Behavior Research Methods最新文献_第3页

A beta way: A tutorial on Bayesian beta regression for psychological research. A beta way：心理学研究贝叶斯beta回归教程。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-10-02 DOI: 10.3758/s13428-026-03106-w

Jason Geller, Robert Kubinec, Chelsea M Parlett Pelleriti, Matti Vuorre

{"title":"A beta way: A tutorial on Bayesian beta regression for psychological research.","authors":"Jason Geller, Robert Kubinec, Chelsea M Parlett Pelleriti, Matti Vuorre","doi":"10.3758/s13428-026-03106-w","DOIUrl":"https://doi.org/10.3758/s13428-026-03106-w","url":null,"abstract":"Rates, percentages, and proportions are common outcomes in psychology and the social sciences. These outcomes are often analyzed using models that assume normality, but this practice overlooks important features of the data, such as their natural bounds at 0 and 1. As a result, estimates can become distorted. In contrast, treating such outcomes as beta-distributed respects these limits and can yield more accurate estimates. Despite these advantages, the use of beta models in applied research remains limited. Our goal is to provide researchers with practical guidance for adopting beta regression models, illustrated with an example drawn from the psychological literature. We begin by introducing the beta distribution and beta regression, emphasizing key components and assumptions. Next, using data from a learning and memory study, we demonstrate how to fit a beta regression model in R with the Bayesian package {brms} and how to interpret results on the response scale using the packages {marginaleffects} and {easystats}. We also discuss model extensions, including zero-inflated, zero- and one-inflated, and ordered beta models. Basic familiarity with regression modeling and R is assumed. To promote wider adoption of these methods, we provide detailed code and materials at https://doi.org/10.5281/zenodo.15830595 . For researchers preferring a frequentist framework, we include an appendix demonstrating equivalent analyses using {glmmTMB}.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"58 11","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149103773","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}

引用次数: 0

How much habituation is enough? An R application for ad hoc content-related limits of acceptance in behavioral research. 多少习惯才足够？行为研究中与内容相关的接受限制的一项R申请。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-09-30 DOI: 10.3758/s13428-026-03170-2

Konstantin Warneke, Stanislav D Siegel, José Afonso, Marco Herbsleb, Sebastian Wallot

{"title":"How much habituation is enough? An R application for ad hoc content-related limits of acceptance in behavioral research.","authors":"Konstantin Warneke, Stanislav D Siegel, José Afonso, Marco Herbsleb, Sebastian Wallot","doi":"10.3758/s13428-026-03170-2","DOIUrl":"https://doi.org/10.3758/s13428-026-03170-2","url":null,"abstract":"Evaluating test-retest reliability is of crucial importance for clinical decision-making and an integral component of studies in empirical sciences. In psychology, classical test theory focused on reliability coefficients, but research has shown that intraclass correlation coefficients and Cronbach's alpha have limited value in quantifying individual measurement error sources appropriately. Preliminary assumptions such as parallel readings and independency of error sources are violated by practice/habituation effects, i.e., test-retest systematic errors. Although awareness of the need for additional measurement quantifications to properly assess test-retest agreement has increased, many such quantifications are insufficiently implemented. Furthermore, one of the most important agreement analyses introduced by Bland and Altman in 1986 has interpretation limitations, as the limits of agreement are descriptive and not linked to content-based clinical decision-making, oftentimes causing inappropriate usage. To counteract these limitations and improve the implementation of agreement analyses in addition to more commonly used reliability coefficients, we introduce a software package that allows predefining acceptable measurement limits (limits of acceptance) to evaluate the sufficiency of task habituation to gauge individual error sources. The package implements a comprehensive test-retest evaluation in order to improve transparency of data quality reporting in psychological and cognitive research.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"58 11","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13627198/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149103776","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}

引用次数: 0

VRrec: A zero-coding open-source VR body-motion capture tool for behavioral research. VRrec：用于行为研究的零编码开源VR肢体动作捕捉工具。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-09-30 DOI: 10.3758/s13428-026-03169-9

Pawel Kobylinski, Bartosz Muczynski, Daniel Cnotkowski, Mariusz Wierzbowski, Cezary Biele

