques are maximum likelihood, asymptotic distribution free, bootstrapping, and the M
plus
approach. The results highlight the divergence of these techniques when sample sizes are small and/or multivariate kurtosis high. Recommendations include using multiple estimation techniques and, when sample sizes are large, sampling the data and reestimating the models to test both the robustness of the specifications and to quantify, to some extent, the large sample bias inherent in the
χ
2
test statistic.</description><identifier>ISSN: 0033-5177</identifier><identifier>EISSN: 1573-7845</identifier><identifier>DOI: 10.1007/s11135-008-9215-6</identifier><identifier>CODEN: QQEJAV</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Bias ; Central business districts ; Datasets ; Discriminant analysis ; Estimation ; Kurtosis ; Measurement ; Methodology ; Methodology of the Social Sciences ; Neighborhoods ; Personality ; Research methods ; Samples ; Sampling ; Simulation ; Social Sciences ; Structural equation modeling ; Structural Models ; Transport ; Travel</subject><ispartof>Quality & quantity, 2010-04, Vol.44 (3), p.427-445</ispartof><rights>Springer Science+Business Media B.V. 2009</rights><rights>Springer Science+Business Media B.V. 2010</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c379t-a9ba3977fda9ca141e5e2331d685679154419c4f9195c3753fff9d7f8ce4a5f43</citedby><cites>FETCH-LOGICAL-c379t-a9ba3977fda9ca141e5e2331d685679154419c4f9195c3753fff9d7f8ce4a5f43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11135-008-9215-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11135-008-9215-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27335,27915,27916,33765,33766,41479,42548,51310</link.rule.ids></links><search><creatorcontrib>Ory, David T.</creatorcontrib><creatorcontrib>Mokhtarian, Patricia L.</creatorcontrib><title>The impact of non-normality, sample size and estimation technique on goodness-of-fit measures in structural equation modeling: evidence from ten empirical models of travel behavior</title><title>Quality & quantity</title><addtitle>Qual Quant</addtitle><description>Ten empirical models of travel behavior are used to measure the variability of structural equation model goodness-of-fit as a function of sample size, multivariate kurtosis, and estimation technique. The estimation techniques are maximum likelihood, asymptotic distribution free, bootstrapping, and the M
plus
approach. The results highlight the divergence of these techniques when sample sizes are small and/or multivariate kurtosis high. Recommendations include using multiple estimation techniques and, when sample sizes are large, sampling the data and reestimating the models to test both the robustness of the specifications and to quantify, to some extent, the large sample bias inherent in the
χ
2
test statistic.</description><subject>Bias</subject><subject>Central business districts</subject><subject>Datasets</subject><subject>Discriminant analysis</subject><subject>Estimation</subject><subject>Kurtosis</subject><subject>Measurement</subject><subject>Methodology</subject><subject>Methodology of the Social Sciences</subject><subject>Neighborhoods</subject><subject>Personality</subject><subject>Research methods</subject><subject>Samples</subject><subject>Sampling</subject><subject>Simulation</subject><subject>Social Sciences</subject><subject>Structural equation modeling</subject><subject>Structural Models</subject><subject>Transport</subject><subject>Travel</subject><issn>0033-5177</issn><issn>1573-7845</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>BHHNA</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqNkcGKFDEURYMo2LZ-gLvgxo0Zk0pSqbiTYXSEATfjOmRSL90ZqpKaJNUwfpcfaNoSBEFw9Qicc8l7F6HXjF4wStX7whjjklA6EN0xSfonaMek4kQNQj5FO0o5J5Ip9Ry9KOWe0mYJtUM_bo-Aw7xYV3HyOKZIYsqznUJ9fIeLnZcJcAnfAds4Yig1zLaGFHEFd4zhYQXcHoeUxgilkOSJDxXPYMuaoeAQcal5dXXNdsLwsG7ynEaYQjx8wHAKI0QH2Oc0t9CIYV5CDq7hv6hy_lbN9gQTvoOjPYWUX6Jn3k4FXv2ee_Tt09Xt5TW5-fr5y-XHG-K40pVYfWe5VsqPVjvLBAMJHeds7AfZK82kEEw74TXTshmSe-_1qPzgQFjpBd-jt1vuklPbtFQzh-JgmmyEtBaj5MA6qnv5HyQfOiEFb-Sbv8j7tObY1jAd5X0_dG3sEdsgl1MpGbxZcjt8fjSMmnPfZuvbtL7NuW_TN6fbnNLYeID8J_jf0k_wgbEy</recordid><startdate>20100401</startdate><enddate>20100401</enddate><creator>Ory, David T.</creator><creator>Mokhtarian, Patricia L.