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Multivariate Behavioral Research最新文献

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Exploring Within-Person Variability in Qualitative Negative and Positive Emotional Granularity by Means of Latent Markov Factor Analysis 通过潜在马尔可夫因子分析探索定性消极和积极情绪粒度的人内差异性
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-04-11 DOI: 10.1080/00273171.2024.2328381
Marcel C. Schmitt, Leonie V. D. E. Vogelsmeier, Yasemin Erbas, Simon Stuber, Tanja Lischetzke
{"title":"Exploring Within-Person Variability in Qualitative Negative and Positive Emotional Granularity by Means of Latent Markov Factor Analysis","authors":"Marcel C. Schmitt, Leonie V. D. E. Vogelsmeier, Yasemin Erbas, Simon Stuber, Tanja Lischetzke","doi":"10.1080/00273171.2024.2328381","DOIUrl":"https://doi.org/10.1080/00273171.2024.2328381","url":null,"abstract":"Emotional granularity (EG) is an individual’s ability to describe their emotional experiences in a nuanced and specific way. In this paper, we propose that researchers adopt latent Markov factor an...","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":"52 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140577725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Model-Based Approach to the Disentanglement and Differential Treatment of Engaged and Disengaged Item Omissions 基于模型的方法来区分和区别对待 "参与 "和 "脱离 "项目遗漏
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-04-09 DOI: 10.1080/00273171.2024.2307518
Esther Ulitzsch, Susu Zhang, Steffi Pohl
{"title":"A Model-Based Approach to the Disentanglement and Differential Treatment of Engaged and Disengaged Item Omissions","authors":"Esther Ulitzsch, Susu Zhang, Steffi Pohl","doi":"10.1080/00273171.2024.2307518","DOIUrl":"https://doi.org/10.1080/00273171.2024.2307518","url":null,"abstract":"Item omissions in large-scale assessments may occur for various reasons, ranging from disengagement to not being capable of solving the item and giving up. Current response-time-based classificatio...","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":"126 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140588624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Considering the ‘With Whom’: Differences Between Event- and Signal-Contingent ESM Data of Person-Specific Social Interactions 考虑 "与谁"：特定人员社会互动的事件和信号相关 ESM 数据之间的差异
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-04-09 DOI: 10.1080/00273171.2024.2335405
Marie Stadel, Marijtje A. J. van Duijn, Aidan G. C. Wright, Laura F. Bringmann, Timon Elmer
{"title":"Considering the ‘With Whom’: Differences Between Event- and Signal-Contingent ESM Data of Person-Specific Social Interactions","authors":"Marie Stadel, Marijtje A. J. van Duijn, Aidan G. C. Wright, Laura F. Bringmann, Timon Elmer","doi":"10.1080/00273171.2024.2335405","DOIUrl":"https://doi.org/10.1080/00273171.2024.2335405","url":null,"abstract":"Experience sampling studies often aim to capture social interactions. A central methodological question in such studies is whether to use event- or signal-contingent sampling. The little existing r...","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":"90 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140577702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Understanding Composite-Based Structural Equation Modeling Methods From the Perspective of Regression Component Analysis 从回归成分分析的角度理解基于复合的结构方程建模方法
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-04-09 DOI: 10.1080/00273171.2024.2330148
Edward E. Rigdon
{"title":"Understanding Composite-Based Structural Equation Modeling Methods From the Perspective of Regression Component Analysis","authors":"Edward E. Rigdon","doi":"10.1080/00273171.2024.2330148","DOIUrl":"https://doi.org/10.1080/00273171.2024.2330148","url":null,"abstract":"Regression component analysis (RCA) replaces the factors in a factor analysis model with weighted composites of the model’s observed variables. The weight matrix may be calculated from the factor m...","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":"56 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140588619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Network Inference With the Lasso 利用套索进行网络推理
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-04-08 DOI: 10.1080/00273171.2024.2317928
Lourens Waldorp, Jonas Haslbeck
