Skip to main content
SpringerLink
Log in

Estimating Relative Stability in Developmental Research: A Critique of Modern Approaches and a Novel Method

  • Original Paper
  • Published:
Journal of Quantitative Criminology Aims and scope Submit manuscript

Abstract

Objective

Developmental/life-course (DLC) criminologists often study the age-graded trajectories of traits and behaviors known to correlate with antisocial outcomes. Much of this work has attempted to discern whether traits like impulse control are relatively stable across different portions of the life course. A range of statistical techniques have been employed by researchers attempting to parameterize relative stability. Yet, despite these attempts, much of the evidence remains mixed.

Methods

We draw on data from the Pathways to Desistance study to examine whether the methods typically used to analyze longitudinal development provide a parameter estimate for relative stability.

Results

The results of our demonstration reveal that none of the methods typically employed by DLC researchers provide a parameter estimate for relative stability. In order to address this oversight, we develop a novel method—P(Δ)—that can be used to estimate the amount of relative (in)stability that is observed in a longitudinal dataset.

Conclusions

Although P(Δ) provides a direct estimate of the degree to which relative (in)stability is observed in one’s dataset, there are several important points that must be considered by future DLC researchers in order to further develop P(Δ) into a statistic that can be used for inferential analysis. We consider these points in the discussion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Notes

  1. We owe a special thanks to Carol Schubert who provided the alpha values upon request.

  2. Substantive findings for the MMC were unchanged when age dummies were included and when control variables for race and sex were included in the analysis. Also, substantive findings were unchanged when the alternative coding for the wave variable (i.e., the timing between waves in months) was utilized; these estimates suggested respondents increased in impulse control by approximately 0.048 points every 12 months. Considering the Pathways study spanned a 7-year period, this effect translates into roughly 0.339 points gained, on average, over the course of the project.

  3. A series of alternative models were estimated where the error covariance matrix was specified with different structures (e.g., unstructured, an autoregressive structure, and the Toeplitz structure). Parameter estimates were substantively unchanged when these models were estimated.

  4. It is worth noting that one can perform an approximate analysis of Jeffreys’s Bayes factor scale—a useful method for identifying the best-fitting model via the BIC statistic—by exponentiating the difference between the BIC values for two models (see Nagin 2005: 69). We would like to thank an anonymous reviewer for pointing this out.

  5. This number was calculated with the binomial coefficient (i.e., the formula for combinations) because ordering does not matter (i.e., we do not want to count AB as unique from BA):

    \(\frac{n!}{r!(n - r)!} = \frac{854!}{2!(854 - 2)!} = \frac{(854*853)}{2} = 364,231\)

  6. A secondary consideration is whether the trials (i.e., two randomly drawn cases) should be weighted to account for the starting position of case 1 relative to case 2. In other words, should P(Δ) give more weight to cases that reliably change rankings when they started further apart at baseline?

References

  • Agresti A, Franklin C (2013) Statistics: the art and science of learning from data, 3rd edn. Pearson, New York

    Google Scholar 

  • Allison P (2002) Missing data. Sage, Thousand Oaks

    Book  Google Scholar 

  • Andrews DA, Bonta J (2010) The psychology of criminal conduct, 5th edn. Matthew Bender & Company, New Providence

    Google Scholar 

  • Arneklev BJ, Cochran JK, Gainey RR (1998) Testing Gottfredson and Hirschi’s “low self-control” stability hypothesis: an exploratory study. Am J Crim Justice 23:107–127

    Article  Google Scholar 

  • Berk R (2010) An introduction to statistical learning from a regression perspective. In: Piquero A, Weisburd D (eds) Handbook of quantitative criminology. Springer, New York, pp 725–740

    Chapter  Google Scholar 

  • Burt CH, Simons RL (2013) Self-control, thrill seeking, and crime motivation matters. Crim Justice Behav 40:1326–1348

    Article  Google Scholar 

  • Burt CH, Simons RL, Simons LG (2006) A longitudinal test of the effects of parenting and the stability of self-control: negative evidence for the general theory of crime. Criminology 44:353–396

    Article  Google Scholar 

  • Burt CH, Sweeten G, Simons RL (2014) Self-control through emerging adulthood: instability, multidimensionality, and criminological significance. Criminology 52:450–487

    Article  Google Scholar 

  • Bushway SD, Piquero AR, Broidy LM, Cauffman E, Mazerolle P (2001) An empirical framework for studying desistance as a process. Criminology 39:491–516

    Article  Google Scholar 

  • Chassin L, Dmitrieva J, Modecki K, Steinberg L, Cauffman E, Piquero AP, Knight GP, Losoya SH (2010) Does adolescent alcohol and marijuana use predict suppressed growth in psychosocial maturity among male juvenile offenders? Psychol Addict Behav 24:48–60

    Article  Google Scholar 

  • Christensen L, Mendoza JL (1986) A method of assessing change in a single subject: an alteration of the RC Index. Behav Ther 17:305–308

