Psychological methods最新文献_第10页

Generalized Gaussian signal detection theory: A unified signal detection framework for confidence data analysis. 广义高斯信号检测理论：用于置信数据分析的统一信号检测框架。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-04 DOI: 10.1037/met0000654

K. Miyoshi, Shin'ya Nishida

{"title":"Generalized Gaussian signal detection theory: A unified signal detection framework for confidence data analysis.","authors":"K. Miyoshi, Shin'ya Nishida","doi":"10.1037/met0000654","DOIUrl":"https://doi.org/10.1037/met0000654","url":null,"abstract":"Human decision behavior entails a graded awareness of its certainty, known as a feeling of confidence. Until now, considerable interest has been paid to behavioral and computational dissociations of decision and confidence, which has raised an urgent need for measurement frameworks that can quantify the efficiency of confidence rating relative to decision accuracy (metacognitive efficiency). As a unique addition to such frameworks, we have developed a new signal detection theory paradigm utilizing the generalized Gaussian distribution (GGSDT). This framework evaluates the observer's metacognitive efficiency and internal standard deviation ratio through shape and scale parameters, respectively. The shape parameter quantifies the kurtosis of internal distributions and can practically be understood in reference to the proportion of the Gaussian ideal observer's confidence being disrupted with random guessing (metacognitive lapse rate). This interpretation holds largely irrespective of the contaminating effects of decision accuracy or operating characteristic asymmetry. Thus, the GGSDT enables hitherto unexplored research protocols (e.g., direct comparison of yes/no vs. forced-choice metacognitive efficiency), expected to find applications in various fields of behavioral science. This article provides a detailed walkthrough of the GGSDT analysis with an accompanying R package (ggsdt). (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":null,"pages":null},"PeriodicalIF":7.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140743195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Normality assumption in latent interaction models. 潜在交互模型中的正态性假设。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-04 DOI: 10.1037/met0000657

Sirio Lonati, Mikko Rönkkö, J. Antonakis

{"title":"Normality assumption in latent interaction models.","authors":"Sirio Lonati, Mikko Rönkkö, J. Antonakis","doi":"10.1037/met0000657","DOIUrl":"https://doi.org/10.1037/met0000657","url":null,"abstract":"Latent moderated structural equation (LMS) is one of the most common techniques for estimating interaction effects involving latent variables (i.e., XWITH command in Mplus). However, empirical applications of LMS often overlook that this estimation technique assumes normally distributed variables and that violations of this assumption may lead to seriously biased parameter estimates. Against this backdrop, we study the robustness of LMS to different shapes and sources of nonnormality and examine whether various statistical tests can help researchers detect such distributional misspecifications. In four simulations, we show that LMS can be severely biased when the latent predictors or the structural disturbances are nonnormal. On the contrary, LMS is unaffected by nonnormality originating from measurement errors. As a result, testing for the multivariate normality of observed indicators of the latent predictors can lead to erroneous conclusions, flagging distributional misspecifications in perfectly unbiased LMS results and failing to reject seriously biased results. To solve this issue, we introduce a novel Hausman-type specification test to assess the distributional assumptions of LMS and demonstrate its performance. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":null,"pages":null},"PeriodicalIF":7.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140744784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Correcting for collider effects and sample selection bias in psychological research. 纠正心理学研究中的对撞机效应和样本选择偏差。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-04 DOI: 10.1037/met0000659

Sophia J Lamp, David P MacKinnon

{"title":"Correcting for collider effects and sample selection bias in psychological research.","authors":"Sophia J Lamp, David P MacKinnon","doi":"10.1037/met0000659","DOIUrl":"https://doi.org/10.1037/met0000659","url":null,"abstract":"Colliders, variables that serve as a common outcome of an independent and dependent variable, pose a major challenge in psychological research. Collider variables can induce bias in the estimation of a population relationship of interest when (a) the composition of a research sample is restricted by scores on a collider variable or (b) researchers adjust for a collider variable in their statistical analyses, as they might do for confounder variables. Both cases interfere with the accuracy and generalizability of statistical results. Despite their importance, however, collider effects remain relatively unknown in psychology. This tutorial article summarizes both the conceptual and the mathematical foundation for collider effects and their relevance to psychological research, and then proposes a method to correct for collider bias in cases of restrictive sample selection based on Thorndike's Case III adjustment (1982). Two simulation studies demonstrated Thorndike's correction as a viable solution for correcting collider bias in research studies, even when restriction on the collider variable was extreme and the selected sample size was as low as N = 100. Bias and relative bias results are reported to evaluate how well the correction equation approximates targeted population correlations under a variety of parameter conditions. We illustrate the application of the correction method to a hypothetical study of intelligence and conscientiousness, discuss the applicability of the method to more complex statistical models as a means of detection for collider bias, and provide code for researchers to apply to their own research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":null,"pages":null},"PeriodicalIF":7.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140744573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 pairwise approximate spatiotemporal symmetry algorithm: A method for segmenting time series pairs. 成对近似时空对称算法：一种分割时间序列对的方法。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-04 DOI: 10.1037/met0000341

Gustav Sjobeck, Steven M Boker, Carl E Scheidt, Wolfgang Tschacher

引用次数: 0

Will all youth answer sexual orientation and gender-related survey questions? An analysis of missingness in a large U.S. survey of adolescents and young adults. 是否所有青少年都会回答与性取向和性别相关的调查问题？美国青少年大型调查中的遗漏分析。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-04 DOI: 10.1037/met0000652

