The current practice of latent growth curve modeling in the social and behavioral sciences: Observations and recommendations

Abstract

We examine recommendations for three key features of latent growth curve models in the structural equation modeling framework. As a basis for the discussion, we review current practice in the social and behavioral sciences literature as found in 441 reports published in the 19 months beginning in January 2019 and compare our findings to extant recommendations. We then provide suggestions for empirical researchers, reviewing the application of these very popular models, specifically focusing on comparison of alternative change models, time metric and interval features implemented, and the treatment of individually varying time intervals.

Keywords

Latent curve models longitudinal guidelines review

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References

Appelbaum

Cooper

Kline

R. B.

Mayo-Wilson

Nezu

A. M.

Rao

S. M.

(2018). Journal article reporting standards for quantitative research in psychology: The APA Publications and Communications Board task force report. American Psychologist, 73(1), 3–25. https://doi.org/10.1037/amp0000191

Aydin

Leite

W. L.

Algina

(2014). The consequences of ignoring variability in measurement occasions within data collection waves in latent growth models. Multivariate Behavioral Research, 49, 149–160. https://doi.org/10.1080/00273171.2014.887901

Baltes

P. B.

Nesselroade

J. R.

(1979). History and rationale of longitudinal research. In Nesselroade

J. R.

Baltes

P. B.

(Eds.), Longitudinal research in the study of behavior and development (pp. 1–39). Academic Press.

Bauer

D. J.

(2007). Observations on the use of growth mixture models in psychological research. Multivariate Behavioral Research, 42, 757–786. https://doi.org/10.1080/00273170701710338

Biesanz

J. C.

Deeb-Sossa

Papadakis

A. A.

Bollen

K. A.

Curran

P. J.

(2004). The role of coding time in estimating and interpreting growth curve models. Psychological Methods, 9, 30–52. https://doi.org/10.1037/1082-989X.9.1.30

Bollen

K. A.

Curran

P. J.

(2006). Latent curve models: A structural equation perspective. Wiley.

Boomsma

Hoyle

R. H.

Panter

A. T.

(2012). The structural equation modeling research report. In Hoyle

R. H.

(Ed.), Handbook of structural equation modeling (pp. 341–358). Guilford Press.

Browne

M. W.

(1993). Structured latent curve models. In Cuadras

C. M.

Rao

C. R.

(Eds.), Multivariate analysis: Future directions 2 (pp. 171–197). Elsevier.

Burnham

K. P.

Anderson

D. R.

(2002). Model selection and multi-model inference: A practical information-theoretic approach (2nd ed.). Springer.

10.

Collins

L. M.

(2006). Analysis of longitudinal data: The integration of theoretical model, temporal design, and statistical model. Annual Review of Psychology, 57, 505–528. https://doi.org/10.1146/annurev.psych.57.102904.190146

11.

Collins

L. M.

Graham

J. W.

(2002). The effect of the timing and spacing of observations in longitudinal studies of tobacco and other drug use: Temporal design considerations. Drug and Alcohol Dependence, 68(s1), 85–96. https://doi.org/10.1016/S0376-8716(02)00217-X

12.

Coulombe

Selig

J. P.

Delaney

H. D.

(2016). Ignoring individual differences in times of assessment in growth curve modeling. International Journal of Behavioral Development, 40, 78–86. https://doi.org/10.1177/0165025415577684

13.

Cudeck

Harring

J. R.

(2007). Analysis of nonlinear patterns of change with random coefficient models. Annual Review of Psychology, 58, 615–637. https://doi.org/10.1146/annurev.psych.58.110405.085520

14.

Cudeck

Klebe

K. J.

(2002). Multiphase mixed effects models for repeated measures data. Psychological Methods, 7, 41–63. https://doi.org/10.1037/1082-989X.7.1.41

15.

Curran

P. J.

(2003). Have multilevel models been structural equation models all along? Multivariate Behavioral Research, 38, 529–569. https://doi.org/10.1207/s15327906mbr3804_5

16.

Estrada

Ferrer

(2019). Studying developmental processes in accelerated cohort-sequential designs with discrete- and continuous-time latent change score models. Psychological Methods, 24, 708–734. https://doi.org/10.1037/met0000215

17.