    Article  Google Scholar 

  • Coyne MA, Vaske JC, Boisvert DL, Wright JP (2015) Sex differences in the stability of self-regulation across childhood. J Dev Life Course Criminol 1:4–20

    Article  Google Scholar 

  • Cullen FT (2011) Beyond adolescence-limited criminology: choosing our future—The American Society of Criminology 2010 Sutherland Address. Criminology 49:287–330

    Article  Google Scholar 

  • Curran PJ, Bauer DJ (2011) The disaggregation of within-person and between-person effects in longitudinal models of change. Annu Rev Psychol 62:583–619

    Article  Google Scholar 

  • Diamond B, Morris R G, and Piquero A R (2015). Stability in the underlying constructs of self-control. Crime Delinq, forthcoming

  • Ellis L, Walsh A (1999) Criminologists’ opinion about causes and theories of crime and delinquency. Criminologist 24:1–4

    Google Scholar 

  • Farrington DP (2003) Developmental and life-course criminology: key theoretical and empirical issues—the 2002 Sutherland Award Address. Criminology 41:221–256

    Article  Google Scholar 

  • Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB (2014) Bayesian data analysis, 3rd edn. CRC Press, New York

    Google Scholar 

  • Gill J (2014) Bayesian methods: a social and behavioral sciences approach, 3rd edn. Chapman and Hall/CRC, Boca Raton

    Google Scholar 

  • Gottfredson MR, Hirschi T (1990) A general theory of crime. Stanford University Press, Palo Alto

    Google Scholar 

  • Graham JW (2009) Missing data analysis: making it work in the real world. Annu Rev Psychol 60:549–576

    Article  Google Scholar 

  • Hay C, Forrest W (2006) The development of self-control: examining self-control theory’s stability thesis. Criminology 44:739–774

    Article  Google Scholar 

  • Hay C, Meldrum R, Forrest W, Ciaravolo E (2010) Stability and change in risk seeking: invesitgating the effects of an intervention program. Youth Violence Juv Justice 8:91–106

    Article  Google Scholar 

  • Higgins GE, Jennings WG, Tewksbury R, Gibson CL (2009) Exploring the link between low self-control and violent victimization trajectories in adolescents. Crim Justice Behav 36:1070–1084

    Article  Google Scholar 

  • Hirschi T, Gottfredson MR (2001) Self-control theory. In: Paternoster R, Bachman R (eds) Explaining criminals and crime. Oxford, New York

    Google Scholar 

  • Hoff PD (2009) A first course in Bayesian statistical methods. Springer, New York

    Book  Google Scholar 

  • Jones BL, Nagin DS (2013) A note on a Stata plugin for estimating group-based trajectory models. Sociol Methods Res 42:608–613

    Article  Google Scholar 

  • Kreuter F, Muthén B (2008) Analyzing criminal trajectory profiles: bridging multilevel and group-based approaches using growth mixture modeling. J Quant Criminol 24:1–31

    Article  Google Scholar 

  • Miller JD, Lynam D (2001) Structural models of personality and their relation to antisocial behavior: a meta-analytic review. Criminology 39:765–792

    Article  Google Scholar 

  • Mitchell O, MacKenzie DL (2006) The stability and resiliency of self-control in a sample of incarcerated offenders. Crime Delinq 52:432–499

    Article  Google Scholar 

  • Moffitt TE (1993) Adolescence-limited and life-course persistent antisocial behavior: a developmental taxonomy. Psychol Rev 100:674–701

    Article  Google Scholar 

  • Monahan KC, Steinberg L, Cauffman E, Mulvey EP (2009) Trajectories of antisocial behavior and psychosocial maturity from adolescence to young adulthood. Dev Psychol 45:1654–1668

    Article  Google Scholar 

  • Monahan KC, Steinberg L, Cauffman E, Mulvey EP (2013) Psychosocial (im)maturity from adolescence to early adulthood: distinguishing between adolescence-limited and persisting antisocial behavior. Dev Psychopathol 25:1093–1105

    Article  Google Scholar 

  • Mulvey E P (2012) Research on pathways to desistance [Maricopa County, AZ and Philadelphia County, PA]: Subject Measures, 2000-2010 ICPSR29961-v2 2012-08-20 2013 Inter-university Consortium for Political and Social Research (ICPSR) http://doi.org/10.3886/ICPSR29961.v2 10.3886/ICPSR29961.v2

  • Mulvey EP, Steinberg L, Fagan J, Cauffman E, Piquero AR, Chassin L, Knight GP, Brame R, Schubert CA, Hecker T, Losoya SH (2004) Theory and research on desistance from antisocial activity among serious adolescent offenders. Youth Violence Juv Justice 2:213–236

    Article  Google Scholar 

  • Na C, Paternoster R (2012) Can self-control change substantially over time? Rethinking the relationship between self- and social control. Criminology 50:427–462

    Article  Google Scholar 

  • Nagin DS (2005) Group-based modeling of development. Harvard University Press, Cambridge

