Latent Curve Models and Latent Change Score Models Estimated in R

REFERENCES

• Adler , D. 2009 . The ‘vioplot’ package in R, [Computer software manual] Retrieved from http://cran.r-project.org/web/packages/vioplot/index.html
   Google Scholar
• Becker , R. A. and Chambers , J. M. 1984 . S: An interactive environment for data analysis and graphics. Pacific Grove , CA : Wadsworth/Brooks/Cole. .
   Google Scholar
• Bentler , P. M. 1995 . EQS program manual. Encino , CA : Multivariate Software. .
   Google Scholar
• Blozis , S. A. 2007 . On fitting nonlinear latent curve models to multiple variables measured longitudinally . Structural Equation Modeling , 14 : 179 – 201 .
   Web of Science ®Google Scholar
• Boker , S. M. , McArdle , J. J. and Neale , M. 2002 . An algorithm for the hierarchical organization of path diagrams and calculation of components of expected covariance . Structural Equation Modeling , 9 : 174 – 194 .
   Web of Science ®Google Scholar
• Boker , S. M. , Neale , M. , Maes , H. H. , Wilde , M. , Spiegel , M. , Brick , T. Spies , J. 2011 . OpenMx: An open source extended Structural Equation Modeling framework . Psychometrika , 76 : 306 – 317 .
   PubMed Web of Science ®Google Scholar
• Bollen , K. A. and Curran , P. J. 2006 . Latent curve models: A structural equation approach. Hoboken , NJ : Wiley. .
   Google Scholar
• Browne , M. W. 1993 . “ Structured latent curve models. ” . In Multivariate analysis: Future directions 2 Edited by: Cuadras , C. M. and Rao , C. R. 171 – 197 . Amsterdam , , The Netherlands : Elsevier. .
   Google Scholar
• Browne , M. W. 2001 . An overview of analytic rotation in exporatory factor analysis . Multivariate Behavioral Research , 36 : 111 – 150 .
   Web of Science ®Google Scholar
• Browne , M. W. and Nesselroade , J. R. 2005 . “ Representing psychological processes with dynamic factor models: Some promising uses and extensions of autoregressive moving average time series models. ” . In Contemporary advances in psychometrics Edited by: Madeau , A. and McArdle , J. J. 415 – 452 . Mahwah , NJ : Erlbaum. .
   Google Scholar
• Curran , P. J. and Bollen , K. A. 2001 . “ The best of both worlds: Combining autoregressive and latent curve models. ” . In New methods for the analysis of change Edited by: Collins , L. M. and Sayer , A. G. 107 – 135 . Washington , DC : American Psychological Association. .
   Google Scholar
• Davidian , W. and Giltinan , D. M. 1995 . Nonlinear models for repeated measurement data. London , , UK : Chapman & Hall. .
   Google Scholar
• Deepayan , S. 2008 . Lattice: Multivariate data visualization with R. New York , NY : Springer. .
   Google Scholar
• Deepayan , S. 2011 . The “lattice” package in R [Computer software manual] Retrieved from http://cran.r-project.org/web/packages/lattice/index.html
   Google Scholar
• Duncan , T. E. , Duncan , S. C. and Strycker , L. A. 2006 . An introduction to latent variable growth curve modeling, , 2nd ed. New York , NY : Routledge. .
   Google Scholar
• Evermann , J. 2010 . Multiple-group analysis using the sem package in the R system . Structural Equation Modeling , 17 : 677 – 702 .
   Web of Science ®Google Scholar
• Ferrer , E. , Hamagami , F. and McArdle , J. J. 2004 . Modeling latent growth curves with incomplete data using different types of structural equation modeling and multilevel software . Structural Equation Modeling , 11 : 452 – 483 .
   Web of Science ®Google Scholar
• Fox , J. 2006 . Structural equation modeling with the sem package in R . Structural Equation Modeling , 13 : 465 – 486 .
   Web of Science ®Google Scholar
• Fox , J. 2010 . The ‘sem’ package in R [Computer software manual] Retrieved from http://cran.r-project.org/web/packages/sem/index.html
   Google Scholar
• Gerstorf , D. , Lövdén , M. , Röcke , C. , Smith , J. and Lindenberger , U. 2007 . Well-being affects changes in perceptual speed in advanced old age: Longitudinal evidence for a dynamic link . Developmental Psychology , 43 : 705 – 718 .
   PubMed Web of Science ®Google Scholar
• Ghisletta , P. , Bickel , J.-F. and Lövdén , M. 2006 . Does activity engagement protect against cognitive decline in old age? Methodological and analytical considerations . Journal of Gerontology: Psychological Sciences , 61B : P253 – P261 .