Ghisletta

Mason

von Oertzen

Hertzog

Nilsson

Lindenberger

(2020). On the use of growth models to study normal cognitive aging. International Journal of Behavioral Development, 44, 88–96. https://doi.org/10.1177/0165025419851576

18.

Grimm

K. J.

Ram

Estabrook

(2017). Growth modeling: Structural equation and multilevel modeling approaches. Guilford Press.

19.

Hancock

G. R.

Stapleton

L. M.

Mueller

R. O.

(Eds.). (2019). The reviewer’s guide to quantitative methods in the social sciences (2nd ed.). Routledge.

20.

Harring

J. R.

Strazzeri

M. M.

Blozis

S. A.

(2020). Piecewise latent growth models: Beyond modeling linear-linear processes. Behavior Research Methods, 53, 593–608. https://doi.org/10.3758/s13428-020-01420-5

21.

Hershberger

S. L.

(2003). The growth of structural equation modeling: 1994-2001. Structural Equation Modeling: An Interdisciplinary Journal, 10(1), 35–46. https://doi.org/10.1207/S15328007SEM1001_2

22.

Hesser

(2015). Modeling individual differences in randomized experiments using growth models: Recommendations for design, statistical analysis and reporting of results of internet interventions. Internet Interventions, 2, 110–120. https://doi.org/10.1016/j.invent.2015.02.003

23.

Hopwood

C. J.

Bleidorn

Wright

A. G.

(2022). Connecting theory to methods in longitudinal research. Perspectives on Psychological Science, 17, 884–894. https://doi.org/10.1177/17456916211008407

24.

Hoyle

R. H.

(1995). Structural equation modeling: Concepts, issues, and applications. SAGE.

25.

Hoyle

R. H.

Isherwood

J. C.

(2013). Reporting results from structural equation modeling analyses in Archives of Scientific Psychology. Archives of Scientific Psychology, 1, 14–22. https://doi.org/10.1037/arc0000004

26.

Jackson

D. L.

(2010). Reporting results of latent growth modeling and multilevel modeling analyses: Some recommendations for rehabilitation psychology. Rehabilitation Psychology, 55(3), 272–285. https://doi.org/10.1037/a0020462

27.

Kline

R. B.

(2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press.

28.

Laird

N. M.

Ware

A. H.

(1982). Random-effects models for longitudinal models. Biometrics, 38, 963–974. https://doi.org/10.2307/2529876

29.

Lampl

(1993). Evidence of saltatory growth in infancy. American Journal of Human Biology, 5(6), 641–652. https://doi.org/10.1002/ajhb.1310050607

30.

Little

T. D.

(2024). Longitudinal structural equation modeling (2nd ed.). Guilford Press.

31.

McArdle

J. J.

(1986). Latent variable growth within behavior genetic models. Behavior Genetics, 16, 163–200. https://doi.org/10.1007/BF01065485

32.

McArdle

J. J.

(1988). Dynamic but structural equation modeling of repeated measures data. In Nesselroade

J. B.

Cattell

R. B.

(Eds.), Handbook of multivariate experimental psychology (pp. 561–614). Plenum Press.

33.

McArdle

J. J.

Hamagami

(1996). Multilevel models from a multiple group structural equation perspective. In Marcoulides

G. A.

Schumacker

R. E.

(Eds.), Advanced structural equation modeling (pp. 89–124). Psychology Press.

34.

McArdle

J. J.

Nesselroade

J. R.

(2014). Longitudinal data analysis using structural equation models. American Psychological Association.

35.

McNeish

Matta

T. H.

(2020). Flexible treatment of time-varying covariates with time unstructured data. Structural Equation Modeling: A Multidisciplinary Journal, 27, 298–317. https://doi.org/10.1080/10705511.2019.1627213

36.

Mehta

P. D.

Neale

M. C.

(2005). People are variables too: Multilevel structural equations modeling. Psychological Methods, 10, 259–284. https://doi.org/10.1037/1082-989X.10.3.259

37.

Mehta

P. D.

West

S. G.

(2000). Putting the individual back into individual growth curves. Psychological Methods, 5, 23–43.

