Factor Structure of the ARIC-NCS Neuropsychological Battery: An Evaluation of Invariance Across Vascular Factors and Demographic Characteristics

Neuropsychological test batteries are designed to assess cognition in detail by measuring cognitive performance in multiple domains. This study examines the factor structure of tests from the ARIC-NCS battery overall and across informative subgroups defined by demographic and vascular risk factors i...

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Veröffentlicht in:Psychological assessment 2016-12, Vol.28 (12), p.1674-1683
Hauptverfasser: Rawlings, Andreea M., Bandeen-Roche, Karen, Gross, Alden L., Gottesman, Rebecca F., Coker, Laura H., Penman, Alan D., Sharrett, A. Richey, Mosley, Thomas H.
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container_end_page 1683
container_issue 12
container_start_page 1674
container_title Psychological assessment
container_volume 28
creator Rawlings, Andreea M.
Bandeen-Roche, Karen
Gross, Alden L.
Gottesman, Rebecca F.
Coker, Laura H.
Penman, Alan D.
Sharrett, A. Richey
Mosley, Thomas H.
description Neuropsychological test batteries are designed to assess cognition in detail by measuring cognitive performance in multiple domains. This study examines the factor structure of tests from the ARIC-NCS battery overall and across informative subgroups defined by demographic and vascular risk factors in a population of older adults. We analyzed neuropsychological test scores from 6,413 participants in the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS) examined in 2011-2013. Confirmatory factor analysis (CFA) was used to assess the fit of an a priori hypothesized 3-domain model, and fit statistics were calculated and compared to 1- and 2-domain models. Additionally, we tested for stability (invariance) of factor structures among different subgroups defined by diabetes, hypertension, age, sex, race, and education. Mean age of participants was 76 years, 76% were White, and 60% were female. CFA on the a priori hypothesized 3-domain structure, including memory, sustained attention and processing speed, and language, fit the data better (comparative fit index [CFI] = 0.973, root mean square error of approximation [RMSEA] = 0.059) than the 2-domain (CFI = 0.960, RMSEA = 0.070) and 1-domain (CFI = 0.947, RMSEA = 0.080) models. Bayesian information criterion value was lowest, and quantile-quantile plots indicated better fit, for the 3-domain model. Additionally, multiple-group CFA supported a common structure across the tested demographic subgroups, and indicated strict invariance by diabetes and hypertension status. In this community-based population of older adults with varying levels of cognitive performance, the a priori hypothesized 3-domain structure fit the data well. The identified factors were configurally invariant by age, sex, race, and education, and strictly invariant by diabetes and hypertension status.
doi_str_mv 10.1037/pas0000293
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Richey</creatorcontrib><creatorcontrib>Mosley, Thomas H.</creatorcontrib><title>Factor Structure of the ARIC-NCS Neuropsychological Battery: An Evaluation of Invariance Across Vascular Factors and Demographic Characteristics</title><title>Psychological assessment</title><addtitle>Psychol Assess</addtitle><description>Neuropsychological test batteries are designed to assess cognition in detail by measuring cognitive performance in multiple domains. This study examines the factor structure of tests from the ARIC-NCS battery overall and across informative subgroups defined by demographic and vascular risk factors in a population of older adults. We analyzed neuropsychological test scores from 6,413 participants in the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS) examined in 2011-2013. Confirmatory factor analysis (CFA) was used to assess the fit of an a priori hypothesized 3-domain model, and fit statistics were calculated and compared to 1- and 2-domain models. 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In this community-based population of older adults with varying levels of cognitive performance, the a priori hypothesized 3-domain structure fit the data well. The identified factors were configurally invariant by age, sex, race, and education, and strictly invariant by diabetes and hypertension status.