   Google Scholar
• Ghisletta , P. , Kennedy , K. M. , Rodrigue , K. M. , Lindenberger , U. and Raz , N. 2010 . Adult age differences and the role of cognitive resources in perceptual-motor skill acquisition: Application of a multilevel negative exponential model . Journal of Gerontology: Psychological Sciences , 65 : 163 – 173 .
   Google Scholar
• Ghisletta , P. and Lindenberger , U. 2004 . Static and dynamic longitudinal structural analyses of cognitive changes in old age . Gerontology , 50 : 12 – 16 .
   PubMed Web of Science ®Google Scholar
• Ghisletta , P. and McArdle , J. J. 2001 . Latent growth curve analyses of the development of height . Structural Equation Modeling , 8 : 531 – 555 .
   Web of Science ®Google Scholar
• Grimm , K. J. and Ram , N. 2009 . Nonlinear growth models in Mplus and SAS . Structural Equation Modeling , 16 : 676 – 701 .
   PubMed Web of Science ®Google Scholar
• Hintze , J. L. and Nelson , R. D. 1998 . Violin plots: A box plot–density trace synergism . The American Statistician , 52 : 181 – 184 .
   Web of Science ®Google Scholar
• Ihaka , R. and Gentleman , R. 1996 . R: A language for data analysis and graphics . Journal of Computational and Graphical Statistics , 5 : 299 – 314 .
   Google Scholar
• Jöreskog , K. G. 1977 . “ Structural equation models in the social sciences: Specification, estimation, and testing. ” . In Applications of statistics Edited by: Krishnaiah , P. R. 265 – 287 . Amsterdam , , The Netherlands : North Holland. .
   Google Scholar
• King , L. A. , King , D. W. , McArdle , J. J. , Saxe , G. N. , Doron-LaMarca , S. and Orazem , R. J. 2006 . Latent difference score approach to longitudinal trauma research . Journal of Traumatic Stress , 19 : 771 – 785 .
   PubMed Web of Science ®Google Scholar
• Laird , N. M. and Ware , J. H. 1982 . Random-effects models for longitudinal data . Biometrics , 38 : 963 – 974 .
   PubMed Web of Science ®Google Scholar
• Lövdén , M. , Ghisletta , P. and Lindenberger , U. 2005 . Social participation attenuates decline in perceptual speed in old and very old age . Psychology and Aging , 20 : 423 – 434 .
   PubMed Web of Science ®Google Scholar
• Lumley , T. , DebRoy , S. , Bates , D. , Murdoch , D. and Bivand , R. 2011 . The ‘foreign’ package in R [Computer software manual] Retrieved from http://cran.r-project.org/web/packages/foreign/index.html
   Google Scholar
• MacCallum , R. C. , Roznowski , M. and Necowitz , L. B. 1992 . Model modifications in covariance structure analysis: The problem of capitalization on chance . Psychological Bulletin , 111 : 490 – 504 .
   PubMed Web of Science ®Google Scholar
• McArdle , J. J. 1980 . Causal modeling applied to psychonomic systems simulation . Behavior Research Methods and Instrumentation , 12 : 193 – 209 .
   Google Scholar
• McArdle , J. J. 1986 . Latent growth within behavior genetic models . Behavior Genetics , 16 : 163 – 200 .
   PubMed Web of Science ®Google Scholar
• McArdle , J. J. 2001 . “ A latent difference score approach to longitudinal dynamic structural analyses. ” . In Structural equation modeling: Present and future Edited by: Cudeck , R. , duToit , S. and Sorbom , D. 342 – 380 . Lincolnwood , IL : Scientific Software International. .
   Google Scholar
• McArdle , J. J. 2009 . Latent variable modeling of differences and changes with longitudinal data . Annual Review of Psychology , 60 : 577 – 605 .
   PubMed Web of Science ®Google Scholar
• McArdle , J. J. and Epstein , D. B. 1987 . Latent growth curves within developmental structural equation models . Child Development , 58 : 110 – 133 .
   PubMed Web of Science ®Google Scholar
• McArdle , J. J. , Ferrer-Caja , E. , Hamagami , F. and Woodcock , R. W. 2002 . Comparative longitudinal structural analyses of the growth and decline of multiple intellectual abilities over the life span . Developmental Psychology , 38 : 115 – 142 .
   PubMed Web of Science ®Google Scholar
• McArdle , J. J. , Grimm , K. J. , Hamagami , F. , Bowles , R. P. and Meredith , W. 2009 . Modeling life-span growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement . Psychological Methods , 14 : 126 – 149 .
   PubMed Web of Science ®Google Scholar
• McArdle , J. J. and Hamagami , F. 1996 . “ Multilevel models from a multiple group structural equation perspective. ” . In Advanced structural equation modeling: Issues and techniques Edited by: Marcoulides , G. A. and Schumaker , R. E. 89 – 124 . Mahwah , NJ : Erlbaum. .
