Ruprecht-Karls-Universitšt Heidelberg

News from the Research Methods Unit

27.11.17 - New GUI for fast-dm

Stephan Radev and Veronika Lerche recently developed a Python-based Graphical User Interface for the diffusion-model analyses with fast-dm. This GUI will be especially useful for beginners in diffusion model analyses. Ist can be downloaded from the fast-dm homepage. We are happy to receive any feedback and suggestions about fast-dm and the GUI!

10.11.17 - New paper in Psychological Research accepted

Abstract:The diffusion model (Ratcliff, 1978) is a stochastic model that is applied to response time (RT) data from binary decision tasks. The model is often used to disentangle different cognitive processes. The validity of the diffusion model parameters has, however, rarely been examined. Only few experimental paradigms have been analyzed with them being restricted to fast response time paradigms. This is attributable to a recommendation stated repeatedly in the diffusion model literature to restrict applications to fast RT paradigms (more specifically, to tasks with mean RTs below 1.5 seconds per trial). We conducted experimental validation studies in which we challenged the necessity of this restriction. We used a binary task that features RTs of several seconds per trial and experimentally examined the convergent and discriminant validity of the four main diffusion model parameters. More precisely, in three experiments, we selectively manipulated these parameters, using a difficulty manipulation (drift rate), speed-accuracy instructions (threshold separation), a more complex motoric task (non-decision time), and an asymmetric payoff matrix (starting point). The results were similar to the findings from experimental validation studies based on fast RT paradigms. Thus, our experiments support the validity of the parameters of the diffusion model and speak in favor of an extension of the model to paradigms based on slower RTs.

Preprint (Note: Some PDFs are password protected! VOSS can help you!)
  • Lerche, V. & Voss, A. (in press). Experimental Validation of the Diffusion Model based on a Slow Response Time Paradigm. Psychological Research. [pdf]
Mischa von Krause

10.11.17 - SMiP has startet!

SMiP Logo

In October 2017, the first cohort of PhD students from the DFG-funded graduate program "Statistical Modelling in Psychology" started. Further information about this program and the participating researchers and institutes can be found on the SMiP homepage. I am happy to welcome SMiP candidate Mischa von Krause in my team!

11.09.17 - New paper in Journal of Personality accepted


Objective: The aim of the present study is to assess whether people differ in the degree to which their well-being is affected by fulfillment of the need for competence. Specifically, we want to examine (a) if inter-individual differences in the within-person coupling of competence satisfaction and well-being (called "competence satisfaction strength"), and of competence dissatisfaction and well-being (called "competence dissatisfaction strength") exist, and (b) if these differences moderate the effects of an experimentally induced frustration of the need for competence.

Method: Two daily diary studies were carried out to assess inter-individual differences in need strengths. In one of these studies, participants (N=129) were subsequently subjected to an experimental frustration of the need for competence.

Results: Including inter-individual differences in the within-person coupling of need fulfillment on well-being improved model fit significantly, indicating that there are statistically meaningful inter-individual differences in need strengths. The interaction of competence satisfaction strength and competence dissatisfaction strength moderated the effect of an experimental competence frustration on negative affect.

Conclusion: Results show that inter-individual differences in the association of competence fulfillment and well-being are a matter of degree, but not quality. They also support the claim that need satisfaction and dissatisfaction are more than psychometric opposites.

Preprint (Note: Some PDFs are password protected! VOSS can help you!)
  • Neubauer, A.B., Lerche, V., & Voss, A. (in press). Inter-individual Differences in the Intra-individual Association of Competence and Well-Being: Combining Experimental and Intensive Longitudinal Designs. Journal of Personality.[pdf]

