Psychological methods最新文献_第8页

Percentage of variance accounted for in structural equation models: The rediscovery of the goodness of fit index. 结构方程模型所占的变异百分比：重新发现拟合优度指数。

IF 7 1区心理学

Psychological methods Pub Date : 2024-09-26 DOI: 10.1037/met0000680

Alberto Maydeu-Olivares,Carmen Ximénez,Javier Revuelta

{"title":"Percentage of variance accounted for in structural equation models: The rediscovery of the goodness of fit index.","authors":"Alberto Maydeu-Olivares,Carmen Ximénez,Javier Revuelta","doi":"10.1037/met0000680","DOIUrl":"https://doi.org/10.1037/met0000680","url":null,"abstract":"This article delves into the often-overlooked metric of percentage of variance accounted for in structural equation models (SEM). The goodness of fit index (GFI) provides the percentage of variance of the sum of squared covariances explained by the model. Despite being introduced over four decades ago, the GFI has been overshadowed in favor of fit indices that prioritize distinctions between close and nonclose fitting models. Similar to R² in regression, the GFI should not be used to this aim but rather to quantify the model's utility. The central aim of this study is to reintroduce the GFI, introducing a novel approach to computing the GFI using mean and mean-and-variance corrected test statistics, specifically designed for nonnormal data. We use an extensive simulation study to evaluate the precision of inferences on the GFI, including point estimates and confidence intervals. The findings demonstrate that the GFI can be very accurately estimated, even with nonnormal data, and that confidence intervals exhibit reasonable accuracy across diverse conditions, including large models and nonnormal data scenarios. The article provides methods and code for estimating the GFI in any SEM, urging researchers to reconsider the reporting of the percentage of variance accounted for as an essential tool for model assessment and selection. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":"24 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324987","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

A computationally efficient and robust method to estimate exploratory factor analysis models with correlated residuals. 估算具有相关残差的探索性因子分析模型的高效稳健计算方法。

IF 7.6 1区心理学

Psychological methods Pub Date : 2024-09-23 DOI: 10.1037/met0000609

Guangjian Zhang, Dayoung Lee

引用次数: 0

A computational method to reveal psychological constructs from text data. 从文本数据中揭示心理结构的计算方法。

IF 7.6 1区心理学

Psychological methods Pub Date : 2024-09-19 DOI: 10.1037/met0000700

Alina Herderich, Heribert H Freudenthaler, David Garcia

{"title":"A computational method to reveal psychological constructs from text data.","authors":"Alina Herderich, Heribert H Freudenthaler, David Garcia","doi":"10.1037/met0000700","DOIUrl":"https://doi.org/10.1037/met0000700","url":null,"abstract":"When starting to formalize psychological constructs, researchers traditionally rely on two distinct approaches: the quantitative approach, which defines constructs as part of a testable theory based on prior research and domain knowledge often deploying self-report questionnaires, or the qualitative approach, which gathers data mostly in the form of text and bases construct definitions on exploratory analyses. Quantitative research might lead to an incomplete understanding of the construct, while qualitative research is limited due to challenges in the systematic data processing, especially at large scale. We present a new computational method that combines the comprehensiveness of qualitative research and the scalability of quantitative analyses to define psychological constructs from semistructured text data. Based on structured questions, participants are prompted to generate sentences reflecting instances of the construct of interest. We apply computational methods to calculate embeddings as numerical representations of the sentences, which we then run through a clustering algorithm to arrive at groupings of sentences as psychologically relevant classes. The method includes steps for the measurement and correction of bias introduced by the data generation, and the assessment of cluster validity according to human judgment. We demonstrate the applicability of our method on an example from emotion regulation. Based on short descriptions of emotion regulation attempts collected through an open-ended situational judgment test, we use our method to derive classes of emotion regulation strategies. Our approach shows how machine learning and psychology can be combined to provide new perspectives on the conceptualization of psychological processes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142293946","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