</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7U4</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88G</scope><scope>88J</scope><scope>8BJ</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BHHNA</scope><scope>CCPQU</scope><scope>DWI</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HEHIP</scope><scope>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>M0C</scope><scope>M2M</scope><scope>M2O</scope><scope>M2R</scope><scope>M2S</scope><scope>MBDVC</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>WZK</scope></search><sort><creationdate>20100401</creationdate><title>The impact of non-normality, sample size and estimation technique on goodness-of-fit measures in structural equation modeling: evidence from ten empirical models of travel behavior</title><author>Ory, David T. ; Mokhtarian, Patricia L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c379t-a9ba3977fda9ca141e5e2331d685679154419c4f9195c3753fff9d7f8ce4a5f43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Bias</topic><topic>Central business districts</topic><topic>Datasets</topic><topic>Discriminant analysis</topic><topic>Estimation</topic><topic>Kurtosis</topic><topic>Measurement</topic><topic>Methodology</topic><topic>Methodology of the Social Sciences</topic><topic>Neighborhoods</topic><topic>Personality</topic><topic>Research methods</topic><topic>Samples</topic><topic>Sampling</topic><topic>Simulation</topic><topic>Social Sciences</topic><topic>Structural equation modeling</topic><topic>Structural Models</topic><topic>Transport</topic><topic>Travel</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ory, David T.</creatorcontrib><creatorcontrib>Mokhtarian, Patricia L.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Sociological Abstracts (pre-2017)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Social Science Database (Alumni Edition)</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Sociological Abstracts</collection><collection>ProQuest One Community College</collection><collection>Sociological Abstracts</collection><collection>ProQuest Central Korea</collection><collection>International Bibliography of the Social Sciences</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Sociology Collection</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Psychology Database</collection><collection>Research Library</collection><collection>Social Science Database</collection><collection>Sociology Database</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</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 One Psychology</collection><collection>ProQuest Central Basic</collection><collection>Sociological Abstracts (Ovid)</collection><jtitle>Quality & quantity</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ory, David T.</au><au>Mokhtarian, Patricia L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The impact of non-normality, sample size and estimation technique on goodness-of-fit measures in structural equation modeling: evidence from ten empirical models of travel behavior</atitle><jtitle>Quality & quantity</jtitle><stitle>Qual Quant</stitle><date>2010-04-01</date><risdate>2010</risdate><volume>44</volume><issue>3</issue><spage>427</spage><epage>445</epage><pages>427-445</pages><issn>0033-5177</issn><eissn>1573-7845</eissn><coden>QQEJAV</coden><abstract>Ten empirical models of travel behavior are used to measure the variability of structural equation model goodness-of-fit as a function of sample size, multivariate kurtosis, and estimation technique. The estimation techniques are maximum likelihood, asymptotic distribution free, bootstrapping, and the M
plus
approach. The results highlight the divergence of these techniques when sample sizes are small and/or multivariate kurtosis high. Recommendations include using multiple estimation techniques and, when sample sizes are large, sampling the data and reestimating the models to test both the robustness of the specifications and to quantify, to some extent, the large sample bias inherent in the
χ
2
test statistic.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s11135-008-9215-6</doi><tpages>19</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0033-5177 |
| ispartof | Quality & quantity, 2010-04, Vol.44 (3), p.427-445 |
| issn | 0033-5177 1573-7845 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_758120965 |
| source | Sociological Abstracts; SpringerLink Journals - AutoHoldings |
| subjects | Bias Central business districts Datasets Discriminant analysis Estimation Kurtosis Measurement Methodology Methodology of the Social Sciences Neighborhoods Personality Research methods Samples Sampling Simulation Social Sciences Structural equation modeling Structural Models Transport Travel |
| title | The impact of non-normality, sample size and estimation technique on goodness-of-fit measures in structural equation modeling: evidence from ten empirical models of travel behavior |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T01%3A47%3A01IST&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=The%20impact%20of%20non-normality,%20sample%20size%20and%20estimation%20technique%20on%20goodness-of-fit%20measures%20in%20structural%20equation%20modeling:%20evidence%20from%20ten%20empirical%20models%20of%20travel%20behavior&rft.jtitle=Quality%20&%20quantity&rft.au=Ory,%20David%20T.&rft.date=2010-04-01&rft.volume=44&rft.issue=3&rft.spage=427&rft.epage=445&rft.pages=427-445&rft.issn=0033-5177&rft.eissn=1573-7845&rft.coden=QQEJAV&rft_id=info:doi/10.1007/s11135-008-9215-6&rft_dat=%3Cproquest_cross%3E758120965%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=203668220&rft_id=info:pmid/&rfr_iscdi=true |