09.03.17 - New paper in QJEP accepted

Abstract: We investigated motivational influences on affective processing biases; specifically, we were interested in whether anticipating positive vs. negative future outcomes during goal pursuit affects attentional biases towards positive or negative stimuli. Attentional valence biases were assessed with the additional singleton task, with the task-irrelevant singleton colors being either positive, negative, or neutral. The motivational relevance of colors was established in a preceding task: in a balanced design, one color acquired positive valence by indicating the chance to win money, and a different color acquired negative valence by indicating the danger to lose money. Blocks of the additional singleton task were associated with either the chance of winning money (positive outcome focus) or the danger of losing money (negative outcome focus). We found an interaction of outcome focus and singleton valence in the accuracy rates, indicating an incongruency effect: Attentional capture was stronger for positive (negative) singletons in the negative (positive) outcome focus conditions. This result further corroborates the counter-regulation hypothesis, extending previous findings on the motivational top-down regulation of affective processing to the domain of early attentional processes.

Preprint (Note: Some PDFs are password protected! VOSS can help you!)
  • Wentura, D., Müller, P., Rothermund, K., & Voss, A. (in press). Counter-regulation in affective attentional biases: Evidence in the additional singleton paradigm. Quarterly Journal of Experimental Psychology. [pdf]

08.11.16 - New paper in JNPE accepted

  • Waichman, I., & Voss, A.(in press). Payment Procedure in a Public Good Game Experiment: The Effects of Endowment Timing, Tangibility, and Source. Journal of Neuroscience, Psychology, and Economics. [pdf]

Abstract: We study whether and how payment procedure affects behavior in a repeated public good game. To this end, we conducted five treatments, varying the times of paying the initial endowment (week before, before, or after the decisions) and the source of the initial endowment (windfall vs. earned money in a real-effort task). We find little evidence for effects of tangible endowment, windfall endowment, or prepaid endowment. However, we observe that payment procedures do infuence decisions in a repeated public good game experiment.

13.09.2016 - New Frontiers Paper

  • Lerche, V., & Voss, A. (2016). Model Complexity in Diffusion Modeling: Benefits of Making the Model More Parsimonious. Frontiers in Psychology, 7(1324). doi:10.3389/fpsyg.2016.01324 [web]

Abstract:The diffusion model (Ratcliff, 1978) takes into account the reaction time distributions of both correct and erroneous responses from binary decision tasks. This high degree of information usage allows the estimation of different parameters mapping cognitive components such as speed of information accumulation or decision bias. For three of the four main parameters (drift rate, starting point, and non-decision time) trial-to-trial variability is allowed. We investigated the influence of these variability parameters both drawing on simulation studies and on data from an empirical test-retest study using different optimization criteria and different trial numbers. Our results suggest that less complex models (fixing intertrial variabilities of the drift rate and the starting point at zero) can improve the estimation of the psychologically most interesting parameters (drift rate, threshold separation, starting point, and non-decision time).

Paper accepted! (15.08.16)

  • Schubert, A.L., Hagemann, D., Voss, A., Bergmann, K. (in press). Evaluating the model fit of diffusion models with the root mean square error of approximation. Journal of Mathematical Psychology. [pdf]

Abstract: The statistical evaluation of model fit is one of the greatest challenges in the application of diffusion modeling in research on individual differences. Relative model fit indices such as the AIC and BIC are often used for model comparison, but they provide no information about absolute model fit. Statistical and graphical tests can be used to identify individuals whose data cannot be accounted for by the diffusion model, but they become overly sensitive when trial numbers are large, and are subjective and time-consuming. We propose that the evaluation of model fit may be supplemented with the root mean square error of approximation (RMSEA; Steiger & Lind, 1980), which is one of the most popular goodness-of-fit indices in structural equation modeling. It is largely invariant to trial numbers, and allows identifying cases with poor model fit, calculating confidence intervals, and conducting power analyses. In two simulation studies, we evaluated whether the RMSEA correctly rejects badly-fitting models irrespective of trial numbers. Moreover, we evaluated how variation in the number of trials, the degree of measurement noise, the presence of contaminant outliers, and the number of estimated parameters affects RMSEA values. The RMSEA correctly distinguished between well- and badly-fitting models unless trial numbers were very small. Moreover, RMSEA values were in a value range expected from structural equation modeling. Finally, we computed cut-off values as heuristics for model acceptance or rejection. In a third simulation study we assessed how the RMSEA performs in model selection in comparison to the AIC and BIC. The RMSEA correctly identified the generating model in the majority of cases, but was outperformed by the AIC and BIC. All in all, we showed that the RMSEA can be of great value in the evaluation of absolute model fit, but that it should only be used in addition to other fit indices in model selection scenarios.

