Journal of Quantitative Criminology

, Volume 33, Issue 2, pp 319–346 | Cite as

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

  • J. C. BarnesEmail author
  • Sarah A. El Sayed
  • Michael TenEyck
  • Joseph L. Nedelec
  • Eric J. Connolly
  • Joseph A. Schwartz
  • Brian B. Boutwell
  • John P. Wright
  • Kevin M. Beaver
  • Nathaniel E. Anderson
Original Paper



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.


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.


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.


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.


Relative stability Impulse control Longitudinal models 



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.


  1. Agresti A, Franklin C (2013) Statistics: the art and science of learning from data, 3rd edn. Pearson, New YorkGoogle Scholar
  2. Allison P (2002) Missing data. Sage, Thousand OaksCrossRefGoogle Scholar
  3. Andrews DA, Bonta J (2010) The psychology of criminal conduct, 5th edn. Matthew Bender & Company, New ProvidenceGoogle Scholar
  4. Arneklev BJ, Cochran JK, Gainey RR (1998) Testing Gottfredson and Hirschi’s “low self-control” stability hypothesis: an exploratory study. Am J Crim Justice 23:107–127CrossRefGoogle Scholar
  5. 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 725–740CrossRefGoogle Scholar
  6. Burt CH, Simons RL (2013) Self-control, thrill seeking, and crime motivation matters. Crim Justice Behav 40:1326–1348CrossRefGoogle Scholar
  7. 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 44:353–396CrossRefGoogle Scholar
  8. Burt CH, Sweeten G, Simons RL (2014) Self-control through emerging adulthood: instability, multidimensionality, and criminological significance. Criminology 52:450–487CrossRefGoogle Scholar
  9. Bushway SD, Piquero AR, Broidy LM, Cauffman E, Mazerolle P (2001) An empirical framework for studying desistance as a process. Criminology 39:491–516CrossRefGoogle Scholar
  10. 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 24:48–60CrossRefGoogle Scholar
  11. Christensen L, Mendoza JL (1986) A method of assessing change in a single subject: an alteration of the RC Index. Behav Ther 17:305–308CrossRefGoogle Scholar
  12. Coyne MA, Vaske JC, Boisvert DL, Wright JP (2015) Sex differences in the stability of self-regulation across childhood. J Dev Life Course Criminol 1:4–20CrossRefGoogle Scholar
  13. Cullen FT (2011) Beyond adolescence-limited criminology: choosing our future—The American Society of Criminology 2010 Sutherland Address. Criminology 49:287–330CrossRefGoogle Scholar
  14. Curran PJ, Bauer DJ (2011) The disaggregation of within-person and between-person effects in longitudinal models of change. Annu Rev Psychol 62:583–619CrossRefGoogle Scholar
  15. Diamond B, Morris R G, and Piquero A R (2015). Stability in the underlying constructs of self-control. Crime Delinq, forthcomingGoogle Scholar
  16. Ellis L, Walsh A (1999) Criminologists’ opinion about causes and theories of crime and delinquency. Criminologist 24:1–4Google Scholar
  17. Farrington DP (2003) Developmental and life-course criminology: key theoretical and empirical issues—the 2002 Sutherland Award Address. Criminology 41:221–256CrossRefGoogle Scholar
  18. Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB (2014) Bayesian data analysis, 3rd edn. CRC Press, New YorkGoogle Scholar
  19. Gill J (2014) Bayesian methods: a social and behavioral sciences approach, 3rd edn. Chapman and Hall/CRC, Boca RatonGoogle Scholar
  20. Gottfredson MR, Hirschi T (1990) A general theory of crime. Stanford University Press, Palo AltoGoogle Scholar
  21. Graham JW (2009) Missing data analysis: making it work in the real world. Annu Rev Psychol 60:549–576CrossRefGoogle Scholar
  22. Hay C, Forrest W (2006) The development of self-control: examining self-control theory’s stability thesis. Criminology 44:739–774CrossRefGoogle Scholar
  23. 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 8:91–106CrossRefGoogle Scholar
  24. 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 36:1070–1084CrossRefGoogle Scholar
  25. Hirschi T, Gottfredson MR (2001) Self-control theory. In: Paternoster R, Bachman R (eds) Explaining criminals and crime. Oxford, New YorkGoogle Scholar
