Process dissociation models are an increasingly important methodology for studying the influence of race on rapid judgments and decisions. While the process dissociation method has contributed many insights into the processes underlying such judgments, there remain several unresolved analytic issues, including which process model best accounts for observed behavior, how best to account for individual differences in process estimates, and how to connect process dissociation estimates to related research stemming from the signal detection tradition. This paper reviews these issues in depth before presenting a simulation study, which allows for a comprehensive examination of the performance of different analytic approaches. Using the information gleaned from this simulation study, I present an updated approach to modeling process dissociation data that will better allow researchers to address questions of interest. Of primary importance, this approach uses a mixed-model framework, which allows for much better handling of individual differences.
AkaikeH. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716–723. doi:10.1109/TAC.1974.1100705
2.
AllenT. J.ShermanJ. W.KlauerK. C. (2010). Social context and the self-regulatoin of implicit bias. Group Processes and Intergroup Relations, 13, 137–149. doi:10.1177/1368430209353635
3.
AmodioD. M.DevineP. G.Harmon-JonesE. (2008). Individual differences in the regulation of intergroup bias: The role of conflict monitoring and neural signals for control. Journal of Personality and Social Psychology, 94, 60–74. doi:10.1037/0022–3514.94.1.60
4.
AmodioD. M.Harmon-JonesE.DevineP. G.CurtinJ. J.HartleyS. L.CovertA. E. (2004). Neural signals for the detection of unintentional race bias. Psychological Science, 15, 88–93. doi:10.1111/j.0963–7214.2004.01502003.x
5.
BaumannJ.DeStenoD. (2010). Emotion guided threat detection: Expecting guns where there are none. Journal of Personality and Social Psychology, 99, 595–610. doi:10.1037/a0020665
6.
BisharaA. J.PayneB. K. (2009). Multinomial process tree models of control and automaticity in weapon misidentification. Journal of Experimental Social Psychology, 45, 524–534. doi:10.1016/j.jesp.2008.11.002
7.
BuchnerA.ErdfelderE.Vaterrodt-PlünneckeB. (1995). Toward unbiased measurement of conscious and unconscious memory processes with the process dissociation framework. Journal of Experimental Psychology: General, 124, 137–160. doi:10.1037/0096–3445.124.2.137
8.
BurkeC. T.BolgerN.ShroutP. E. (2007). Individual differences in adjustment to spousal loss: A nonlinear mixed model analysis. International Journal of Behavioral Development, 31, 405–415. doi:10.1177/0165025407077758
9.
ConreyF. R.ShermanJ. W.GawronskiB.HugenbergK.GroomC. J. (2005). Separating multiple processes in implicit social cognition: The quad model of implicit task performance. Journal of Personality and Social Psychology, 89, 469–487. doi:10.1037/0022–3514.89.4.469
10.
ConwayP.GawronskiB. (2013). Deontological and utilitarian inclinations in moral decision making: A process dissociation approach. Journal of Personality and Social Psychology, 104, 216–235. doi:10.1037/a0031021
11.
CorrellJ.ParkB.JuddC. M.WittenbrinkB. (2002). The police officer’s dilemma: Using ethnicity to disambiguate potentially threatening individuals. Journal of Personality and Social Psychology, 83, 1314–1329. doi:10.1037/0022–3514.83.6.1314
12.
CorrellJ.ParkB.JuddC. M.WittenbrinkB.SadlerM. S.KeeseeT. (2007). Across the thin blue line: Police officers and racial bias in the decision to shoot. Journal of Personality and Social Psychology, 92, 1006–1023. doi:10.1037/0022–3514.92.6.1006
13.
CorrellJ.WittenbrinkB.ParkB.JuddC. M.GoyleA. (2011). Dangerous enough: Moderating racial bias with contextual threat cues. Journal of Experimental Social Psychology, 47, 184–189. doi:10.1016/j.jesp.2010.08.017
14.