{"title":"VRrec: A zero-coding open-source VR body-motion capture tool for behavioral research.","authors":"Pawel Kobylinski, Bartosz Muczynski, Daniel Cnotkowski, Mariusz Wierzbowski, Cezary Biele","doi":"10.3758/s13428-026-03169-9","DOIUrl":"https://doi.org/10.3758/s13428-026-03169-9","url":null,"abstract":"We present VRrec, an open-source, motion-tracking and recording tool for PC-based virtual reality (VR). The tool addresses a persistent gap in VR-based experimental research by enabling real-time capture of head, hand, and optional body-tracking data without the need to code. VRrec runs discreetly in the background, collecting positional and rotational data as researchers engage participants with third-party VR applications. This design lets researchers use flexible paradigms that leverage off-the-shelf VR content, eliminating the need to build or modify custom software. However, because VRrec does not read application-level events or object states from the target VR software, it does not directly support paradigms that require synchronization with in-app events or distances to dynamic virtual objects or avatars. VRrec still allows manual event marking for contextual annotation. The resulting data are stored as plain text, which can be imported into various analysis pipelines to derive behavioral metrics in fields such as social psychology, rehabilitation, and consumer research. Evaluations show consistent and stable recording performance with minimal impact on system resources, while also indicating some limitations for study designs that require millisecond-accurate timing precision. By streamlining VR motion data acquisition, VRrec broadens the range of feasible VR study designs and reduces technical barriers, making VR-based behavioral research more accessible. Both the source code and the executable version of VRrec are freely available on GitHub.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"58 11","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13627176/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149102831","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}

引用次数: 0

Emotion profile: A data-driven method to dissect context-specific and co-occurring patterns of emotion. 情绪概况：一种数据驱动的方法来剖析特定情境和共同发生的情绪模式。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-09-30 DOI: 10.3758/s13428-026-03190-y

Xin Hu, Lauren M Bylsma, Dan Zhang

{"title":"Emotion profile: A data-driven method to dissect context-specific and co-occurring patterns of emotion.","authors":"Xin Hu, Lauren M Bylsma, Dan Zhang","doi":"10.3758/s13428-026-03190-y","DOIUrl":"https://doi.org/10.3758/s13428-026-03190-y","url":null,"abstract":"Human emotions are inherently complex, often manifesting intricate patterns of co-occurrence and variations across different contexts. Previous research has employed numerous indices to capture the complexity of emotional experience, yet these indices are usually mathematically redundant, leading to challenges in interpreting the multifaceted nature of emotions and their relevance to mental health. To address this, we propose a data-driven method to derive indices independently capturing co-occurring patterns of people's emotions across various contexts, which we term \"emotion profiles,\" and evaluated it across three online community samples. Study 1 utilized video stimuli as emotion-eliciting contexts; 514 participants reported their experiences of four positive and four negative emotions in each context, which formed their emotion profiles. Parallel principal component analysis identified four significant principal components of emotion profiles (EP-PCs): context non-specificity, positive emotion co-occurrence, negative emotion co-occurrence, and mixed emotion. Study 2 recruited another 509 participants and assessed their emotion profiles twice over a 2-week interval. The four EP-PCs were replicated with different participants and different stimuli (r = .75 to .86), with EP-PC1 and EP-PC2 also showing good test-retest reliability. Study 3 employed an imagined scenario paradigm with 310 participants, confirming that the first three EP-PCs generalized across paradigms. Moreover, exploratory analysis revealed that EP-PCs mediated the associations between emotional granularity and mental health outcomes, clarifying distinct predictive pathways linking positive and negative emotional granularity to depressive and anxiety symptoms. This illustrates how the proposed method may inform emotion-mental health research.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"58 11","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149103786","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}

引用次数: 0

Quantifying infants' everyday restrained experiences in the home using wearable inertial sensors. 使用可穿戴惯性传感器量化婴儿在家中的日常克制体验。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-09-30 DOI: 10.3758/s13428-026-03185-9