  26. Hoff PD (2009) A first course in Bayesian statistical methods. Springer, New YorkCrossRefGoogle Scholar
  27. Jones BL, Nagin DS (2013) A note on a Stata plugin for estimating group-based trajectory models. Sociol Methods Res 42:608–613CrossRefGoogle Scholar
  28. Kreuter F, Muthén B (2008) Analyzing criminal trajectory profiles: bridging multilevel and group-based approaches using growth mixture modeling. J Quant Criminol 24:1–31CrossRefGoogle Scholar
  29. Miller JD, Lynam D (2001) Structural models of personality and their relation to antisocial behavior: a meta-analytic review. Criminology 39:765–792CrossRefGoogle Scholar
  30. Mitchell O, MacKenzie DL (2006) The stability and resiliency of self-control in a sample of incarcerated offenders. Crime Delinq 52:432–499CrossRefGoogle Scholar
  31. Moffitt TE (1993) Adolescence-limited and life-course persistent antisocial behavior: a developmental taxonomy. Psychol Rev 100:674–701CrossRefGoogle Scholar
  32. Monahan KC, Steinberg L, Cauffman E, Mulvey EP (2009) Trajectories of antisocial behavior and psychosocial maturity from adolescence to young adulthood. Dev Psychol 45:1654–1668CrossRefGoogle Scholar
  33. 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 25:1093–1105CrossRefGoogle Scholar
  34. 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)  10.3886/ICPSR29961.v2
  35. 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 2:213–236CrossRefGoogle Scholar
  36. Na C, Paternoster R (2012) Can self-control change substantially over time? Rethinking the relationship between self- and social control. Criminology 50:427–462CrossRefGoogle Scholar
  37. Nagin DS (2005) Group-based modeling of development. Harvard University Press, CambridgeCrossRefGoogle Scholar
  38. Nisbett RE, Aronson J, Blair C, Dickens W, Flynn J, Halpern DF, Turkheimer E (2012) Intelligence: new findings and theoretical developments. Am Psychol 67:130–159CrossRefGoogle Scholar
  39. Pratt TC (2015) A self-control/life-course theory of criminal behavior. Eur J Criminol. doi: 10.1177/1477370815587771 Google Scholar
  40. 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 40:588–607CrossRefGoogle Scholar
  41. Sampson RJ, Laub JH (1993) Crime in the making: pathways and turning points through life. Harvard University Press, CambridgeGoogle Scholar
  42. 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 2:237–255CrossRefGoogle Scholar
  43. Singer JD, Willett JB (2003) Applied longitudinal data analysis. Oxford University Press, New YorkCrossRefGoogle Scholar
  44. Skardhamar T (2010) Distinguishing between facts and artifacts in group-based modeling. Criminology 48:295–320CrossRefGoogle Scholar
  45. Spearman C (1904) The proof and measurement of association between two things. Am J Psychol 15:72–101CrossRefGoogle Scholar
  46. Steinberg L (2004) Risk-taking in adolescence: what changes, and why? Ann N Y Acad Sci 1021:51–58CrossRefGoogle Scholar
  47. Steinberg L (2007) Risk taking in adolescence: new perspectives from brain and behavioral science. Curr Dir Psychol Sci 16:55–59CrossRefGoogle Scholar
  48. 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 44:1764–1778CrossRefGoogle Scholar
  49. 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 30:709–730CrossRefGoogle Scholar
  50. Turner MG, Piquero AR (2002) The stability of self-control. J Crim Justice 30:457–471CrossRefGoogle Scholar
  51. Weinberger DA, Schwartz GE (1990) Distress and restraint as superordinate dimensions of self-reported adjustment: a typological perspective. J Personal 58:381–417CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • J. C. Barnes
    • 1
    Email author
  • Sarah A. El Sayed
    • 2
  • Michael TenEyck
    • 1
  • Joseph L. Nedelec
    • 1
  • Eric J. Connolly
    • 3
  • Joseph A. Schwartz
    • 4
  • Brian B. Boutwell
    • 5
  • John P. Wright
    • 1
    • 6
  • Kevin M. Beaver
    • 6
    • 7
  • Nathaniel E. Anderson
    • 8
  1. 1.University of CincinnatiCincinnatiUSA
  2. 2.The University of Texas at ArlingtonArlingtonUSA
  3. 3.Pennsylvania State University, AbingtonAbingtonUSA
  4. 4.University of Nebraska, OmahaOmahaUSA
  5. 5.St. Louis UniversitySt. LouisUSA
  6. 6.King Abdulaziz UniversityJeddahSaudi Arabia
  7. 7.Florida State UniversityTallahasseeUSA
  8. 8.The Mind Research NetworkAlbuquerqueUSA

Personalised recommendations