Sabra L. Katz-Wise, Lynsie R. Ranker, R. Korkodilos, Jennifer Conti, Kimberly M Nelson, Ziming Xuan, Allegra R Gordon

{"title":"Will all youth answer sexual orientation and gender-related survey questions? An analysis of missingness in a large U.S. survey of adolescents and young adults.","authors":"Sabra L. Katz-Wise, Lynsie R. Ranker, R. Korkodilos, Jennifer Conti, Kimberly M Nelson, Ziming Xuan, Allegra R Gordon","doi":"10.1037/met0000652","DOIUrl":"https://doi.org/10.1037/met0000652","url":null,"abstract":"Some researchers and clinicians may feel hesitant to assess sexual orientation and gender-related characteristics in youth surveys because they are unsure if youth will respond to these questions or are concerned the questions will cause discomfort or offense. This can result in missed opportunities to identify LGBTQ+ youth and address health inequities among this population. The aim of this study was to examine the prevalence and sociodemographic patterns of missingness among survey questions assessing current sexual orientation, gender identity and expression (SOGIE), and past change in sexual orientation (sexual fluidity) among a diverse sample of U.S. youth. Participants (N = 4,245, ages 14-25 years; 95% cisgender, 70% straight/heterosexual, 53% youth of color), recruited from an online survey panel, completed the Wave 1 survey of the longitudinal Sexual Orientation Fluidity in Youth (SO*FLY) Study in 2021. Current SOGIE, past sexual fluidity, and sociodemographic characteristics were assessed for missingness. Overall, 95.7% of participants had no missing questions, 3.8% were missing one question, and 0.5% were missing ≥ 2 questions. Past sexual fluidity and assigned sex were most commonly missing. Sociodemographic differences between participants who skipped the SOGIE questions and the rest of the sample were minimal. Missingness for the examined items was low and similar across sociodemographic characteristics, suggesting that almost all youth are willing to respond to survey questions about SOGIE. SOGIE and sexual fluidity items should be included in surveys and clinical assessments of youth to inform clinical care, policy-making, interventions, and resource development to improve the health of all youth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":null,"pages":null},"PeriodicalIF":7.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140743772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Relating violations of measurement invariance to group differences in response times. 将违反测量不变性与反应时间的群体差异联系起来。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-04 DOI: 10.1037/met0000655

D. Molenaar, Remco Feskens

引用次数: 0

Reconsideration of the type I error rate for psychological science in the era of replication. 复制时代对心理科学I型错误率的再思考。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-01 Epub Date: 2022-04-11 DOI: 10.1037/met0000490

Michael T Carlin, Mack S Costello, Madisyn A Flansburg, Alyssa Darden

引用次数: 0

Causal effect analysis in nonrandomized data with latent variables and categorical indicators: The implementation and benefits of EffectLiteR. 具有潜在变量和分类指标的非随机数据的因果分析：EffectLiteR的实施和益处。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-01 Epub Date: 2022-05-12 DOI: 10.1037/met0000489

Marie-Ann Sengewald, Axel Mayer

{"title":"Causal effect analysis in nonrandomized data with latent variables and categorical indicators: The implementation and benefits of EffectLiteR.","authors":"Marie-Ann Sengewald, Axel Mayer","doi":"10.1037/met0000489","DOIUrl":"10.1037/met0000489","url":null,"abstract":"<p><p>Instead of using manifest proxies for a latent outcome or latent covariates in a causal effect analysis, the R package EffectLiteR facilitates a direct integration of latent variables based on structural equation models (SEM). The corresponding framework considers latent interactions and provides various effect estimates for evaluating the differential effectiveness of treatments. In addition, a user-friendly graphical interface customizes the implementation of the complex models. We aim to enable applications of EffectLiteR in more contexts, and therefore generalize the framework for incorporating latent variables measured with categorical indicators. This refers, for instance, to achievement tests in educational large-scale assessments (LSAs), which are typically constructed in the tradition of item response theory (IRT). We review different modeling strategies for incorporating latent variables from IRT models in an effect analysis (i.e., individual score estimates, plausible values, SEM for categorical indicators). The strategies differ in the handling of measurement error and, thus, have different implications for the accuracy and efficiency of causal effect estimates. We describe our extensions of EffectLiteR based on SEM for categorical indicators and illustrate the model specification step-by-step. In addition, we present a hands-on example, where we apply EffectLiteR in LSA data. The practical benefit of using latent variables in comparison to proficiency scores is of special interest in the application and discussion. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":null,"pages":null},"PeriodicalIF":7.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49474648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Efficient alternatives for Bayesian hypothesis tests in psychology. 心理学中贝叶斯假设检验的有效替代方案。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-01 Epub Date: 2022-04-14 DOI: 10.1037/met0000482

Sandipan Pramanik, Valen E Johnson

引用次数: 0

A structural equation modeling approach for modeling variability as a latent variable. 一种结构方程建模方法，用于将可变性建模为潜在变量。

IF 7 1区心理学

Psychological methods Pub Date : 2024-04-01 Epub Date: 2022-04-11 DOI: 10.1037/met0000477

Yi Feng, Gregory R Hancock

引用次数: 0