Daniel Augusto Utsumi, Rogério Tavares Gasi, Mônica Carolina Miranda, Emanuel Henrique Gonçalves Querino, Sabine Pompéia
{"title":"Open-source delay discounting assessment software: Development and usability.","authors":"Daniel Augusto Utsumi, Rogério Tavares Gasi, Mônica Carolina Miranda, Emanuel Henrique Gonçalves Querino, Sabine Pompéia","doi":"10.3758/s13428-025-02598-2","DOIUrl":"10.3758/s13428-025-02598-2","url":null,"abstract":"<p><p>Delay discounting (DD) describes the tendency of individuals to devalue the worth of a reward as a function of the delay in receiving it. DD is impaired in many clinical conditions and changes across development. Many existing automated DD tasks are built on copyrighted software and primarily designed for English speakers, which hinders content editing and accessibility. Given this scenario, we had three objectives: (1) to develop open-source DD software named the \"Waiting Game\" with a user interface (UI) that is easily editable (regarding language, reward type/magnitude and delay duration) via an Excel spreadsheet, and provides automated DD scoring; (2) to create a comprehensive manual (User Guide) to accompany the software; and (3) to assess the software's usability and the clarity of the manual through an online questionnaire completed by experts in cognitive assessment. The software was developed using game design and encompasses three tasks that assess DD under three conditions: (1) hypothetical delays (waiting is imagined) and no real rewards (only points) are gained); (2) real delays (waiting is necessary) and real rewards gained; and (3) real delays and hypothetical rewards. An expert evaluation using the System Usability Scale and the International Test Commission recommendations confirmed the software's suitability. Minor changes were made to the User Guide and UI based on the expert feedback. We conclude that the Waiting Game offers a valid, cost-free, and automated solution for DD assessment that facilitates reward and delay manipulations in hypothetical/real delay and reward paradigms across diverse sociocultural contexts.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"75"},"PeriodicalIF":4.6,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143035832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Manuel Suero, Juan Botella, Juan I Duran, Desirée Blazquez-Rincón
{"title":"Reformulating the meta-analytical random effects model of the standardized mean difference as a mixture model.","authors":"Manuel Suero, Juan Botella, Juan I Duran, Desirée Blazquez-Rincón","doi":"10.3758/s13428-024-02554-6","DOIUrl":"10.3758/s13428-024-02554-6","url":null,"abstract":"<p><p>The classical meta-analytical random effects model (REM) has some weaknesses when applied to the standardized mean difference, g. Essentially, the variance of the studies involved is taken as the conditional variance, given a δ value, instead of the unconditional variance. As a consequence, the estimators of the variances involve a dependency between the g values and their variances that distorts the estimates. The classical REM is expressed as a linear model and the variance of g is obtained through a framework of components of variance. Although the weaknesses of the REM are negligible in practical terms in a wide range of realistic scenarios, all together, they make up an approximate, simplified version of the meta-analytical random effects model. We present an alternative formulation, as a mixture model, and provide formulas for the expected value, variance and skewness of the marginal distribution of g. A Monte Carlo simulation supports the accuracy of the formulas. Then, unbiased estimators of both the mean and the variance of the true effects are proposed, and assessed through Monte Carlo simulations. The advantages of the mixture model formulation over the \"classical\" formulation are discussed.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"74"},"PeriodicalIF":4.6,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11761815/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143035920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ignace T C Hooge, Antje Nuthmann, Marcus Nyström, Diederick C Niehorster, Gijs A Holleman, Richard Andersson, Roy S Hessels
