CHANGE CHANGE CHANGE
ADOLESCENCE IS A TIME OF CHANGE
(but how can we measure this?)
Contents and resources for the H2020 Marie Skłodowska-Curie innovative training network Workshop on Missing Data & Longitudinal Methods, and with much pleasure offered to the participants of this workshop (or anyone else that's interested) by Wim Beyers (© 2017 & 2020).
+ Contents and resources for the FLAMES2015 Mplus Workshop: Theory into Practice, Day 1 'Path and Growth Models', organized by FLAMES in cooperation with SOKA, KULeuven, and with much pleasure offered to the participants of this workshop (or anyone else that's interested) by Wim Beyers (© 2015).
+ Contents and resources for the EARA2009 Methodology Workshop, part 'Longitudinal Analyses', organized by EARA, and with much pleasure offered to the participants of this workshop (or anyone else that's interested) by Wim Beyers (© 2009).
Workshop H2020 Marie Sklodowska-Curie Missings & Longitudinal Methods 10112017.pdf Also a more recent version with voice over on Youtube!
Data (best is to place and/or copy the datafiles to the directory were you also put the syntaxes for the analyses; 'save target/link as')
FOR FLAMES Mplus WORKSHOP 2015 & Marie Curie WORKSHOP 2017 & 2020
All data-files below in one zip-folder mplusdata.zip (extract in a folder, e.g. called Mplus)!
SEMDATA.XLS (a copy in Excel)
SEMDATA.DAT (a copy in tab delimited format, for use in Mplus)
PARCELS ANTI.SAV (raw data in SPSS used in autoregression-latent and LCM example)
PARCELS ANTI.XLS (a copy in Excel)
PARCELS ANTI.DAT (a copy in tab delimited format, for use in Mplus)
ANTISOCIAL.CSV (data used for Extension 1 of LGCM: measurement invariance)
LTA_PARENTINGZ.SAV (raw data in SPSS used in LTA example)
LTA_PARENTINGZ.XLS (a copy in Excel)
LTAPARENTINGZ.DAT (a copy in tab delimited format, for use in Mplus)
EX6.11.DAT (used in LGCM - piecewise)
FOR EARA WORKSHOP 2009
EARADATA.SAV (raw data in SPSS)
EARADATA.XLS (a copy in Excel)
EARADATA.TXT (a copy in fixed ASCI (without labels), in raw text format)
EARADATA.DAT (same, but now with a .dat suffix, for use in for instance Lisrel (FIML) or in Mplus)
EARADATA MVA EM.SAV (data in SPSS with missings estimated and imputed using the EM algorithm)
EARADATAMIEM.DAT (same, but now with a .dat suffix, for use in Mplus)
ANTI.SAV and ANTI.DAT (data on antisocial behavior only, for use in Mplus demo version)
GPA.SAV and GPA.DAT (data on gpa only, for use in Mplus demo version)
AR CONTRA EXAMPLE.SAV (data showing that autoregressive modeling of change sometimes leads to wrong conclusions)
MVA.spo.pdf, R ANOVA.spo.pdf, MACS1.spo.pdf (SPSS outputs converted to pdf's; all described on the slides)
PARCELSANTI.cm, PARCELSANTI.ac, PARCELSANTI.me (covariances, asymptotics and means of parcels of antisocial behavior, for use in Lisrel)
earadata.cm, earadata.ac, earadata.me (covariances, asymptotic covariances and means, for use in Lisrel)
Analysis examples (downloadable syntaxes, to open in Lisrel (*.spl) or Mplus (*.inp); all described on the slides; 'save target/link as' in folders called 'Lisrel' and 'Mplus')
FOR FLAMES Mplus WORKSHOP 2015 & Marie Curie WORKSHOP 2017 & 2020
All syntax (*.inp) files in one zip-folder mplussyntax.zip (extract in same folder as data, e.g. called Mplus)!