{"title":"Network Inference With the Lasso","authors":"Lourens Waldorp, Jonas Haslbeck","doi":"10.1080/00273171.2024.2317928","DOIUrl":"https://doi.org/10.1080/00273171.2024.2317928","url":null,"abstract":"Calculating confidence intervals and p-values of edges in networks is useful to decide their presence or absence and it is a natural way to quantify uncertainty. Since lasso estimation is often use...","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":"70 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140577701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Assessing and Addressing Zero Inflation in Intensive Longitudinal Data 评估和解决密集纵向数据中的零膨胀问题
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-03-25 DOI: 10.1080/00273171.2024.2310430
Sijing (SJ) Shao
{"title":"Assessing and Addressing Zero Inflation in Intensive Longitudinal Data","authors":"Sijing (SJ) Shao","doi":"10.1080/00273171.2024.2310430","DOIUrl":"https://doi.org/10.1080/00273171.2024.2310430","url":null,"abstract":"Published in Multivariate Behavioral Research (Ahead of Print, 2024)","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":"1 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140300507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Improving the Walktrap Algorithm Using K-Means Clustering. 利用 K-Means 聚类改进 Walktrap 算法
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-03-01 Epub Date: 2024-02-15 DOI: 10.1080/00273171.2023.2254767
Michael Brusco, Douglas Steinley, Ashley L Watts
{"title":"Improving the Walktrap Algorithm Using <i>K</i>-Means Clustering.","authors":"Michael Brusco, Douglas Steinley, Ashley L Watts","doi":"10.1080/00273171.2023.2254767","DOIUrl":"10.1080/00273171.2023.2254767","url":null,"abstract":"<p><p>The walktrap algorithm is one of the most popular community-detection methods in psychological research. Several simulation studies have shown that it is often effective at determining the correct number of communities and assigning items to their proper community. Nevertheless, it is important to recognize that the walktrap algorithm relies on hierarchical clustering because it was originally developed for networks much larger than those encountered in psychological research. In this paper, we present and demonstrate a computational alternative to the hierarchical algorithm that is conceptually easier to understand. More importantly, we show that better solutions to the sum-of-squares optimization problem that is heuristically tackled by hierarchical clustering in the walktrap algorithm can often be obtained using exact or approximate methods for <i>K</i>-means clustering. Three simulation studies and analyses of empirical networks were completed to assess the impact of better sum-of-squares solutions.</p>","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":" ","pages":"266-288"},"PeriodicalIF":3.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11014777/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139742635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Contributions to Constructing Forced-Choice Questionnaires Using the Thurstonian IRT Model. 使用瑟斯顿IRT模型构建强迫选择问卷的贡献。
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-03-01 Epub Date: 2023-09-30 DOI: 10.1080/00273171.2023.2248979
Luning Sun, Zijie Qin, Shan Wang, Xuetao Tian, Fang Luo
{"title":"Contributions to Constructing Forced-Choice Questionnaires Using the Thurstonian IRT Model.","authors":"Luning Sun, Zijie Qin, Shan Wang, Xuetao Tian, Fang Luo","doi":"10.1080/00273171.2023.2248979","DOIUrl":"10.1080/00273171.2023.2248979","url":null,"abstract":"<p><p>Forced-choice questionnaires involve presenting items in blocks and asking respondents to provide a full or partial ranking of the items within each block. To prevent involuntary or voluntary response distortions, blocks are usually formed of items that possess similar levels of desirability. Assembling forced-choice blocks is not a trivial process, because in addition to desirability, both the direction and magnitude of relationships between items and the traits being measured (i.e., factor loadings) need to be carefully considered. Based on simulations and empirical studies using item pairs, we provide recommendations on how to construct item pairs matched by desirability. When all pairs contain items keyed in the same direction, score reliability is improved by maximizing within-block loading differences. Higher reliability is obtained when even a small number of pairs consist of unequally keyed items.</p>","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":" ","pages":"229-250"},"PeriodicalIF":3.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41167895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Cluster Randomized Trials with a Pretest and Posttest: Equivalence of Three-, Two- and One-Level Analyses, and Sample Size Calculation. 采用前测和后测的分组随机试验：三层、两层和一层分析的等效性及样本量计算。