{"title":"The fundamentals of eye tracking part 2: From research question to operationalization.","authors":"Ignace T C Hooge, Antje Nuthmann, Marcus Nyström, Diederick C Niehorster, Gijs A Holleman, Richard Andersson, Roy S Hessels","doi":"10.3758/s13428-024-02590-2","DOIUrl":"10.3758/s13428-024-02590-2","url":null,"abstract":"<p><p>In this article, we discuss operationalizations and examples of experimental design in eye-tracking research. First, we distinguish direct operationalization for entities like saccades, which are closely aligned with their original concepts, and indirect operationalization for concepts not directly measurable, such as attention or mind-wandering. The latter relies on selecting a measurable proxy. Second, we highlight the variability in algorithmic operationalizations and emphasize that changing parameters can affect outcome measures. Transparency in reporting these parameters and algorithms is crucial for comparisons across studies. Third, we provide references to studies for common operationalizations in eye-tracking research and discuss key operationalizations in reading research. Fourth, the IO-model is introduced as a tool to help researchers operationalize difficult concepts. Finally, we present three example experiments with useful methods for eye-tracking research, encouraging readers to consider these examples for inspiration in their own experiments.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"73"},"PeriodicalIF":4.6,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11761893/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143035966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Combining automation and expertise: A semi-automated approach to correcting eye-tracking data in reading tasks.","authors":"Naser Al Madi, Brett Torra, Yixin Li, Najam Tariq","doi":"10.3758/s13428-025-02597-3","DOIUrl":"10.3758/s13428-025-02597-3","url":null,"abstract":"<p><p>In reading tasks, drift can move fixations from one word to another or even another line, invalidating the eye-tracking recording. Manual correction is time-consuming and subjective, while automated correction is fast - yet limited in accuracy. In this paper, we present Fix8 (Fixate), an open-source GUI tool that offers a novel semi-automated correction approach for eye-tracking data in reading tasks. The proposed approach allows the user to collaborate with an algorithm to produce accurate corrections faster without sacrificing accuracy. Through a usability study (N = 14) we assess the time benefits of the proposed technique, and measure the correction accuracy in comparison to manual correction. In addition, we assess subjective workload through the NASA Task Load Index, and user opinions through Likert-scale questions. Our results show that, on average, the proposed technique was 44% faster than manual correction without any sacrifice of accuracy. In addition, users reported a preference for the proposed technique, lower workload, and higher perceived performance compared to manual correction. Fix8 is a valuable tool that offers useful features for generating synthetic eye-tracking data, visualization, filters, data converters, and eye-movement analysis in addition to the main contribution in data correction.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"72"},"PeriodicalIF":4.6,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11762023/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143035644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vivato V Andriamiarana, Pascal Kilian, Holger Brandt, Augustin Kelava
{"title":"Are Bayesian regularization methods a must for multilevel dynamic latent variables models?","authors":"Vivato V Andriamiarana, Pascal Kilian, Holger Brandt, Augustin Kelava","doi":"10.3758/s13428-024-02589-9","DOIUrl":"10.3758/s13428-024-02589-9","url":null,"abstract":"<p><p>Due to the increased availability of intensive longitudinal data, researchers have been able to specify increasingly complex dynamic latent variable models. However, these models present challenges related to overfitting, hierarchical features, non-linearity, and sample size requirements. There are further limitations to be addressed regarding the finite sample performance of priors, including bias, accuracy, and type I error inflation. Bayesian estimation provides the flexibility to treat these issues simultaneously through the use of regularizing priors. In this paper, we aim to compare several Bayesian regularizing priors (ridge, Bayesian Lasso, adaptive spike-and-slab Lasso, and regularized horseshoe). To achieve this, we introduce a multilevel dynamic latent variable model. We then conduct two simulation studies and a prior sensitivity analysis using empirical data. The results show that the ridge prior is able to provide sparse estimation while avoiding overshrinkage of relevant signals, in comparison to other Bayesian regularization priors. In addition, we find that the Lasso and heavy-tailed regularizing priors do not perform well compared to light-tailed priors for the logistic model. In the context of multilevel dynamic latent variable modeling, it is often attractive to diversify the choice of priors. However, we instead suggest prioritizing the choice of ridge priors without extreme shrinkage, which we show can handle the trade-off between informativeness and generality, compared to other priors with high concentration around zero and/or heavy tails.