Cross-lagged panel modeling with binary and ordinal outcomes. 二元和序数结果的跨滞后面板建模。

IF 7.6 1区心理学

Psychological methods Pub Date : 2024-09-19 DOI: 10.1037/met0000701

Bengt Muthén, Tihomir Asparouhov, Katie Witkiewitz

引用次数: 0

Thinking clearly about time-invariant confounders in cross-lagged panel models: A guide for choosing a statistical model from a causal inference perspective. 清晰思考交叉滞后面板模型中的时变混杂因素：从因果推论角度选择统计模型指南》。

IF 7.6 1区心理学

Psychological methods Pub Date : 2024-09-19 DOI: 10.1037/met0000647

Kou Murayama, Thomas Gfrörer

引用次数: 0

Scaling and estimation of latent growth models with categorical indicator variables. 使用分类指标变量对潜在增长模型进行缩放和估计。

IF 7.6 1区心理学

Psychological methods Pub Date : 2024-09-19 DOI: 10.1037/met0000679

Kyungmin Lim, Su-Young Kim

{"title":"Scaling and estimation of latent growth models with categorical indicator variables.","authors":"Kyungmin Lim, Su-Young Kim","doi":"10.1037/met0000679","DOIUrl":"https://doi.org/10.1037/met0000679","url":null,"abstract":"Although the interest in latent growth models (LGMs) with categorical indicator variables has recently increased, there are still difficulties regarding the selection of estimation methods and the interpretation of model estimates. However, difficulties in estimating and interpreting categorical LGMs can be avoided by understanding the scaling process. Depending on which parameter constraint methods are selected at each step of the scaling process, the scale applied to the model changes, which can produce significant differences in the estimation results and interpretation. In other words, if a different method is chosen for any of the steps in the scaling process, the estimation results will not be comparable. This study organizes the scaling process and its relationship with estimation methods for categorical LGMs. Specifically, this study organizes the parameter constraint methods included in the scaling process of categorical LGMs and extensively considers the effect of parameter constraints at each step on the meaning of estimates. This study also provides evidence for the scale suitability and interpretability of model estimates through a simple illustration. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142293950","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

How should we model the effect of "change"-Or should we? 我们应该如何模拟 "变化 "的效果？

IF 7.6 1区心理学

Psychological methods Pub Date : 2024-09-19 DOI: 10.1037/met0000663

Ethan M McCormick, Daniel J Bauer

{"title":"How should we model the effect of \"change\"-Or should we?","authors":"Ethan M McCormick, Daniel J Bauer","doi":"10.1037/met0000663","DOIUrl":"https://doi.org/10.1037/met0000663","url":null,"abstract":"There have been long and bitter debates between those who advocate for the use of residualized change as the foundation of longitudinal models versus those who utilize difference scores. However, these debates have focused primarily on modeling change in the outcome variable. Here, we extend these same ideas to the covariate side of the change equation, finding similar issues arise when using lagged versus difference scores as covariates of interest in models of change. We derive a system of relationships that emerge across models differing in how time-varying covariates are represented, and then demonstrate how the set of logical transformations emerges in applied longitudinal settings. We conclude by considering the practical implications of a synthesized understanding of the effects of difference scores as both outcomes and predictors, with specific consequences for mediation analysis within multivariate longitudinal models. Our results suggest that there is reason for caution when using difference scores as time-varying covariates, given their propensity for inducing apparent inferential inversions within different analyses. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142293949","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

Uses of uncertain statistical power: Designing future studies, not evaluating completed studies. 使用不确定的统计能力：设计未来的研究，而不是评估已完成的研究。

