Latent Variable Analyses of Age Trends of Cognition in the Health and Retirement Study, 1992-2004
The present study was conducted to better describe age trends in cognition among older adults in the longitudinal Health and Retirement Study (HRS) from 1992 to 2004 ( N > 17,000). The authors used contemporary latent variable models to organize this information in terms of both cross-sectional a...
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| Veröffentlicht in: | Psychology and aging 2007-09, Vol.22 (3), p.525-545 |
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| container_title | Psychology and aging |
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| creator | McArdle, John J Fisher, Gwenith G Kadlec, Kelly M |
| description | The present study was conducted to better describe age trends in cognition among older adults in the longitudinal Health and Retirement Study (HRS) from 1992 to 2004 (
N
> 17,000). The authors used contemporary latent variable models to organize this information in terms of both cross-sectional and longitudinal inferences about age and cognition. Common factor analysis results yielded evidence for at least 2 common factors, labeled Episodic Memory and Mental Status, largely separable from vocabulary. Latent path models with these common factors were based on demographic characteristics. Multilevel models of factorial invariance over age indicated that at least 2 common factors were needed. Latent curve models of episodic memory were based on age at testing and showed substantial age differences and age changes, including impacts due to retesting as well as several time-invariant and time-varying predictors. |
| doi_str_mv | 10.1037/0882-7974.22.3.525 |
| format | Article |
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N
> 17,000). The authors used contemporary latent variable models to organize this information in terms of both cross-sectional and longitudinal inferences about age and cognition. Common factor analysis results yielded evidence for at least 2 common factors, labeled Episodic Memory and Mental Status, largely separable from vocabulary. Latent path models with these common factors were based on demographic characteristics. Multilevel models of factorial invariance over age indicated that at least 2 common factors were needed. Latent curve models of episodic memory were based on age at testing and showed substantial age differences and age changes, including impacts due to retesting as well as several time-invariant and time-varying predictors.</description><identifier>ISSN: 0882-7974</identifier><identifier>EISSN: 1939-1498</identifier><identifier>DOI: 10.1037/0882-7974.22.3.525</identifier><identifier>PMID: 17874952</identifier><identifier>CODEN: PAGIEL</identifier><language>eng</language><publisher>Washington, DC: American Psychological Association</publisher><subject>Adult. Elderly ; Age ; Age Differences ; Aged ; Aged, 80 and over ; Aging ; Aging - psychology ; Biological and medical sciences ; Cognition ; Cognition & reasoning ; Developmental psychology ; Discriminant analysis ; Elderly people ; Episodic memory ; Factor Analysis ; Female ; Fundamental and applied biological sciences. Psychology ; Health Surveys ; Human ; Humans ; Individuality ; Latent variable analysis ; Latent Variables ; Longitudinal Studies ; Male ; Mental Recall ; Mental Status Schedule - statistics & numerical data ; Middle Aged ; Models, Statistical ; Neuropsychological Tests - statistics & numerical data ; Older people ; Psychology. Psychoanalysis. Psychiatry ; Psychology. Psychophysiology ; Psychometrics ; Retention (Psychology) ; Retirement ; Sex Factors ; Structural Equation Modeling ; Studies ; United States</subject><ispartof>Psychology and aging, 2007-09, Vol.22 (3), p.525-545</ispartof><rights>2007 American Psychological Association</rights><rights>2007 INIST-CNRS</rights><rights>(PsycINFO Database Record (c) 2007 APA, all rights reserved).