Loading…
Application of Hierarchical Linear Models to Assessing Change
Recent advances in the statistical theory of hierarchical linear models should enable important breakthroughs in the measurement of psychological change and the study of correlates of change. A two-stage model of change is proposed here. At the first, or within-subject stage, an individual's st...
Saved in:
Published in: | Psychological bulletin 1987-01, Vol.101 (1), p.147-158 |
---|---|
Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-a454t-fc441ffe900845a2b78d55b81929231f35805ca919a844a0a307626840a1db813 |
---|---|
cites | |
container_end_page | 158 |
container_issue | 1 |
container_start_page | 147 |
container_title | Psychological bulletin |
container_volume | 101 |
creator | Bryk, Anthony S Raudenbush, Stephen W |
description | Recent advances in the statistical theory of hierarchical linear models should enable important breakthroughs in the measurement of psychological change and the study of correlates of change. A two-stage model of change is proposed here. At the first, or within-subject stage, an individual's status on some trait is modeled as a function of an individual growth trajectory plus random error. At the second, or between-subjects stage, the parameters of the individual growth trajectories vary as a function of differences between subjects in background characteristics, instructional experiences, and possibly experimental treatments. This two-stage conceptualization, illustrated with data on Head Start children, allows investigators to model individual change, predict future development, assess the quality of measurement instruments for distinguishing among growth trajectories, and to study systematic variation in growth trajectories as a function of background characteristics and experimental treatments. |
doi_str_mv | 10.1037/0033-2909.101.1.147 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_614288501</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3802812</sourcerecordid><originalsourceid>FETCH-LOGICAL-a454t-fc441ffe900845a2b78d55b81929231f35805ca919a844a0a307626840a1db813</originalsourceid><addsrcrecordid>eNp9kM1Lw0AQxRdRsFb_Ai_Bj2PqzH4kuwcPpagVKl70vEzTTY3EJO6mh_73bmgpXpR3GGb4vTfwGLtEmCCI_A5AiJQbMHHFSZTMj9gIjTApSqWO2ehAnLKzED4BIFeZGLH7adfVVUF91TZJWybzynnyxUc81cmiahz55KVduTokfZtMQ3AhVM06mX1Qs3bn7KSkOriL_Ryz98eHt9k8Xbw-Pc-mi5Skkn1aFlJiWToDoKUivsz1SqmlRsMNF1gKpUEVZNCQlpKABOQZz7QEwlXExJhd7XI7335vXOjtZ7vxTXxpM5RcawX_QhyEzHIUeYSu_4KQm0znCrOBEjuq8G0I3pW289UX-a1FsEPjdujTDn3GFW2UHFw3-2wKsb7SU1NU4WDViJkwMmK3O4w6sl3YFuT7qqhdsMtN_SvuB2wmiJo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>614288501</pqid></control><display><type>article</type><title>Application of Hierarchical Linear Models to Assessing Change</title><source>Applied Social Sciences Index & Abstracts (ASSIA)</source><source>International Bibliography of the Social Sciences (IBSS)</source><source>EBSCOhost APA PsycARTICLES</source><creator>Bryk, Anthony S ; Raudenbush, Stephen W</creator><creatorcontrib>Bryk, Anthony S ; Raudenbush, Stephen W</creatorcontrib><description>Recent advances in the statistical theory of hierarchical linear models should enable important breakthroughs in the measurement of psychological change and the study of correlates of change. A two-stage model of change is proposed here. At the first, or within-subject stage, an individual's status on some trait is modeled as a function of an individual growth trajectory plus random error. At the second, or between-subjects stage, the parameters of the individual growth trajectories vary as a function of differences between subjects in background characteristics, instructional experiences, and possibly experimental treatments. This two-stage conceptualization, illustrated with data on Head Start children, allows investigators to model individual change, predict future development, assess the quality of measurement instruments for distinguishing among growth trajectories, and to study systematic variation in growth trajectories as a function of background characteristics and experimental treatments.</description><identifier>ISSN: 0033-2909</identifier><identifier>EISSN: 1939-1455</identifier><identifier>DOI: 10.1037/0033-2909.101.1.147</identifier><identifier>CODEN: PSBUAI</identifier><language>eng</language><publisher>Washington, DC: American Psychological Association</publisher><subject>Biological and medical sciences ; Cognitive Development ; Development ; Fundamental and applied biological sciences. Psychology ; Human ; Mathematical Modeling ; Psychology ; Psychology. Psychoanalysis. Psychiatry ; Psychology. Psychophysiology ; Psychometrics. Statistics. Methodology ; Statistical Analysis ; Statistical Estimation ; Statistics ; Statistics. Mathematics</subject><ispartof>Psychological bulletin, 1987-01, Vol.101 (1), p.147-158</ispartof><rights>1987 American Psychological Association</rights><rights>1987 INIST-CNRS</rights><rights>Copyright American Psychological Association Jan 1987</rights><rights>1987, American Psychological