Hanzhi Wang, Hailey N Rousey, John M Franchak

{"title":"Quantifying infants' everyday restrained experiences in the home using wearable inertial sensors.","authors":"Hanzhi Wang, Hailey N Rousey, John M Franchak","doi":"10.3758/s13428-026-03185-9","DOIUrl":"https://doi.org/10.3758/s13428-026-03185-9","url":null,"abstract":"Physical restraint-including being held, carried, and restrained in devices-is a common feature of infants' everyday lives. However, previous survey-based and video-based methods cannot simultaneously provide continuous, full-day accounts of infants' restrained experiences. This study developed and validated a machine learning model to quantify infants' restrained time moment-to-moment across the full day in the home environment using wearable sensor data. We used a dataset that includes 146 home-visit sessions from 66 infants, with 30 younger infants aged 4-7 months, and 36 older infants aged 11-14 months. We annotated infants' restrained states in the first 1.5-h video recording of each session as ground-truth labels. The supervised machine-learning model achieved high accuracy (89%) and substantial kappa agreement (κ = .73) compared with human-coded ground truth. The model showed a slight bias toward overestimating unrestrained periods relative to restrained periods, but this bias was mitigated when we used a longer data-aggregation window. The model also showed convergent validity by corroborating prior studies that showed an age-related decrease in infants' overall restrained time throughout the day. In short, the current study demonstrated the utility of using wearable sensors to quantify infants' real-world restrained experiences, offering a new tool for studying how daily restraint influences early development.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"58 11","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13627237/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149102898","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}

引用次数: 0

Including auxiliary cases to address missing data issues through multiple-group models. 包括通过多组模型解决丢失数据问题的辅助案例。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-09-30 DOI: 10.3758/s13428-026-03180-0

Po-Yi Chen

{"title":"Including auxiliary cases to address missing data issues through multiple-group models.","authors":"Po-Yi Chen","doi":"10.3758/s13428-026-03180-0","DOIUrl":"https://doi.org/10.3758/s13428-026-03180-0","url":null,"abstract":"This study explores the use of auxiliary cases to address missing data problems. Extending from the framework of integrative data analysis (IDA), auxiliary cases are defined as cases from other independent samples or existing studies that, while not part of the target group of interest, have sufficient data on the target variables to reduce the impact of missing data on target analyses. These cases can be included in analyses through multiple-group models as an auxiliary group with proper cross-group measurement invariance constraints, while allowing focal structural parameters to be freely estimated. Although past studies based on complete data have found that IDA can stabilize the estimates, most IDA studies mainly consider missing data as a challenge of data integration. In this study, we offer a different perspective by showing that data integration can also serve as a method to limit the impact of missing data. Specifically, our simulations show that the effects of including auxiliary cases on the power and efficiency of the target analyses are more substantial under missing data conditions than under complete data conditions. However, if there are improper cross-group invariance constraints in the analytic model or if inter-dataset heterogeneities are not accounted for in the analyses, the inclusion of auxiliary cases may instead introduce additional bias and reduce power, especially when full information maximum likelihood is used. An empirical example based on two independent experimental datasets is provided. Some issues related to the use of auxiliary cases are also discussed.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"58 11","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149103760","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}

引用次数: 0

A teamwork response tree model for dyadic agreement-accuracy responses. 二元一致性准确响应的团队响应树模型。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-09-25 DOI: 10.3758/s13428-026-03178-8

Peida Zhan, Gaohong Chu

{"title":"A teamwork response tree model for dyadic agreement-accuracy responses.","authors":"Peida Zhan, Gaohong Chu","doi":"10.3758/s13428-026-03178-8","DOIUrl":"https://doi.org/10.3758/s13428-026-03178-8","url":null,"abstract":"Teamwork research increasingly relies on collaborative problem-solving (CPS) tasks to assess how individuals coordinate and integrate knowledge in joint work settings. However, most existing measurement approaches focus on final task accuracy and provide limited insight into the interaction processes that produce collaborative outcomes. Conventional scoring methods typically confound whether team members reach agreement with whether their responses are correct. This study introduces the Teamwork Response Tree (TRTree) model that decomposes dyadic collaborative responses into two linked latent processes: an agreement process and an accuracy process. The model is formulated within the item response tree framework and estimated using Bayesian methods. An empirical illustration using dyadic collaborative matrix reasoning tasks shows that the model yields interpretable estimates of individual ability, team-level ability, team-level agreement propensity, and item-level agreement difficulty. A Monte Carlo simulation study further evaluates parameter recovery under varying data conditions. Results indicate satisfactory parameter recovery and predictable effects of data informativeness on estimation accuracy. By separating convergence from correctness, the TRTree model provides a process-sensitive approach to measuring teamwork and extends item response tree modeling to collaborative problem-solving contexts.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"58 11","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149057371","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}