difference score.inp (calculation anti4-anti 1 + support as a predictor)
R ANOVA.SPV (pdf with SPSS output of repeated measures ANOVA of antisocial behavior)
autoregression.inp (autoregression of anti4 ON anti1 + support as a predictor of 'change')
autoregression latent.inp (same, but with latent variables)
autoregressionb.inp (path model with antisocial behavior, gpa, support and structure, including mediation)
autoregression-multigroup.inp (gender as a moderator of stability in antisocial behavior - free estimation)
autoregression-multigroupb.inp (gender as a moderator of stability in antisocial behavior - fixed estimation)
cross-lagged.inp (crosslagged model of antisocial behavior and gpa T1-T4)
lcm anti.inp (Latent Change Model - antisocial behavior)
lgcm anti.inp (Latent Growth Curve Model - antisocial behavior)
lgcm_anti + predictors.inp (same, now with gender and support as predictors)
lgcm_anti + predictors + interaction.inp (same, but now with support X level interaction prediction change in antisocial behavior)
lgcm anti - piecewise.inp (piecewise growth model of antisocial behavior, with 2 slopes)
lgcm anti + gpa.inp (multivariate Latent Growth Curve Model)
antisocial baseline.inp (baseline model measurement invariance)
antisocial FL invariance.inp (factor loadings invariant)
antisocial FL+I invariance.inp (factor loadings + intercepts invariant)
antisocial FL+I invariance partial.inp (partial measurement invariance)
antisocial baselineWLSMV.inp (baseline model measurement invariance - categorical data)
antisocial FL invariance WLSMV.inp (factor loadings invariant - categorical data)
antisocial FL invariance WLSMV 2.inp (savedata: DIFFTEST IS deriv.dat)
antisocial FL+Treshold invariance WLSMV.inp (factor loadings + intercepts/tresholds invariant - categorical data)
cohort-sequential growth model anti.inp (linear Latent Growth Curve Model anti, cohort-sequential design - multigroup)
cohort-sequential growth model antib.inp (curvilinear Latent Growth Curve Model anti, cohort-sequential design - multigroup)
cohort-sequential growth model anti 2.inp (linear Latent Growth Curve Model anti, cohort-sequential design - data cohort)
cohort-sequential growth model antib 2b.inp (curvilinear Latent Growth Curve Model anti, cohort-sequential design - data cohort)
cohort-sequential growth model anti 2 piecewise.inp (linear piecewise Latent Growth Curve Model anti, cohort-sequential design - data cohort)
lcga_anti2.inp (Latent Class Growth Analysis - Nagin approach, antisocial behavior, two classes)
lgmm_anti2.inp (Latent Growth Mixture Model, antisocial behavior, two classes with equal variances across classes)
lgmm_anti2free.inp (Latent Growth Mixture Model, antisocial behavior, two classes with free variances across classes)
lcga_anti5c.inp (curvilinear Latent Class Growth Analysis anti - 5 classes, best solution)
lta_parenting4.inp (Latent Transition Analysis of parenting styles - 4 classes)
lta_parenting5.inp (Latent Transition Analysis of parenting styles - 5 classes, best solution)
FOR EARA WORKSHOP 2009
All Lisrel syntaxes ànd datafiles in one zip-folder lisrel.zip (extract in a folder called Lisrel)!
macs1.spl (comparison of means ànd covariances for longitudinals and dropouts at Wave 1)
ar_anti.spl (autoregressive model of change, with observed variables)
arsem_anti.spl (autoregressive model of change, with latent variables)
crosslagged.spl (crosslagged model, with observed variables)
lcm_anti.spl (Latent Change Model of antisocial behavior)
lgc_anti.spl (Latent Growth Curve model of antisocial behavior, with 'complete' estimated data)
lgc_anti-FIML.spl (Latent Growth Curve model of antisocial behavior, with missing data and the FIML approach)
lgc_anti+cov.spl (Latent Growth Curve model of antisocial behavior, with gender and support as predictors of change)
lgc_anti.inp (Latent Growth Curve model of antisocial behavior, with gender and support as predictors of change - in Mplus)
lgc_antiread.spl (Multivariate Latent Growth Curve model)
lgc_antiread+FIML.spl (Multivariate Latent Growth Curve model, with missing data and the FIML approach)
All Mplus syntaxes ànd datafiles in one zip-folder mplus.zip (extract in a folder called Mplus)!
lcga_anti2.inp (Latent Class Growth Analysis - Nagin approach, antisocial behavior, two classes)
lcga_anti3.inp (Latent Class Growth Analysis - Nagin approach, antisocial behavior, three classes)
lgmm_anti2.inp (Latent Growth Mixture Model, antisocial behavior, two classes with equal variances across classes)
lgmm_anti3.inp (Latent Growth Mixture Model, antisocial behavior, three classes with equal variances across classes)
lgmm_anti3b.inp (Latent Growth Mixture Model, antisocial behavior, three classes with equal intercept variances across classes and slope variances fixed to zero; best solution)
lgmm_anti2free.inp (Latent Growth Mixture Model, antisocial behavior, two classes with free variances across classes)
lgmm_anti3free.inp (Latent Growth Mixture Model, antisocial behavior, three classes with free variances across classes)
Key Literature (articles are available as pdf's, on request)
Defining time and choosing intervals
Rueter, M. A., & Conger, R. D. (1998). Reciprocal influences between parenting and adolescent problem-solving behavior. Developmental Psychology, 34, 1470-1482.
Missing data and how to handle them
Little, T. D., Lindenberger, U., & Maier, H. (2000). Selectivity and generalizability in longitudinal research: On the effects of continuers and dropouts. In T. D. Little, K. U. Schnabel, & J. Baumert (Eds.), Modeling longitudinal and multilevel data: Practical issues, applied approaches, and specific examples (pp. 187-200). Mahwah, NJ: Erlbaum.
Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147-177.
Wothke, W. (2000). Longitudinal and multigroup modeling with missing data. In T. D. Little, K. U. Schnabel, & J. Baumert (Eds.), Modeling longitudinal and multilevel data: Practical issues, applied approaches, and specific examples (pp. 219-240). Mahwah, NJ: Erlbaum.