38.

Miller

M. L.

Ferrer

(2017). The effect of sampling-time variation on latent growth curve models. Structural Equation Modeling: A Multidisciplinary Journal, 24, 831–854.

39.

Mueller

R. O.

Hancock

G. R.

(2019). Structural equation modeling. In Hancock

G. R.

Stapleton

L. M.

Mueller

R. O.

(Eds.), The reviewer’s guide to quantitative methods in the social sciences (2nd ed., pp. 445–456). Routledge.

40.

Muthén

L. K.

Muthén

B. O.

(2017). Mplus user’s guide (8th ed.).

41.

Neale

M. C.

(1998). Modeling interaction and nonlinear effects with Mx: A general approach. In Marcoulides

Schumacker

(Eds.), Interaction and non-linear effects in structural equation modeling (pp. 43–61). Erlbaum.

42.

Newsom

J. T.

(2015). Longitudinal structural equation modeling: A comprehensive introduction. Routledge.

43.

Preacher

K. J.

(2019). Latent growth curve models. In Hancock

G. R.

Stapleton

L. M.

Mueller

R. O.

(Eds.), The reviewer’s guide to quantitative methods in the social sciences (2nd ed., pp. 178–192). Routledge.

44.

Ram

Grimm

K. J.

(2007). Using simple and complex growth models to articulate developmental change: Matching method to theory. International Journal of Behavioral Development, 31, 303–316. https://doi.org/10.1177/0165025407077751

45.

Rovine

M. J.

Molenaar

P. C.

(1998). The covariance between level and shape in the latent growth curve model with estimated basis vector coefficients. Methods of Psychological Research Online, 3(2), 95–107. https://www.dgps.de/fachgruppen/methoden/mpr-online/issue5/art7/article.html

46.

Singer

J. D.

Willett

J. B.

(2003). Applied longitudinal data analysis. Oxford University Press.

47.

Sterba

S. K.

(2014). Fitting nonlinear latent growth curve models with individually varying time points. Structural Equation Modeling: A Multidisciplinary Journal, 21, 630–647. https://doi.org/10.1080/10705511.2014.919828

48.

Thompson

(2000). Ten commandments of structural equation modeling. In Grimm

L. G.

Yarnold

P. R.

(Eds.), Reading and understanding more multivariate statistics (pp. 261–283). American Psychological Association.

49.

Timmons

A. C.

Preacher

K. J.

(2015). The importance of temporal design: How do measurement intervals affect the accuracy and efficiency of parameter estimates in longitudinal research? Multivariate Behavioral Research, 50(1), 41–55. https://doi.org/10.1080/00273171.2014.961056

50.

van de Schoot

Sijbrandij

Winter

S. D.

Depaoli

Vermunt

J. K.

(2017). The GRoLTS-Checklist: Guidelines for reporting on latent trajectory studies. Structural Equation Modeling: A Multidisciplinary Journal, 24(3), 451–467. https://doi.org/10.1080/10705511.2016.1247646

51.

Voelkle

M. C.

Gische

Driver

C. C.

Lindenberger

(2018). The role of time in the quest for understanding psychological mechanisms. Multivariate Behavioral Research, 53, 782–805.

52.

Wagenmakers

E.-J.

Farrell

(2004). AIC model selection using Akaike weights. Psychonomic Bulletin & Review, 11, 192–196. https://doi.org/10.3758/BF03206482

53.

Widaman

K. F.

Thompson

J. S.

(2003). On specifying the null model for incremental fit indices in structural equation modeling. Psychological Methods, 8(1), 16–37. https://doi.org/10.1037/1082-989X.8.1.16

54.

Wilkinson

, Task Force on Statistical Inference, American Psychological Association, & Science Directorate. (1999). Statistical methods in psychological journals: Guidelines and explanations. American Psychologist, 54(8), 594–604. https://doi.org/10.1037/0003-066X.54.8.594

55.

West

S. G.

Taylor

A. B.

(2009). Evaluating model fit for growth curve models: Integration of fit indices from SEM and MLM frameworks. Psychological Methods, 14(3), 183–201. https://doi.org/10.1037/a0015858

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