CudeckR.HarringJ. R. (2007). Analysis of nonlinear patterns of change with random coefficient models. Annual Review of Psychology, 58, 615–637. doi:10.1146/annurev.psych.58.110405.085520
15.
CurranT.HintzmanD. L. (1995). Violations of the independence assumption in process dissociation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 531–547. doi:10.1037/0278–7393.21.3.531
16.
EstesW. K.MaddoxW. T. (2005). Risks of drawing inferences about cognitive processes from model fits to individual vs. average performance. Psychonomic Bulletin & Review, 12, 403–408. doi:10.3758/BF03193784
17.
GauntR.LeyensJ.-P.DemoulinS. (2002). Intergroup relations and the attribution of emotions: Control over memory for secondary emotions associated with the ingroup and outgroup. Journal of Experimental Social Psychology, 38, 508–514. doi:10.1016/S0022–1031(02)00014–8
18.
GelmanA.CarlinJ. B.SternH. S.RubinD. B. (2004). Bayesian data analysis (2nd ed.). Boca Raton, FL: Chapman & Hall.
19.
GollwitzerP. M.BrandstätterV. (1997). Implementation intentions and effective goal pursuit. Journal of Personality and Social Psychology, 73, 186–199. doi:10.1037/0022–3514.73.1.186
20.
GovorunO.PayneB. K. (2006). Ego-depletion and prejudice: Separating automatic and controlled components. Social Cognition, 24, 111–136. doi:10.1521/soco.2006.24.2.111
21.
JacobyL. L. (1991). A process dissociation framework: Separating automatic from intentional uses of memory. Journal of Memory and Language, 30, 513–541. doi:10.1016/0749–596X(91)90025-F
22.
JacobyL. L.ShroutP. E. (1997). Toward a psychometric analysis of violations of the independence assumption in process dissociation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23, 505–510. doi:10.1037/0278–7393.23.2.505
23.
JuddC. M.WestfallJ.KennyD. A. (2012). Treating stimuli as a random factor in social psychology: A new and comprehensive solution to a pervasive but largely ignored problem. Journal of Personality and Social Psychology, 103, 54–69. doi:10.1037/a0028347
24.
KlauerK. C. (2006). Hierarchical multinomial processing tree models: A latent-class approach. Psychometrika, 71, 7–31. doi:10.1007/s11336–004–1188–3
25.
KlauerK. C. (2010). Hierarchical multinomial processing tree models: A latent-trait approach. Psychometrika, 75, 70–98. doi:10.1007/s11336–009–9141–0
26.
KlauerK. C.VossA. (2008). Effects of race on responses and response latencies in the weapon identification task: A test of six models. Personality and Social Psychology Bulletin, 34, 1124–1140. doi:10.1177/0146167208318603
27.
LindsayD. S.JacobyL. L. (1994). Stroop process dissociations: The relationship between facilitation and interference. Journal of Experimental Psychology: Human Perception and Performance, 20, 219–234. doi:10.1037/0096–1523.20.2.219
28.
LoganG. D.GordonR. D. (2001). Executive control of visual attention in dual-task situations. Psychological Review, 108, 393–434. doi:10.1037//0033–295X.108.2.393
29.
MacmillanN. A.CreelmanC. D. (2005). Detection theory: A user’s guide. Mahwah, NJ: Lawrence Erlbaum Associates.
30.
MeissnerC. A.BrighamJ. C.ButzD. A. (2005). Memory for own- and other-race faces: A dual-process approach. Applied Cognitive Psychology, 19, 545–567. doi:10.1002/acp.1097
31.
MendozaS. A.GollwitzerP. M.AmodioD. M. (2010). Reducing the expression of implicit stereotypes: Reflexive control through implementation intentions. Personality and Social Psychology Bulletin, 36, 512–523. doi:10.1177/0146167210362789
32.
MuthénB. (2004). Latent variable analysis. In KaplanD. (Ed.), The Sage handbook of quantitative methodology for the social sciences (pp. 345–368). Thousand Oaks, CA: Sage.