Association</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a454t-fc441ffe900845a2b78d55b81929231f35805ca919a844a0a307626840a1db813</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,4024,27923,27924,27925,30999,33223</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=8116394$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Bryk, Anthony S</creatorcontrib><creatorcontrib>Raudenbush, Stephen W</creatorcontrib><title>Application of Hierarchical Linear Models to Assessing Change</title><title>Psychological bulletin</title><description>Recent advances in the statistical theory of hierarchical linear models should enable important breakthroughs in the measurement of psychological change and the study of correlates of change. A two-stage model of change is proposed here. At the first, or within-subject stage, an individual's status on some trait is modeled as a function of an individual growth trajectory plus random error. At the second, or between-subjects stage, the parameters of the individual growth trajectories vary as a function of differences between subjects in background characteristics, instructional experiences, and possibly experimental treatments. This two-stage conceptualization, illustrated with data on Head Start children, allows investigators to model individual change, predict future development, assess the quality of measurement instruments for distinguishing among growth trajectories, and to study systematic variation in growth trajectories as a function of background characteristics and experimental treatments.</description><subject>Biological and medical sciences</subject><subject>Cognitive Development</subject><subject>Development</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Human</subject><subject>Mathematical Modeling</subject><subject>Psychology</subject><subject>Psychology. Psychoanalysis. Psychiatry</subject><subject>Psychology. Psychophysiology</subject><subject>Psychometrics. Statistics. Methodology</subject><subject>Statistical Analysis</subject><subject>Statistical Estimation</subject><subject>Statistics</subject><subject>Statistics. Mathematics</subject><issn>0033-2909</issn><issn>1939-1455</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1987</creationdate><recordtype>article</recordtype><sourceid>7QJ</sourceid><sourceid>8BJ</sourceid><recordid>eNp9kM1Lw0AQxRdRsFb_Ai_Bj2PqzH4kuwcPpagVKl70vEzTTY3EJO6mh_73bmgpXpR3GGb4vTfwGLtEmCCI_A5AiJQbMHHFSZTMj9gIjTApSqWO2ehAnLKzED4BIFeZGLH7adfVVUF91TZJWybzynnyxUc81cmiahz55KVduTokfZtMQ3AhVM06mX1Qs3bn7KSkOriL_Ryz98eHt9k8Xbw-Pc-mi5Skkn1aFlJiWToDoKUivsz1SqmlRsMNF1gKpUEVZNCQlpKABOQZz7QEwlXExJhd7XI7335vXOjtZ7vxTXxpM5RcawX_QhyEzHIUeYSu_4KQm0znCrOBEjuq8G0I3pW289UX-a1FsEPjdujTDn3GFW2UHFw3-2wKsb7SU1NU4WDViJkwMmK3O4w6sl3YFuT7qqhdsMtN_SvuB2wmiJo</recordid><startdate>198701</startdate><enddate>198701</enddate><creator>Bryk, Anthony S</creator><creator>Raudenbush, Stephen W</creator><general>American Psychological Association</general><general>American Psychological Association, etc</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>FIXVA</scope><scope>FKUCP</scope><scope>IOIBA</scope><scope>K30</scope><scope>PAAUG</scope><scope>PAWHS</scope><scope>PAWZZ</scope><scope>PAXOH</scope><scope>PBHAV</scope><scope>PBQSW</scope><scope>PBYQZ</scope><scope>PCIWU</scope><scope>PCMID</scope><scope>PCZJX</scope><scope>PDGRG</scope><scope>PDWWI</scope><scope>PETMR</scope><scope>PFVGT</scope><scope>PGXDX</scope><scope>PIHIL</scope><scope>PISVA</scope><scope>PJCTQ</scope><scope>PJTMS</scope><scope>PLCHJ</scope><scope>PMHAD</scope><scope>PNQDJ</scope><scope>POUND</scope><scope>PPLAD</scope><scope>PQAPC</scope><scope>PQCAN</scope><scope>PQCMW</scope><scope>PQEME</scope><scope>PQHKH</scope><scope>PQMID</scope><scope>PQNCT</scope><scope>PQNET</scope><scope>PQSCT</scope><scope>PQSET</scope><scope>PSVJG</scope><scope>PVMQY</scope><scope>PZGFC</scope><scope>7QJ</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><scope>7RZ</scope><scope>PSYQQ</scope></search><sort><creationdate>198701</creationdate><title>Application of Hierarchical Linear Models to Assessing Change</title><author>Bryk, Anthony S ; Raudenbush, Stephen W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a454t-fc441ffe900845a2b78d55b81929231f35805ca919a844a0a307626840a1db813</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1987</creationdate><topic>Biological and medical sciences</topic><topic>Cognitive Development</topic><topic>Development</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Human</topic><topic>Mathematical Modeling</topic><topic>Psychology</topic><topic>Psychology. Psychoanalysis. Psychiatry</topic><topic>Psychology. Psychophysiology</topic><topic>Psychometrics. Statistics. Methodology</topic><topic>Statistical Analysis</topic><topic>Statistical Estimation</topic><topic>Statistics</topic><topic>Statistics. Mathematics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bryk, Anthony S</creatorcontrib><creatorcontrib>Raudenbush, Stephen W</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Periodicals Index Online Segment 03</collection><collection>Periodicals Index Online Segment 04</collection><collection>Periodicals Index Online Segment 29</collection><collection>Periodicals Index Online</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - West</collection><collection>Primary Sources Access (Plan D) - International</collection><collection>Primary