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Aging</subject><subject>Atherosclerosis</subject><subject>Bayes Theorem</subject><subject>Cognition</subject><subject>Cognition &amp; reasoning</subject><subject>Demographic Characteristics</subject><subject>Demographics</subject><subject>Demography</subject><subject>Diabetes Mellitus - psychology</subject><subject>Discriminant analysis</subject><subject>Factor Analysis</subject><subject>Factor Analysis, Statistical</subject><subject>Female</subject><subject>Human</subject><subject>Humans</subject><subject>Hypertension - psychology</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Statistical</subject><subject>Neuropsychological Assessment</subject><subject>Neuropsychological Tests</subject><subject>Neuropsychology</subject><subject>Prospective Studies</subject><subject>Risk Factors</subject><issn>1040-3590</issn><issn>1939-134X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kt9qFDEUxgdRbK3e-AAS8EaE0WQymWS8ENZpqwulgi3iXTibyeymzE7Gk8zCvkUf2Yxb658LQyDhnF--5OQ7Wfac0TeMcvl2hEDTKGr-IDtmNa9zxstvD9OeljTnoqZH2ZMQbihlJVficXZUVHU1x4-z23Mw0SO5ijiZOKElviNxY8niy7LJL5srcmkn9GPYm43v_doZ6MkHiNHi_h1ZDORsB_0E0flhPrkcdoAOBpMEDPoQyFcIZuoByeGiQGBoyand-jXCuHGGNBvAlLLoQnQmPM0eddAH--xuPcmuz8-um0_5xeePy2ZxkUMpi5hbqSolBHRV26ZAW3emM2XR8ZK3plNtqpyaUnHLhRCM11LV9SpNySgTsOIn2fuD7DittrY1dogIvR7RbQH32oPTf2cGt9Frv9OCMlVwngRe3Qmg_z7ZEPXWBWP7Hgbrp6ATVVVClkwk9OU_6I2fcEjVJaoUklYyefc_SkomC6WUTNTrA_Xzd9F2909mVM_doH93Q4Jf_FnkPfrL_gTkBwBG0LPHgMmD3ibLEFPhs5gulGaFZpUs-Q-h58ER</recordid><startdate>20161201</startdate><enddate>20161201</enddate><creator>Rawlings, Andreea M.</creator><creator>Bandeen-Roche, Karen</creator><creator>Gross, Alden L.</creator><creator>Gottesman, Rebecca F.</creator><creator>Coker, Laura H.</creator><creator>Penman, Alan D.</creator><creator>Sharrett, A. 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Richey</creatorcontrib><creatorcontrib>Mosley, Thomas H.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>APA PsycArticles®</collection><collection>ProQuest One Psychology</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Psychological assessment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rawlings, Andreea M.</au><au>Bandeen-Roche, Karen</au><au>Gross, Alden L.</au><au>Gottesman, Rebecca F.</au><au>Coker, Laura H.</au><au>Penman, Alan D.</au><au>Sharrett, A. Richey</au><au>Mosley, Thomas H.</au><au>Ben-Porath, Yossef S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Factor Structure of the ARIC-NCS Neuropsychological Battery: An Evaluation of Invariance Across Vascular Factors and Demographic Characteristics</atitle><jtitle>Psychological assessment</jtitle><addtitle>Psychol Assess</addtitle><date>2016-12-01</date><risdate>2016</risdate><volume>28</volume><issue>12</issue><spage>1674</spage><epage>1683</epage><pages>1674-1683</pages><issn>1040-3590</issn><eissn>1939-134X</eissn><abstract>Neuropsychological test batteries are designed to assess cognition in detail by measuring cognitive performance in multiple domains. This study examines the factor structure of tests from the ARIC-NCS battery overall and across informative subgroups defined by demographic and vascular risk factors in a population of older adults. We analyzed neuropsychological test scores from 6,413 participants in the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS) examined in 2011-2013. Confirmatory factor analysis (CFA) was used to assess the fit of an a priori hypothesized 3-domain model, and fit statistics were calculated and compared to 1- and 2-domain models. Additionally, we tested for stability (invariance) of factor structures among different subgroups defined by diabetes, hypertension, age, sex, race, and education. Mean age of participants was 76 years, 76% were White, and 60% were female. CFA on the a priori hypothesized 3-domain structure, including memory, sustained attention and processing speed, and language, fit the data better (comparative fit index [CFI] = 0.973, root mean square error of approximation [RMSEA] = 0.059) than the 2-domain (CFI = 0.960, RMSEA = 0.070) and 1-domain (CFI = 0.947, RMSEA = 0.080) models. Bayesian information criterion value was lowest, and quantile-quantile plots indicated better fit, for the 3-domain model. Additionally, multiple-group CFA supported a common structure across the tested demographic subgroups, and indicated strict invariance by diabetes and hypertension status. In this community-based population of older adults with varying levels of cognitive performance, the a priori hypothesized 3-domain structure fit the data well. The identified factors were configurally invariant by age, sex, race, and education, and strictly invariant by diabetes and hypertension status.</abstract><cop>United States</cop><pub>American Psychological Association</pub><pmid>26963590</pmid><doi>10.1037/pas0000293</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-4903-7360</orcidid><oa>free_for_read</oa></addata></record>
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subjects Aged
Aged, 80 and over
Aging
Atherosclerosis
Bayes Theorem
Cognition
Cognition & reasoning
Demographic Characteristics
Demographics
Demography
Diabetes Mellitus - psychology
Discriminant analysis
Factor Analysis
Factor Analysis, Statistical
Female
Human
Humans
Hypertension - psychology
Male
Middle Aged
Models, Statistical
Neuropsychological Assessment
Neuropsychological Tests
Neuropsychology
Prospective Studies
Risk Factors
title Factor Structure of the ARIC-NCS Neuropsychological Battery: An Evaluation of Invariance Across Vascular Factors and Demographic Characteristics
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