</rights><rights>Copyright American Psychological Association Sep 2007</rights><rights>2007, American Psychological Association</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a481t-82ce40665a859bcc34f4184c76f759dc096b41ad45b76c4c96403bb5f99d71b43</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,778,782,27911,27912,30986,30987</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=19075461$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17874952$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Zacks, Rose T</contributor><creatorcontrib>McArdle, John J</creatorcontrib><creatorcontrib>Fisher, Gwenith G</creatorcontrib><creatorcontrib>Kadlec, Kelly M</creatorcontrib><title>Latent Variable Analyses of Age Trends of Cognition in the Health and Retirement Study, 1992-2004</title><title>Psychology and aging</title><addtitle>Psychol Aging</addtitle><description>The present study was conducted to better describe age trends in cognition among older adults in the longitudinal Health and Retirement Study (HRS) from 1992 to 2004 (
N
> 17,000). The authors used contemporary latent variable models to organize this information in terms of both cross-sectional and longitudinal inferences about age and cognition. Common factor analysis results yielded evidence for at least 2 common factors, labeled Episodic Memory and Mental Status, largely separable from vocabulary. Latent path models with these common factors were based on demographic characteristics. Multilevel models of factorial invariance over age indicated that at least 2 common factors were needed. Latent curve models of episodic memory were based on age at testing and showed substantial age differences and age changes, including impacts due to retesting as well as several time-invariant and time-varying predictors.</description><subject>Adult. Elderly</subject><subject>Age</subject><subject>Age Differences</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Aging</subject><subject>Aging - psychology</subject><subject>Biological and medical sciences</subject><subject>Cognition</subject><subject>Cognition & reasoning</subject><subject>Developmental psychology</subject><subject>Discriminant analysis</subject><subject>Elderly people</subject><subject>Episodic memory</subject><subject>Factor Analysis</subject><subject>Female</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Health Surveys</subject><subject>Human</subject><subject>Humans</subject><subject>Individuality</subject><subject>Latent variable analysis</subject><subject>Latent Variables</subject><subject>Longitudinal Studies</subject><subject>Male</subject><subject>Mental Recall</subject><subject>Mental Status Schedule - statistics & numerical data</subject><subject>Middle Aged</subject><subject>Models, Statistical</subject><subject>Neuropsychological Tests - statistics & numerical data</subject><subject>Older people</subject><subject>Psychology. Psychoanalysis. Psychiatry</subject><subject>Psychology. Psychophysiology</subject><subject>Psychometrics</subject><subject>Retention (Psychology)</subject><subject>Retirement</subject><subject>Sex Factors</subject><subject>Structural Equation Modeling</subject><subject>Studies</subject><subject>United States</subject><issn>0882-7974</issn><issn>1939-1498</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7QJ</sourceid><recordid>eNqF0UGL1DAUB_AgijuufgEPEkS9aMckfWmS4zDsusKAoKvX8Jqms106bTdJD_PtzTiDqyJ6Cg9-7_8gf0Kec7bkrFTvmdaiUEbBUohluZRCPiALbkpTcDD6IVn8BGfkSYy3jDHFjXpMzrjSCowUC4IbTH5I9BuGDuve09WA_T76SMeWrraeXgc_ND-m9bgdutSNA-0Gmm48vfLYpxuKQ0M_-9QFvzskfUlzs39HuTGiEIzBU_KoxT76Z6f3nHy9vLheXxWbTx8-rlebAkHzVGjhPLCqkqilqZ0roQWuwamqVdI0jpmqBo4NyFpVDpypgJV1LVtjGsVrKM_Jm2PuFMa72cdkd110vu9x8OMcbaWF4ULo_0KpOGcVlBm-_APejnPI_5PDOIASsoR_IcGlBsWZyUgckQtjjMG3dgrdDsPecmYPXdpDVfZQlRXCljZ3mZdenJLneueb-5VTeRm8PgGMDvs24OC6eO8MUxIqnt3bo8MJ7RT3DkPqXO-jm0NuN9kJt7-effV3_Tv7DogXvj4</recordid><startdate>20070901</startdate><enddate>20070901</enddate><creator>McArdle, John J</creator><creator>Fisher, Gwenith G</creator><creator>Kadlec, Kelly M</creator><general>American Psychological Association</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>7QJ</scope><scope>NAPCQ</scope><scope>7RZ</scope><scope>PSYQQ</scope><scope>7X8</scope></search><sort><creationdate>20070901</creationdate><title>Latent Variable Analyses of Age Trends of Cognition in the Health and Retirement Study, 1992-2004</title><author>McArdle, John J ; Fisher, Gwenith G ; Kadlec, Kelly M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a481t-82ce40665a859bcc34f4184c76f759dc096b41ad45b76c4c96403bb5f99d71b43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Adult. Elderly</topic><topic>Age</topic><topic>Age