Does ROC asymmetry reverse when detecting new stimuli? Reinvestigating whether the retrievability of mnemonic information is task-dependent.

Recently, it has been suggested that the mnemonic information that underlies recognition decisions changes when participants are asked to indicate whether a test stimulus is new rather than old (Brainerd et al., 2021, Journal of Experimental Psychology: Learning Memory, and Cognition, advance online publication). However, some observations that have been interpreted as evidence for this assertion need not be due to mnemonic changes, but may instead be the result of conservative response strategies if the possibility of asymmetric receiver operating characteristics (ROCs) is taken into account. Conversely, recent findings in support of asymmetric ROCs rely on the assumption that the mnemonic information accessed by the decision-maker does not depend on whether an old or a new item is considered to be the target Kellen et al. (2021, Psychological Review 128[6], 1022-1050). Here, we aim to clarify whether there is such a difference in accessibility of mnemonic information by applying signal detection theory. To this end, we used two versions of a simultaneous detection and identification task in which we presented participants with two test stimuli at a time. In one version, the old item was the target; in the other, the new item was the target. This allowed us to assess differences in mnemonic information retrieved in the two tasks while taking possible ROC asymmetry into account. Results clearly indicate that there is indeed a difference in the accessibility of mnemonic information as postulated by (Brainerd et al., 2021, Journal of Experimental Psychology: Learning Memory, and Cognition, advance online publication).

The Seven-parameter Diffusion Model: an Implementation in Stan for Bayesian Analyses.

Diffusion models have been widely used to obtain information about cognitive processes from the analysis of responses and response-time data in two-alternative forced-choice tasks. We present an implementation of the seven-parameter diffusion model, incorporating inter-trial variabilities in drift rate, non-decision time, and relative starting point, in the probabilistic programming language Stan. Stan is a free, open-source software that gives the user much flexibility in defining model properties such as the choice of priors and the model structure in a Bayesian framework. We explain the implementation of the new function and how it is used in Stan. We then evaluate its performance in a simulation study that addresses both parameter recovery and simulation-based calibration. The recovery study shows generally good recovery of the model parameters in line with previous findings. The simulation-based calibration study validates the Bayesian algorithm as implemented in Stan.

An adaptive rejection sampler for sampling from the Wiener diffusion model.

The Wiener diffusion model with two absorbing boundaries is one of the most frequently applied models for jointly modeling responses and response latencies in psychological research. We consider four methods for sampling from the model with and without variability in drift rate, starting point, and non-decision time: Inverse transform sampling, rejection sampling, and two new methods based on adaptive rejection sampling (ARS). We implement these four methods in an R package, validate the methods, and compare their sampling speed in different settings. All four implemented methods provide samples that follow the intended distributions. The ARS-based methods, however, outperform the other methods in sampling speed as the requested sample size increases. We provide guidelines for when using ARS is more efficient than using traditional methods and vice versa.

The simultaneous recognition of multiple words: A process analysis.

In everyday life, recognition decisions often have to be made for multiple objects simultaneously. In contrast, research on recognition memory has predominantly relied on single-item recognition paradigms. We present a first systematic investigation into the cognitive processes that differ between single-word and paired-word tests of recognition memory. In a single-word test, participants categorize previously presented words and new words as having been studied before (old) or not (new). In a paired-word test, however, the test words are randomly paired, and participants provide joint old-new categorizations of both words for each pair. Across two experiments (N = 170), we found better memory performance for words tested singly rather than in pairs and, more importantly, dependencies between the two single-word decisions implied by the paired-word test. We extended two popular model classes of single-item recognition to paired-word recognition, a discrete-state model and a continuous model. Both models attribute performance differences between single-word and paired-word recognition to differences in memory-evidence strength. Discrete-state models account for the dependencies in paired-word decisions in terms of dependencies in guessing. In contrast, continuous models map the dependencies on mnemonic (Experiment 1 & 2) as well as on decisional processes (Experiment 2). However, in both experiments, model comparison favored the discrete-state model, indicating that memory decisions for word pairs seem to be mediated by discrete states. Our work suggests that individuals tackle multiple-item recognition fundamentally differently from single-item recognition, and it provides both a behavioral and model-based paradigm for studying multiple-item recognition.

rtmpt: An R package for fitting response-time extended multinomial processing tree models.

Response-time extended multinomial processing tree models (RT-MPT; Klauer and Kellen, Journal of Mathematical Psychology, 82, 111-130 2018) provide estimates of process-completion times for cognitive processes modeled by means of multinomial processing tree (MPT) models (Batchelder and Riefer, Psychonomic Bulletin & Review, 6, 57-86 1999). We present the R package rtmpt with which it is possible to fit RT-MPT models easily. The package is free and open source, it can be used with two established MPT syntaxes, and has a number of useful features, such as suppressing process-completion times for specific process outcomes, holding process probabilities constant, and changing some prior parameters. In the background of the R package, an altered version of the original C++ code is used for the MCMC sampling. We provide a guide to using rtmpt, validate the underlying hierarchical Bayesian algorithm of rtmpt using simulation-based calibration and show that previously reported results can be reproduced using rtmpt.