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-03-01 Epub Date: 2023-08-17 DOI: 10.1080/00273171.2023.2240779
Gerard J P Van Breukelen
{"title":"Cluster Randomized Trials with a Pretest and Posttest: Equivalence of Three-, Two- and One-Level Analyses, and Sample Size Calculation.","authors":"Gerard J P Van Breukelen","doi":"10.1080/00273171.2023.2240779","DOIUrl":"10.1080/00273171.2023.2240779","url":null,"abstract":"<p><p>In a cluster randomized trial clusters of persons, for instance, schools or health centers, are assigned to treatments, and all persons in the same cluster get the same treatment. Although less powerful than individual randomization, cluster randomization is a good alternative if individual randomization is impossible or leads to severe treatment contamination (carry-over). Focusing on cluster randomized trials with a pretest and post-test of a quantitative outcome, this paper shows the equivalence of four methods of analysis: a three-level mixed (multilevel) regression for repeated measures with as levels cluster, person, and time, and allowing for unstructured between-cluster and within-cluster covariance matrices; a two-level mixed regression with as levels cluster and person, using change from baseline as outcome; a two-level mixed regression with as levels cluster and time, using cluster means as data; a one-level analysis of cluster means of change from baseline. Subsequently, similar equivalences are shown between a constrained mixed model and methods using the pretest as covariate. All methods are also compared on a cluster randomized trial on mental health in children. From these equivalences follows a simple method to calculate the sample size for a cluster randomized trial with baseline measurement, which is demonstrated step-by-step.</p>","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":" ","pages":"206-228"},"PeriodicalIF":3.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10018178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
ABkPowerCalculator: An App to Compute Power for Balanced (AB)k Single Case Experimental Designs. ABkPowerCalculator：用于平衡（AB）k单案例实验设计的计算功率的应用程序。
IF 3.8 3区 心理学
Multivariate Behavioral Research Pub Date : 2024-03-01 Epub Date: 2023-10-17 DOI: 10.1080/00273171.2023.2261229
Prathiba Batley, Madhav Thamaran, Larry V Hedges
{"title":"ABkPowerCalculator: An App to Compute Power for Balanced (AB)<sup>k</sup> Single Case Experimental Designs.","authors":"Prathiba Batley, Madhav Thamaran, Larry V Hedges","doi":"10.1080/00273171.2023.2261229","DOIUrl":"10.1080/00273171.2023.2261229","url":null,"abstract":"<p><p>Single case experimental designs are an important research design in behavioral and medical research. Although there are design standards prescribed by the What Works Clearinghouse for single case experimental designs, these standards do not include statistically derived power computations. Recently we derived the equations for computing power for (AB)<sup>k</sup> designs. However, these computations and the software code in R may not be accessible to applied researchers who are most likely to want to compute power for their studies. Therefore, we have developed an (AB)<sup>k</sup> power calculator Shiny App (https://abkpowercalculator.shinyapps.io/ABkpowercalculator/) that researchers can use with no software training. These power computations assume that the researcher would be interested in fitting multilevel models with autocorrelations or conduct similar analyses. The purpose of this software contribution is to briefly explain how power is derived for balanced (AB)<sup>k</sup> designs and to elaborate on how to use the Shiny App. The app works well on not just computers but mobile phones without installing the R program. We believe this can be a valuable tool for practitioners and applied researchers who want to plan their single case studies with sufficient power to detect appropriate effect sizes.</p>","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":" ","pages":"406-410"},"PeriodicalIF":3.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41240849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
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