IF 7.6 1区心理学

Psychological methods Pub Date : 2024-09-19 DOI: 10.1037/met0000577

Jolynn Pek, Kathryn J Hoisington-Shaw, Duane T Wegener

{"title":"Uses of uncertain statistical power: Designing future studies, not evaluating completed studies.","authors":"Jolynn Pek, Kathryn J Hoisington-Shaw, Duane T Wegener","doi":"10.1037/met0000577","DOIUrl":"https://doi.org/10.1037/met0000577","url":null,"abstract":"tatistical power is a topic of intense interest as part of proposed methodological reforms to improve the defensibility of psychological findings. Power has been used in disparate ways-some that follow and some that do not follow from definitional features of statistical power. We introduce a taxonomy on three uses of power (comparing the performance of different procedures, designing or planning studies, and evaluating completed studies) in the context of new developments that consider uncertainty due to sampling variability. This review first describes fundamental concepts underlying power, new quantitative developments in power analysis, and the application of power analysis in designing studies. To facilitate the pedagogy of using power for design, we provide web applications to illustrate these concepts and examples of power analysis using newly developed methods. We also describe why using power for evaluating completed studies can be counterproductive. We conclude with a discussion of future directions in quantitative research on power analysis and provide recommendations for applying power in substantive research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142293953","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

Solving variables with Monte Carlo simulation experiments: A stochastic root-solving approach. 用蒙特卡罗模拟实验求解变量：随机求根法

IF 7.6 1区心理学

Psychological methods Pub Date : 2024-09-19 DOI: 10.1037/met0000689

R Philip Chalmers

{"title":"Solving variables with Monte Carlo simulation experiments: A stochastic root-solving approach.","authors":"R Philip Chalmers","doi":"10.1037/met0000689","DOIUrl":"https://doi.org/10.1037/met0000689","url":null,"abstract":"Despite their popularity and flexibility, questions remain regarding how to optimally solve particular unknown variables of interest using Monte Carlo simulation experiments. This article reviews two common approaches based on either performing deterministic iterative searches with noisy objective functions or by constructing interpolation estimates given fitted surrogate functions, highlighting the inefficiencies and inferential concerns of both methods. To address these limitations, and to fill a gap in existing Monte Carlo experimental methodology, a novel algorithm termed the probabilistic bisection algorithm with bolstering and interpolations (ProBABLI) is presented with the goal providing efficient, consistent, and unbiased estimates (with associated confidence intervals) for the stochastic root equations found in Monte Carlo simulation research. Properties of the ProBABLI approach are demonstrated using practical sample size planning applications for independent samples t tests and structural equation models given target power rates, precision criteria, and expected power functions that incorporate prior beliefs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142293951","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

Investigating the effects of congruence between within-person associations: A comparison of two extensions of response surface analysis. 调查人内关联之间一致性的影响：响应面分析法两种扩展方法的比较。

IF 7 1区心理学

Psychological methods Pub Date : 2024-09-12 DOI: 10.1037/met0000666

Sarah Humberg,Niclas Kuper,Katrin Rentzsch,Tanja M Gerlach,Mitja D Back,Steffen Nestler

{"title":"Investigating the effects of congruence between within-person associations: A comparison of two extensions of response surface analysis.","authors":"Sarah Humberg,Niclas Kuper,Katrin Rentzsch,Tanja M Gerlach,Mitja D Back,Steffen Nestler","doi":"10.1037/met0000666","DOIUrl":"https://doi.org/10.1037/met0000666","url":null,"abstract":"Response surface analysis (RSA) allows researchers to study whether the degree of congruence between two predictor variables is related to a potential psychological outcome. Here, we adapt RSA to the case in which the two predictor variables whose congruence is of interest refer to individual differences in within-person associations (WPAs) between variables that fluctuate over time. For example, a WPA-congruence hypothesis in research on romantic relationships could posit that partners are happier when they have similar social reactivities-that is, when they have similarly strong WPAs between the quantity of their social interactions and their momentary well-being. One method for testing a WPA-congruence hypothesis is a two-step approach in which the individuals' WPAs are first estimated as random slopes in respective multilevel models, and then these estimates are used as predictors in a regular RSA. As an alternative, we suggest combining RSA with multilevel structural equation modeling (MSEM) by specifying the WPAs as random slopes in the structural equation and using their latent second-order terms to predict the outcome on Level 2. We introduce both approaches and provide and explain their corresponding computer code templates. We also compared the two approaches with a simulation study and found that the MSEM model-despite its complexities (e.g., nonlinear functions of latent slopes)-has advantages over the two-step approach. We conclude that the MSEM approach should be used in practice. We demonstrate its application using data from a daily diary study and offer guidance for important decisions (e.g., about standardization). (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":"10 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174540","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