Cancellation, negation, and rejection.

In this paper, new evidence is presented for the assumption that the reason-relation reading of indicative conditionals ('if A, then C') reflects a conventional implicature. In four experiments, it is investigated whether relevance effects found for the probability assessment of indicative conditionals (Skovgaard-Olsen, Singmann, & Klauer, 2016a) can be classified as being produced by (a) a conversational implicature, (b) a (probabilistic) presupposition failure, or (c) a conventional implicature. After considering several alternative hypotheses, and the accumulating evidence from other studies as well, we conclude that the evidence is most consistent with the Relevance Effect being the outcome of a conventional implicature. This finding indicates that the reason-relation reading is part of the semantic content of indicative conditionals, albeit not part of their primary truth-conditional content.

Probabilistic conditional reasoning: Disentangling form and content with the dual-source model.

The present research examines descriptive models of probabilistic conditional reasoning, that is of reasoning from uncertain conditionals with contents about which reasoners have rich background knowledge. According to our dual-source model, two types of information shape such reasoning: knowledge-based information elicited by the contents of the material and content-independent information derived from the form of inferences. Two experiments implemented manipulations that selectively influenced the model parameters for the knowledge-based information, the relative weight given to form-based versus knowledge-based information, and the parameters for the form-based information, validating the psychological interpretation of these parameters. We apply the model to classical suppression effects dissecting them into effects on background knowledge and effects on form-based processes (Exp. 3) and we use it to reanalyse previous studies manipulating reasoning instructions. In a model-comparison exercise, based on data of seven studies, the dual-source model outperformed three Bayesian competitor models. Overall, our results support the view that people make use of background knowledge in line with current Bayesian models, but they also suggest that the form of the conditional argument, irrespective of its content, plays a substantive, yet smaller, role.

Controlling the "uncontrollable": Faking effects on the affect misattribution procedure.

In two experiments, the impact of faking on the affect misattribution procedure (AMP) was examined. Results revealed that faking influences both the overall means and the convergent validity of AMP effects in terms of correlations with self-report measures. Faking effects were very selective in that they affected fake-prime trials only, for which AMP effects were significant, but reversed in direction, while AMP effects for non-fake trials remained intact. Importantly, neither strategic advice nor prior task experience was a necessary prerequisite for successful faking. The discussion focuses on possible processes underlying successful faking in the AMP.

Surface Cues Explain the Logic-Liking Effect in Disjunctions.

The finding that people tend to prefer logically valid conclusions over invalid ones is known in the literature as the logic-liking effect and has traditionally been interpreted as evidence for the notion of so-called logical intuitions. Results of more recent empirical studies investigating conditional and categorical syllogisms suggest, however, that previous instances of the logic-liking effect can be accounted for by a confound in terms of surface-feature atmosphere. But the true nature of this atmosphere effect has so far remained largely elusive. Here, we address this issue and introduce two variants of disjunctive syllogisms that enable us to deconfound validity, possibility of the conclusion, and surface-feature atmosphere, which has been impossible with simple disjunctive syllogisms used in earlier studies. Three experiments, in which participants were asked to provide liking and logic ratings for these arguments, revealed that the logic-liking effect in disjunctive syllogisms can be explained by an atmosphere confound in combination with implied demand to consider logicality when judging likability. We also observed a strong atmosphere effect in logic ratings over and above an effect of logical validity per se. Furthermore, atmosphere effects appear to be induced only by specific surface features, namely those that are ecologically valid, if fallible, predictors for logicality. We conclude that acquired atmosphere heuristics provide proxies for logical validity that reasoners often take at face value. A comparison of the present results with previous findings from experiments that focused on conditional and categorical syllogisms additionally indicates that these atmosphere heuristics are used irrespective of an argument's complexity.

Absolute and relative stability of loss aversion across contexts.

Individuals' decisions under risk tend to be in line with the notion that "losses loom larger than gains." This loss aversion in decision making is commonly understood as a stable individual preference that is manifested across different contexts. The presumed stability and generality, which underlies the prominence of loss aversion in the literature at large, has been recently questioned by studies reporting how loss aversion can disappear, and even reverse, as a function of the choice context. The present study investigated whether loss aversion reflects a trait-like attitude of avoiding losses or rather individuals' adaptability to different contexts. We report three experiments investigating the within-subject context sensitivity of loss aversion in a two-alternative forced-choice task. Our results show that the choice context can shift people's loss aversion, though somewhat inconsistently. Moreover, individual estimates of loss aversion are shown to have a considerable degree of stability. Altogether, these results indicate that even though the absolute value of loss aversion can be affected by external factors such as the choice context, estimates of people's loss aversion still capture the relative dispositions toward gains and losses across individuals. (PsycInfo Database Record (c) 2024 APA, all rights reserved).