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"71"},"PeriodicalIF":4.6,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11754388/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143021939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A beginner's guide to eye tracking for psycholinguistic studies of reading.","authors":"Elizabeth R Schotter, Brian Dillon","doi":"10.3758/s13428-024-02572-4","DOIUrl":"10.3758/s13428-024-02572-4","url":null,"abstract":"<p><p>Eye tracking has been a popular methodology used to study the visual, cognitive, and linguistic processes underlying word recognition and sentence parsing during reading for several decades. However, the successful use of eye tracking requires researchers to make deliberate choices about how they apply this technique, and there is wide variability across labs and fields with respect to which choices are \"standard.\" We aim to provide an easy-to-reference guideline that can help new researchers with their entrée into eye-tracking-while-reading research. Because the standards do - and should - vary from field to field or study to study as is appropriate for the research question, we do not set a rigid recipe for handling eye tracking data, but rather provide a conceptual framework within which researchers can make informed decisions about how to treat their data so that it is most informative for their research question. Therefore, this paper provides a description of eye movements in reading and an overview of psycholinguistic research on the topic, an overview of experiment design considerations, a description of the data processing pipeline and important choice points and implications, an overview of common dependent measures and their calculation, and a summary of resources for data analysis.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"68"},"PeriodicalIF":4.6,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143021930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Merel Dutry, Alexandra Vereeck, Wouter Duyck, Eva Derous, Stijn Schelfhout, Arnaud Szmalec, Evy Woumans, Mark Schittekatte, Dries Debeer, Nicolas Dirix
{"title":"Validation of the Children's International Cognitive Ability Resource (Ch-ICAR).","authors":"Merel Dutry, Alexandra Vereeck, Wouter Duyck, Eva Derous, Stijn Schelfhout, Arnaud Szmalec, Evy Woumans, Mark Schittekatte, Dries Debeer, Nicolas Dirix","doi":"10.3758/s13428-024-02591-1","DOIUrl":"10.3758/s13428-024-02591-1","url":null,"abstract":"<p><p>The International Cognitive Ability Resource, abbreviated ICAR, counters some of the practical problems researchers face when using good, but proprietary, licensed intelligence tests like the Wechsler tests, which include unfeasible administration times and financial costs. So far, ICAR has been validated for adolescents and adults in many countries, offering a viable test alternative for these populations. For use among children, however, the appropriateness of this resource was yet unknown. Therefore, we set out to develop a children's ICAR: an instrument composed of ICAR-items, which provides a measure of cognitive ability in children between 11 and 14 years of age. The present article discusses the compilation process of the Ch-ICAR drawing from a pilot study, and evaluates its validity based on two additional studies. The pilot study involved 99 primary school pupils and aimed to select items for the Ch-ICAR instrument. Study 1 investigated the basic psychometric qualities of the Ch-ICAR in a sample of 820 secondary school pupils. Study 2 examined the construct validity by cross-validating the Ch-ICAR with on the one hand Raven's 2 Progressive Matrices, and on the other hand the Flemish CoVaT-CHC Basic Version, relying on samples of 91 secondary and 96 primary school pupils, respectively. Results support the utility of the Ch-ICAR as a measure of children's cognitive abilities within a research context.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"66"},"PeriodicalIF":4.6,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143021949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yasin Altinisik, Roy S Hessels, Caspar J Van Lissa, Rebecca M Kuiper