Latent Change Model (LCM)
McArdle, J. J., & Nesselroade, J. R. (1994). Structuring data to study development and change. In S. H. Cohen & H. W. Reese (Eds.), Life-span developmental psychology: Methodological innovations (pp. 223-268). Hillsdale, NJ: Erlbaum.
Hertzog, C., & Nesselroade, J. R. (2003). Assessing psychological change in adulthood: An overview of methodological issues. Psychology and Aging, 18, 639-657.
Latent Growth Curve modeling (LGCM)
Willett, J. B., & Sayer, A. G. (1994). Using covariance structure analysis to detect correlates and predictors of individual change over time. Psychological Bulletin, 116, 363-381.
Duncan, T. E., Duncan, S. C., Strycker, L. A., Li, F., & Alpert, A. (1999). An introduction to latent variable growth curve modeling: Concepts, issues, and applications (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.
Duncan, T. E., Duncan, S. C., & Stoolmiller, M. (1994). Modeling developmental processes using latent growth structural equation methodology. Applied Psychological Measurement, 18, 343-354.
McArdle, J. J., & Nesselroade, J. R. (2002). Growth curve analysis in contemporary psychological research. In J. Schinka & W. Velicer (Eds.), Comprehensive handbook of psychology (Vol. 2): Research methods in psychology (pp. 447-480). New York: Wiley.
Latent Class Growth Analysis (LCGA)
Nagin, D. S. (1999). Analyzing developmental trajectories: A semiparametric group-based approach. Psychological Methods, 4, 139-157.
Nagin, D. S. (2001). Analyzing developmental trajectories of distinct but related behaviors: A group-based method. Psychological Methods, 6, 18-34.
Latent Growth Mixture Modeling (LGMM)
Muthen, B., & Muthen, L. K. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and Experimental Research, 24, 882-891.
Muthén, B. (2001). Second-generation structural equation modeling with a combination of categorical and continuous latent variables. In L. M. Collins & A. G. Sayer (Eds.), New methods for the analysis of change (pp. 291-322). Washington, DC: American Psychological Association.
Muthén, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345-368). Newbury Park, CA: Sage.
Longitudinal measurement invariance
Bishop, J., Geiser, C., & Cole, D. A. (2014). Modeling latent growth with multiple indicators: A comparison of three approaches. Psychological Methods. doi: 10.1037/met0000018
Coertjens, L., van Daal, T., Donche, V., De Maeyer, S., Vanthournout, G., & Van Petegem, P. (2013). Analysing change in learning strategies over time: A comparison of three statistical techniques. Studies in Educational Evaluation, 39, 49-55.
Coertjens, L., Donche,V., De Maeyer, S., Vanthournout, G., & Van Petegem ,P. (2013). Modeling change in learning strategies throughout higher education: A multi-indicator latent growth perspective. PLoS ONE, 8: e67854. doi:10.1371/journal.pone.0067854
Coertjens, L., Donche, V., De Maeyer, S., Vanthournout, G., & Van Petegem, P. (2012). Longitudinal measurement invariance of learning strategy scales: Are we using the same ruler at each wave? Journal of Psychoeducational Assessment, 30, 577-587. doi: 10.1177/0734282912438844
Wu, A., Liu, Y., Gadermann, A. M., & Zumbo, B. D. (2010). Multiple-indicator multilevel growth model: A solution to multiple methodological challenges in longitudinal studies. Social Indicators Research, 97, 123-142. doi: 10.1007/s11205-009-9496-8
Metha, P. D., Neale, M. C., & Flay, B. R. (2004). Squeezing interval change from ordinal panel data: Latent growth curves with ordinal outcomes. Psychological Methods, 9, 301-333. doi: 10.1037/1082-989X.9.3.301
Duncan, T. E., Duncan, S. C., Strycker, L. A., Li, F., & Alpert, A. (1999). An introduction to latent variable growth curve modeling: Concepts, issues, and applications (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.
Latent Transition Analysis (LTA)
Collins, L. M., & Lanza, S. T. (2009). Latent class and latent transition analysis: With applications in the social, behavioral and health sciences. Hoboken, NJ: John Wiley & Sons.
Graham, J. W., Collins, L. M., Wugalter, S. E., Chung, N. K., & Hansen, W. B. (1991). Modeling transitions in latent stage-sequential processes: A substance use prevention example. Journal of Consulting and Clinical Psychology, 59, 48-57.
Kaplan, D. (2008). An overview of Markov chain methods for the study of stage-sequential developmental processes. Developmental Psychology, 44, 457–467.
Meeus, W., van de Schoot, R., Keijsers, L., Schwartz, S., & Branje, S. (2010). On the progression and stability of adolescent identity formation: A five-wave longitudinal study in early-to-middle and middle-to-late adolescence. Child Development, 81, 1565-1581.
Velicer, W. F.,
Martin, R. A., & Collins, L. M. (1996). Latent transition analysis for
longitudinal data. Addiction, 91, 197-210.