Paper accepted! (11.07.16)

  • Schubert, A.L., Frischkorn, G.T., Hagemann, D., Voss, A. (in press). Trait characteristics of diffusion model parameters. Journal of Intelligence. [pdf]

Abstract: Cognitive modeling of response time distributions has seen a huge rise of popularity in individual differences research. In particular, several studies have shown that individual differences in the drift rate parameter of the diffusion model, which reflects the speed of information uptake, are substantially related to individual differences in intelligence. However, if diffusion model parameters are to reflect trait-like properties of cognitive processes, they have to qualify as trait-like variables themselves, i.e. that they are stable across time and consistent over different situations. To assess their trait characteristics, we conducted a latent state-trait analysis of diffusion model parameters estimated from three response time tasks that 114 participants completed at two laboratory sessions eight months apart. Drift rate, boundary separation, and non-decision time parameters showed a great temporal stability over a period of eight months. However, the coefficients of consistency and reliability were only low to moderate and highest for drift rate parameters. These results show that the consistent variance of diffusion model parameters across tasks can be regarded as temporally stable ability parameters. Moreover, they illustrate the need for using broader batteries of response time tasks in future studies on the relationship between diffusion model parameters and intelligence.

New paper accepted! (12.04.16)

  • Germar, M., Albrecht, T., Voss, A., & Mojzisch, A. (in press). Social Conformity is due to Biased Stimulus Processing: Electrophysiological and Diffusion Analyses. Social Cognitive and Affective Neuroscience. [pdf]

Abstract: Hundreds of studies have found that humans' decisions are strongly influenced by the opinions of others, even when making simple perceptual decisions. In the present study, we aimed to clarify whether this effect can be explained by social influence biasing (early) perceptual processes. We employed stimulus evoked potentials (SEPs), lateralized readiness potentials (LRPs) and a diffusion model analysis of reaction time data to uncover the neurocognitive processes underlying social conformity in perceptual decision-making. The diffusion model analysis showed that social conformity was due to a biased uptake of stimulus information and accompanied by more careful stimulus processing. As indicated by larger N1- amplitudes, social influence increased early attentional resources for stimulus identification and discrimination. Furthermore, LRP analyses revealed that stimulus processing was biased even in cases of non-conformity. In conclusion, our results suggest that the opinion of others can cause individuals to selectively process stimulus information supporting this opinion, thereby inducing social conformity. This effect is present even when individuals do not blindly follow the majority but rather carefully process stimulus information.

New paper accepted! (05.01.16)

  • Bowen, H., Spaniol, J., Patel, R., & Voss, A. (in press). A Diffusion Model Analysis of Decision Biases Affecting Delayed Recognition of Emotional Stimuli. PLOS ONE.[pdf]

Abstract: Previous empirical work suggests that emotion can influence accuracy and cognitive biases underlying recognition memory, depending on the experimental conditions. The current study examines the effects of arousal and valence on delayed recognition memory using the diffusion model which allows the separation of two decision biases thought to underlie memory: response bias and memory bias. Memory bias has not been given much attention in the literature but can provide insight into the retrieval dynamics of emotion modulated memory. Participants viewed emotional pictorial stimuli; half were given a recognition test 1-day later and the other half 7-days later. Analyses revealed that emotional valence generally evokes liberal responding, whereas high arousal evokes liberal responding only at a short retention interval. The memory bias analyses indicated that participants experienced greater familiarity with high-arousal compared to low-arousal items and this pattern became more pronounced as study-test lag increased; positive items evoke greater familiarity compared to negative and this pattern remained stable across retention interval. The findings provide insight into the separate contributions of valence and arousal to the cognitive mechanisms underlying delayed emotion modulated memory.

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