Differences</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Aging</topic><topic>Aging - psychology</topic><topic>Biological and medical sciences</topic><topic>Cognition</topic><topic>Cognition & reasoning</topic><topic>Developmental psychology</topic><topic>Discriminant analysis</topic><topic>Elderly people</topic><topic>Episodic memory</topic><topic>Factor Analysis</topic><topic>Female</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Health Surveys</topic><topic>Human</topic><topic>Humans</topic><topic>Individuality</topic><topic>Latent variable analysis</topic><topic>Latent Variables</topic><topic>Longitudinal Studies</topic><topic>Male</topic><topic>Mental Recall</topic><topic>Mental Status Schedule - statistics & numerical data</topic><topic>Middle Aged</topic><topic>Models, Statistical</topic><topic>Neuropsychological Tests - statistics & numerical data</topic><topic>Older people</topic><topic>Psychology. Psychoanalysis. Psychiatry</topic><topic>Psychology. Psychophysiology</topic><topic>Psychometrics</topic><topic>Retention (Psychology)</topic><topic>Retirement</topic><topic>Sex Factors</topic><topic>Structural Equation Modeling</topic><topic>Studies</topic><topic>United States</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>McArdle, John J</creatorcontrib><creatorcontrib>Fisher, Gwenith G</creatorcontrib><creatorcontrib>Kadlec, Kelly M</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>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Nursing & Allied Health Premium</collection><collection>APA PsycArticles®</collection><collection>ProQuest One Psychology</collection><collection>MEDLINE - Academic</collection><jtitle>Psychology and aging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>McArdle, John J</au><au>Fisher, Gwenith G</au><au>Kadlec, Kelly M</au><au>Zacks, Rose T</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Latent Variable Analyses of Age Trends of Cognition in the Health and Retirement Study, 1992-2004</atitle><jtitle>Psychology and aging</jtitle><addtitle>Psychol Aging</addtitle><date>2007-09-01</date><risdate>2007</risdate><volume>22</volume><issue>3</issue><spage>525</spage><epage>545</epage><pages>525-545</pages><issn>0882-7974</issn><eissn>1939-1498</eissn><coden>PAGIEL</coden><abstract>The present study was conducted to better describe age trends in cognition among older adults in the longitudinal Health and Retirement Study (HRS) from 1992 to 2004 (
N
> 17,000). The authors used contemporary latent variable models to organize this information in terms of both cross-sectional and longitudinal inferences about age and cognition. Common factor analysis results yielded evidence for at least 2 common factors, labeled Episodic Memory and Mental Status, largely separable from vocabulary. Latent path models with these common factors were based on demographic characteristics. Multilevel models of factorial invariance over age indicated that at least 2 common factors were needed. Latent curve models of episodic memory were based on age at testing and showed substantial age differences and age changes, including impacts due to retesting as well as several time-invariant and time-varying predictors.</abstract><cop>Washington, DC</cop><pub>American Psychological Association</pub><pmid>17874952</pmid><doi>10.1037/0882-7974.22.3.525</doi><tpages>21</tpages></addata></record> |
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| subjects | Adult. Elderly Age Age Differences Aged Aged, 80 and over Aging Aging - psychology Biological and medical sciences Cognition Cognition & reasoning Developmental psychology Discriminant analysis Elderly people Episodic memory Factor Analysis Female Fundamental and applied biological sciences. Psychology Health Surveys Human Humans Individuality Latent variable analysis Latent Variables Longitudinal Studies Male Mental Recall Mental Status Schedule - statistics & numerical data Middle Aged Models, Statistical Neuropsychological Tests - statistics & numerical data Older people Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Psychometrics Retention (Psychology) Retirement Sex Factors Structural Equation Modeling Studies United States |
| title | Latent Variable Analyses of Age Trends of Cognition in the Health and Retirement Study, 1992-2004 |
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