引用次数: 0

Measuring the dynamics of attentional capture in hand and eye movements with virtual reality. 用虚拟现实技术测量手和眼的注意力捕获动态。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-09-24 DOI: 10.3758/s13428-026-03177-9

Max D Gurr, Jeff Moher, Matthew D Egbert, Christopher D Erb

{"title":"Measuring the dynamics of attentional capture in hand and eye movements with virtual reality.","authors":"Max D Gurr, Jeff Moher, Matthew D Egbert, Christopher D Erb","doi":"10.3758/s13428-026-03177-9","DOIUrl":"10.3758/s13428-026-03177-9","url":null,"abstract":"Laboratory investigations of attentional capture typically use two-dimensional displays and button-press responses, which may limit their generalizability to everyday experiences. The current study used a virtual reality (VR) system to measure the dynamics of attentional capture by simultaneously recording participants' (N = 54) hand and eye movements as they completed a modified additional singleton task. In both a sparsely detailed and richly detailed virtual environment, participants reached to select a uniquely shaped target that was accompanied by a uniquely colored distractor on 50% of trials. We observed robust attentional capture costs across our measures of hand and eye movements, with greater latencies in initiation and movement times, larger reach curvatures, more overall eye movement, and delayed first target fixations on distractor-present trials. Three-dimensional target attraction and distractor attraction scores provided sensitive measures of the time course of attentional capture and allowed for more direct interpretations of performance than reach curvature. Although initiation times, response times, gaze distances, and target fixation proportions were elevated in the richly detailed environment relative to the sparsely detailed environment, we failed to observe a significant interaction between environmental detail and attentional capture costs in any of our measures. Taken together, our results demonstrate the feasibility of using VR to examine the dynamics of attentional capture in immersive virtual environments with richer, more continuous behavioral measures.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"58 11","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13612694/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149036394","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}

引用次数: 0

An LLM canary in the online data coalmine: Bayesian reasoning problems as a capability-gap test for LLM contamination in online samples. 在线数据煤矿中的LLM金丝雀：贝叶斯推理问题作为在线样本中LLM污染的能力差距测试。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-09-24 DOI: 10.3758/s13428-026-03184-w

Vera Wilde

{"title":"An LLM canary in the online data coalmine: Bayesian reasoning problems as a capability-gap test for LLM contamination in online samples.","authors":"Vera Wilde","doi":"10.3758/s13428-026-03184-w","DOIUrl":"https://doi.org/10.3758/s13428-026-03184-w","url":null,"abstract":"The growing use of large language models (LLMs) by participants in online studies threatens the validity of behavioral research data. I propose that Bayesian reasoning problems, which have decades of well-replicated human performance benchmarks, can serve as calibrated detectors of LLM contamination in online samples - an approach I call a capability-gap test. In two preregistered pilots of a Bayesian reasoning training tool (N = 148), participants' accuracy on positive predictive value (PPV) calculation problems reached roughly three times established human performance ceilings. Specifically, 57% of Pilot 2 participants achieved perfect 5/5 scores, against a meta-analytic ceiling of approximately 24% for a single problem presented in natural frequency format, a level at which perfect scores are effectively unattainable. Including two outcome measures - accuracy (correct numerical answer) and Bayesian algorithm use (evidence of the reasoning process) - allows researchers to distinguish LLM contamination from authentic learning effects: accuracy detects contamination, while algorithm use preserves treatment effect signals. This is itself a signal detection problem, structurally analogous to the mass screenings for low-prevalence problems around which the Bayesian reasoning literature was developed. Bayesian reasoning problems offer four advantages as contamination detectors: well-established human performance ceilings from meta-analyses, a large human-LLM performance gap, known reference distributions enabling nuanced assessment, and ease of embedding in existing surveys. I provide practical recommendations for using these problems as data quality diagnostics in online research.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"58 11","pages":""},"PeriodicalIF":5.0,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149036408","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}

引用次数: 0

The effect of incentive type on data quality and quantity in an experience sampling study in a student population. 学生群体经验抽样研究中激励类型对数据质量和数量的影响。

IF 5 2区心理学

Behavior Research Methods Pub Date : 2026-09-23 DOI: 10.3758/s13428-026-03164-0

Milla Pihlajamäki, Ginette Lafit, Olivia J Kirtley, Inez Myin-Germeys, Gudrun Eisele

引用次数: 0