    Book  Google Scholar 

  • Nisbett RE, Aronson J, Blair C, Dickens W, Flynn J, Halpern DF, Turkheimer E (2012) Intelligence: new findings and theoretical developments. Am Psychol 67:130–159

    Article  Google Scholar 

  • Pratt TC (2015) A self-control/life-course theory of criminal behavior. Eur J Criminol. doi:10.1177/1477370815587771

    Google Scholar 

  • Ray JV, Jones S, Loughran TA, Jennings WG (2013) Testing the stability of self-control: identifying unique developmental patterns and associated risk factors. Crim Justice Behav 40:588–607

    Article  Google Scholar 

  • Sampson RJ, Laub JH (1993) Crime in the making: pathways and turning points through life. Harvard University Press, Cambridge

    Google Scholar 

  • Schubert CA, Mulvey EP, Steinberg L, Cauffman E, Losoya SH, Hecker T, Chassin L, Knight GP (2004) Operational lessons from the pathways to desistance project. Youth Violence Juv Justice 2:237–255

    Article  Google Scholar 

  • Singer JD, Willett JB (2003) Applied longitudinal data analysis. Oxford University Press, New York

    Book  Google Scholar 

  • Skardhamar T (2010) Distinguishing between facts and artifacts in group-based modeling. Criminology 48:295–320

    Article  Google Scholar 

  • Spearman C (1904) The proof and measurement of association between two things. Am J Psychol 15:72–101

    Article  Google Scholar 

  • Steinberg L (2004) Risk-taking in adolescence: what changes, and why? Ann N Y Acad Sci 1021:51–58

    Article  Google Scholar 

  • Steinberg L (2007) Risk taking in adolescence: new perspectives from brain and behavioral science. Curr Dir Psychol Sci 16:55–59

    Article  Google Scholar 

  • Steinberg L, Albert D, Cauffman E, Banich M, Graham S (2008) Age differences in sensation seeking and impulsivity as indexed by behavior and self-report: evidence for a dual systems model. Dev Psychol 44:1764–1778

    Article  Google Scholar 

  • Sullivan CJ, Loughran T (2014) Investigating the functional form of the self-control—delinquency relationship in a sample of serious young offenders. J Quant Criminol 30:709–730

    Article  Google Scholar 

  • Turner MG, Piquero AR (2002) The stability of self-control. J Crim Justice 30:457–471

    Article  Google Scholar 

  • Weinberger DA, Schwartz GE (1990) Distress and restraint as superordinate dimensions of self-reported adjustment: a typological perspective. J Personal 58:381–417

    Article  Google Scholar 

Download references

Acknowledgments

The Pathways to Desistance project was supported by funds from the following: Office of Juvenile Justice and Delinquency Prevention (2007-MU-FX-0002), National Institute of Justice (2008-IJ-CX-0023), John D. and Catherine T. MacArthur Foundation, William T. Grant Foundation, Robert Wood Johnson Foundation, William Penn Foundation, Center for Disease Control, National Institute on Drug Abuse (R01DA019697), Pennsylvania Commission on Crime and Delinquency, and the Arizona Governor’s Justice Commission. We are grateful for their support. The content of this paper, however, is solely the responsibility of the authors and does not necessarily represent the official views of these agencies. No support was received from any of these agencies for the present study.

Author information

Authors and Affiliations

  1. University of Cincinnati, Cincinnati, OH, USA

    J. C. Barnes, Michael TenEyck, Joseph L. Nedelec & John P. Wright

  2. The University of Texas at Arlington, Arlington, TX, USA

    Sarah A. El Sayed

  3. Pennsylvania State University, Abington, Abington, PA, USA

    Eric J. Connolly

  4. University of Nebraska, Omaha, Omaha, NE, USA

    Joseph A. Schwartz

  5. St. Louis University, St. Louis, MO, USA

    Brian B. Boutwell

  6. King Abdulaziz University, Jeddah, Saudi Arabia

    John P. Wright & Kevin M. Beaver

  7. Florida State University, Tallahassee, FL, USA

    Kevin M. Beaver

  8. The Mind Research Network, Albuquerque, NM, USA

    Nathaniel E. Anderson

Authors
  1. J. C. Barnes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sarah A. El Sayed
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael TenEyck
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Joseph L. Nedelec
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Eric J. Connolly
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Joseph A. Schwartz
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Brian B. Boutwell
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. John P. Wright
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Kevin M. Beaver
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Nathaniel E. Anderson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. C. Barnes.

Additional information

The authors would like to thank Arjan Blokland for his helpful comments on the original manuscript. The final product was much improved based on his suggestions as well as those provided by the anonymous reviewers.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Barnes, J.C., El Sayed, S.A., TenEyck, M. et al. Estimating Relative Stability in Developmental Research: A Critique of Modern Approaches and a Novel Method. J Quant Criminol 33, 319–346 (2017). https://doi.org/10.1007/s10940-016-9298-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10940-016-9298-5

Keywords

Search

Navigation