33.
PayneB. K. (2001). Prejudice and perception: The role of automatic and controlled processes in misperceiving a weapon. Journal of Personality and Social Psychology, 81, 181–192. doi:10.1037/0022–3514.81.2.181
34.
PayneB. K. (2008). What mistakes disclose: A process dissociation approach to automatic and controlled processes in social psychology. Social and Personality Psychology Compass, 2, 1073–1092. doi:10.1111/j.1751–9004.2008.00091.x
35.
PayneB. K.JacobyL. L. (2006). What should a process model deliver?Psychological Inquiry, 17, 194–198. doi:10.1207/s15327965pli1703_4
36.
PinheiroJ. C.BatesD. M. (2000). Mixed-effects models in S and S-PLUS. New York, NY: Springer Verlag.
37.
RafteryA. E. (1995). Bayesian model selection in social research. Sociological Methodology, 25, 111–163. doi:10.2307/271063
38.
RaudenbushS. W.BrykA. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage.
39.
R Core Team. (2013). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from http://www.R-project.org/
40.
RieferD. M.BatchelderW. H. (1991). Statistical inference for multinomial processing tree models. In DoignonJ.-P.FalmagneJ.-C. (Eds.), Mathematical psychology: Current developments (pp. 313–335). New York, NY: Springer-Verlag.
41.
RouderJ. N.LuJ.MoreyR. D.SunD.SpeckmanP. L. (2008). A hierarchical process-dissociation model. Journal of Experimental Psychology: General, 137, 370–389. doi:10.1037/0096–3445.137.2.370
42.
SAS Institute Inc. (2010). SAS/STAT® 9.22 user’s guide. Cary, NC: Author.
43.
ShermanJ. W. (2006). On building a better process model: It’s not only how many, but which ones and by which means. Psychological Inquiry, 17, 173–184. doi:10.1207/s15327965pli1703_3
44.
ShermanJ. W.GawronskiB.GonsalkoraleK.HugenbergK.AllenT. J.GroomC. J. (2008). The self-regulation of automatic associations and behavioral impulses. Psychological Review, 115, 314–335. doi:10.1037/0033–295X.115.2.314
45.
SmithJ. B.BatchelderW. H. (2010). Beta-MPT: Multinomial processing tree models for addressing individual differences. Journal of Mathematical Psychology, 54, 167–183. doi:10.1016/j.jmp.2009.06.007
46.
SpiegelhalterD.ThomasA.BestN.LunnD. (2003). WinBUGS user manual: Version 1.4. Cambridge, UK: MRC Biostatistics Unit, Institute of Public Health.
47.
StahlC.DegnerJ. (2007). Assessing automatic activation of valence: A multinomial model of EAST performance. Experimental Psychology, 54, 99–112. doi:10.1027/1618–3169.54.2.99
48.
StahlC.KlauerK. C. (2007). HMMTree: A computer program for latent-class hierarchical multinomial processing tree models. Behavior Research Methods, 39, 267–273. doi:10.3758/BF03193157
49.
StanislawH.TodorovN. (1999). Calculation of signal detection theory measures. Behavior Research Methods, Instruments, and Computers, 31, 137–149. doi:10.3758/BF03207704
50.
StewartB. D.PayneB. K. (2008). Bringing automatic stereotyping under control: Implementation intentions as efficient means of thought control. Personality and Social Psychology Bulletin, 34, 1332–1345. doi:10.1177/0146167208321269
51.
TothJ. P.ReingoldE. M.JacobyL. L. (1994). Toward a redefinition of implicit memory: Process dissociations following elaborative processing and self-generation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 290–303. doi:10.1037//0278–7393.20.2.290
52.
YonelinasA. P.JacobyL. L. (1996). Response bias and the process-dissociation procedure. Journal of Experimental Psychology: General, 125, 422–434. doi:10.1037/0096–3445.125.4.422