Sources Access & Build (Plan A) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Midwest</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Northeast</collection><collection>Primary Sources Access (Plan D) - Southeast</collection><collection>Primary Sources Access (Plan D) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Southeast</collection><collection>Primary Sources Access (Plan D) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - UK / I</collection><collection>Primary Sources Access (Plan D) - Canada</collection><collection>Primary Sources Access (Plan D) - EMEALA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - International</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - International</collection><collection>Primary Sources Access (Plan D) - West</collection><collection>Periodicals Index Online Segments 1-50</collection><collection>Primary Sources Access (Plan D) - APAC</collection><collection>Primary Sources Access (Plan D) - Midwest</collection><collection>Primary Sources Access (Plan D) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Canada</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - EMEALA</collection><collection>Primary Sources Access & Build (Plan A) - APAC</collection><collection>Primary Sources Access & Build (Plan A) - Canada</collection><collection>Primary Sources Access & Build (Plan A) - West</collection><collection>Primary Sources Access & Build (Plan A) - EMEALA</collection><collection>Primary Sources Access (Plan D) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - Midwest</collection><collection>Primary Sources Access & Build (Plan A) - North Central</collection><collection>Primary Sources Access & Build (Plan A) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - Southeast</collection><collection>Primary Sources Access (Plan D) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - APAC</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - MEA</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>PsycArticles</collection><collection>ProQuest One Psychology</collection><jtitle>Psychological bulletin</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bryk, Anthony S</au><au>Raudenbush, Stephen W</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of Hierarchical Linear Models to Assessing Change</atitle><jtitle>Psychological bulletin</jtitle><date>1987-01</date><risdate>1987</risdate><volume>101</volume><issue>1</issue><spage>147</spage><epage>158</epage><pages>147-158</pages><issn>0033-2909</issn><eissn>1939-1455</eissn><coden>PSBUAI</coden><abstract>Recent advances in the statistical theory of hierarchical linear models should enable important breakthroughs in the measurement of psychological change and the study of correlates of change. A two-stage model of change is proposed here. At the first, or within-subject stage, an individual's status on some trait is modeled as a function of an individual growth trajectory plus random error. At the second, or between-subjects stage, the parameters of the individual growth trajectories vary as a function of differences between subjects in background characteristics, instructional experiences, and possibly experimental treatments. This two-stage conceptualization, illustrated with data on Head Start children, allows investigators to model individual change, predict future development, assess the quality of measurement instruments for distinguishing among growth trajectories, and to study systematic variation in growth trajectories as a function of background characteristics and experimental treatments.</abstract><cop>Washington, DC</cop><pub>American Psychological Association</pub><doi>10.1037/0033-2909.101.1.147</doi><tpages>12</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0033-2909 |
ispartof | Psychological bulletin, 1987-01, Vol.101 (1), p.147-158 |
issn | 0033-2909 1939-1455 |
language | eng |
recordid | cdi_proquest_journals_614288501 |
source | Applied Social Sciences Index & Abstracts (ASSIA); International Bibliography of the Social Sciences (IBSS); EBSCOhost APA PsycARTICLES |
subjects | Biological and medical sciences Cognitive Development Development Fundamental and applied biological sciences. Psychology Human Mathematical Modeling Psychology Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Psychometrics. Statistics. Methodology Statistical Analysis Statistical Estimation Statistics Statistics. Mathematics |
title | Application of Hierarchical Linear Models to Assessing Change |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T04%3A06%3A56IST&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=Application%20of%20Hierarchical%20Linear%20Models%20to%20Assessing%20Change&rft.jtitle=Psychological%20bulletin&rft.au=Bryk,%20Anthony%20S&rft.date=1987-01&rft.volume=101&rft.issue=1&rft.spage=147&rft.epage=158&rft.pages=147-158&rft.issn=0033-2909&rft.eissn=1939-1455&rft.coden=PSBUAI&rft_id=info:doi/10.1037/0033-2909.101.1.147&rft_dat=%3Cproquest_cross%3E3802812%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a454t-fc441ffe900845a2b78d55b81929231f35805ca919a844a0a307626840a1db813%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=614288501&rft_id=info:pmid/&rfr_iscdi=true |