   Google Scholar
• McArdle , J. J. and Hamagami , F. 2001 . “ Latent difference score structural models for linear dynamic analyses with incomplete longitudinal data. ” . In New methods for the analysis of change Edited by: Collins , L. M. and Sayer , M. 139 – 175 . Washington , DC : American Psychological Association. .
   Google Scholar
• McArdle , J. J. , Hamagami , F. , Meredith , W. and Bradway , K. P. 2000 . Modeling the dynamic hypotheses of gf-gc theory using longitudinal life-span data . Learning and Individual Differences , 12 : 53 – 79 .
   Web of Science ®Google Scholar
• McArdle , J. J. and McDonald , R. P. 1984 . Some algebraic properties of the reticular action model for moment structures . British Journal of Mathematical and Statistical Psychology , 27 : 234 – 251 .
   Google Scholar
• McArdle , J. J. and Nesselroade , J. R. 1994 . “ Using multivariate data to structure developmental change. ” . In Life-span developmental psychology: Methodological contributions Edited by: Cohen , S. H. and Reese , H. W. 223 – 267 . Hillsdale , NJ : Erlbaum. .
   Google Scholar
• Meredith , W. and Tisak , J. 1990 . Latent curve analysis . Psychometrika , 55 : 107 – 122 .
   Web of Science ®Google Scholar
• Muthén , L. K. and Muthén , B. O. 1998–2010 . Mplus user's guide, , 6th ed. Los Angeles , CA : Muthén & Muthén. .
   Google Scholar
• Neale , M. C. , Boker , S. M. , Xie , G. and Maes , H. H. 2006 . Mx: Statistical modeling, , 7th ed. Richmond , VA : Department of Psychiatry, Virginia Commonwealth University. .
   Google Scholar
• Nesselroade , J. R. , McArdle , J. J. , Aggen , S. H. and Meyers , J. M. 2002 . “ Alternative dynamic factor models for multivariate time-series analyses. ” . In Modeling intraindividual variability with repeated measures data: Advances and techniques Edited by: Moskowitz , D. S. and Hershberger , S. L. 235 – 265 . Mahwah , NJ : Erlbaum. .
   Google Scholar
• OpenMx Development Team. 2010 . OpenMx documentation. Retrieved from http://openmx.psyc.virginia.edu/documentation
   Google Scholar
• Osborne , R. T. and Lindsey , J. M. 1967 . A longitudinal investigation of change in the factorial composition of intelligence with age in young school children . The Journal of Genetic Psychology , 110 : 49 – 58 .
   PubMed Web of Science ®Google Scholar
• Osborne , R. T. and Suddick , D. E. 1972 . A longitudinal investigation of the intellectual differentiation hypothesis . The Journal of Genetic Psychology , 121 : 83 – 89 .
   Web of Science ®Google Scholar
• Preacher , K. J. , Wichman , A. L. , MacCallum , R. C. and Briggs , N. E. 2008 . Latent growth curve modeling. Los Angeles , CA : Sage. .
   Google Scholar
• R Development Core Team. 2010 . R: A language and environment for statistical computing. Vienna , , Austria : Author. .
   Google Scholar
• Raz , N. , Lindenberger , U. , Ghisletta , P. , Rodrigue , K. M. , Kennedy , K. M. and Acker , J. D. 2008 . Neuroanatomical correlates of fluid intelligence in healthy adults and persons with vascular risk factors . Cerebral Cortex , 18 : 718 – 726 .
   Web of Science ®Google Scholar
• Revelle , W. 2010 . Psych: Procedures for psychological, psychometric, and personality research. Evanston , IL Retrieved from http://personality-project.org/r/psych.manual.pdf
   Google Scholar
• Rosseel , Y. 2011 . The ‘lavaan’ package in R. Retrieved from http://cran.r-project.org/web/packages/lavaan/index.html
   Google Scholar
• Rovine , M. J. and Molenaar , P. C. M. 2000 . A structural modeling approach to a multilevel random coefficients model . Multivariate Behavioral Research , 35 : 51 – 88 .
   PubMed Web of Science ®Google Scholar
• TIBCO Software Inc. 2010 . TIBCO Spotfire S⁺ 8.2 user's guide. Somerville , MA : Author. .
   Google Scholar
• Wechsler , D. 1949 . Manual of the Wechsler Intelligence Scale for Children. New York , NY : Psychological Corporation. .
   Google Scholar
• Wright , S. 1920 . The relative importance of heredity and environment in determining the piebald pattern of guinea-pigs . Proceedings of the National Academy of Sciences , 6 : 320 – 332 .
   PubMedGoogle Scholar