{"title":"An AIC-type information criterion evaluating theory-based hypotheses for contingency tables.","authors":"Yasin Altinisik, Roy S Hessels, Caspar J Van Lissa, Rebecca M Kuiper","doi":"10.3758/s13428-024-02570-6","DOIUrl":"10.3758/s13428-024-02570-6","url":null,"abstract":"<p><p>Researchers face inevitable difficulties when evaluating theory-based hypotheses in the context of contingency tables. Log-linear models are often insufficient to evaluate such hypotheses, as they do not provide enough information on complex relationships between cell probabilities in many real-life applications. These models are usually used to evaluate the relationships between variables using only equality restrictions between model parameters, while specifying theory-based hypotheses often also requires inequality restrictions. Moreover, high-dimensional contingency tables generally contain low cell counts and/or empty cells, complicating parameter estimation in log-linear models. The presence of many parameters in these models also causes difficulties in interpretation when evaluating the hypotheses of interest. This study proposes a method that simplifies evaluating theory-based hypotheses for high-dimensional contingency tables by simultaneously addressing each of the above problems. With this method, theory-based hypotheses, which are specified using equality and/or inequality constraints with respect to (functions of) cell probabilities, are evaluated using an AIC-type information criterion, GORICA. We conduct a simulation study to evaluate the performance of GORICA in the context of contingency tables. Two empirical examples illustrate the use of the method.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"70"},"PeriodicalIF":4.6,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11754365/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143021937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marcus Nyström, Ignace T C Hooge, Roy S Hessels, Richard Andersson, Dan Witzner Hansen, Roger Johansson, Diederick C Niehorster
{"title":"The fundamentals of eye tracking part 3: How to choose an eye tracker.","authors":"Marcus Nyström, Ignace T C Hooge, Roy S Hessels, Richard Andersson, Dan Witzner Hansen, Roger Johansson, Diederick C Niehorster","doi":"10.3758/s13428-024-02587-x","DOIUrl":"10.3758/s13428-024-02587-x","url":null,"abstract":"<p><p>There is an abundance of commercial and open-source eye trackers available for researchers interested in gaze and eye movements. Which aspects should be considered when choosing an eye tracker? The paper describes what distinguishes different types of eye trackers, their suitability for different types of research questions, and highlights questions researchers should ask themselves to make an informed choice.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"67"},"PeriodicalIF":4.6,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11754381/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143021946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Criterion validity of five open-source app-based cognitive and sensory tasks in an Australian adult life course sample aged 18 to 82: Labs without walls.","authors":"Shally Zhou, Brooke Brady, Kaarin J Anstey","doi":"10.3758/s13428-024-02583-1","DOIUrl":"10.3758/s13428-024-02583-1","url":null,"abstract":"<p><p>With recent technical advances, many cognitive and sensory tasks have been adapted for smartphone testing. This study aimed to assess the criterion validity of a subset of self-administered, open-source app-based cognitive and sensory tasks by comparing test performance to lab-based alternatives. An in-person baseline was completed by 43 participants (aged 21 to 82) from the larger Labs without Walls project (Brady et al., 2023) to compare the self-administered, app-based tasks with researcher-administered equivalents. 4 preset tasks sourced from Apple's ResearchKit (Spatial Memory, Trail Making Test, Stroop Test, and dBHL Tone Audiometry) and 1 custom-built task (Ishihara Color Deficiency Test) were compared. All tasks except the Spatial Memory task demonstrated high comparability to the researcher-administered version. Specifically, the Trail Making Tests were strongly correlated (.77 and .78 for parts A and B, respectively), Stroop correlations ranged from .77 to .89 and the Ishihara tasks were moderately correlated (r = .69). ICCs for the Audiometry task ranged from .56 to .96 (Moderate to Excellent) with 83% sensitivity and 100% specificity. Bland-Altman plots revealed a mean bias between -5.35 to 9.67 dB for each ear and frequency with an overall bias of 3.02 and 1.98 for the left and right ears, respectively, within the minimum testing interval. Furthermore, all app-based tasks were significantly correlated with age. These results offer preliminary evidence of the validity of four open-source cognitive and sensory tasks with implications for effective remote testing in non-lab settings.</p>","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 2","pages":"69"},"PeriodicalIF":4.6,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11754352/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143021942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}