Pub Date : 2024-05-01Epub Date: 2023-08-31DOI: 10.1080/00273171.2023.2235682
Bo Zhang, Jing Luo, Jian Li
The graded forced-choice (FC) format has recently emerged as an alternative that may preserve the advantages and overcome the issues of the dichotomous FC measures. The current study presented the first large-scale evaluation of the performance of three types of FC measures (FC2, FC4 and FC5 with 2, 4 and 5 response options, respectively) and compared their performance to their Likert (LK) counterparts (LK2, LK4, and LK5) on (1) psychometric properties, (2) respondent reactions, and (3) susceptibility to response styles. Results showed that, compared to LK measures with the same number of response options, the three FC scales provided better support for the hypothesized factor structure, were perceived as more faking-resistant and cognitive demanding, and were less susceptible to response styles. FC4/5 and LK4/5 demonstrated similarly good reliability, while LK2 provided more reliable scores than FC2. When compared across the three FC measures, FC4 and FC5 displayed comparable psychometric performance and respondent reactions. FC4 exhibited a moderate presence of extreme response style, while FC5 had a weak presence of both extreme and middle response styles. Based on these findings, the study recommends the use of graded FC over dichotomous FC and LK, particularly FC5 when extreme response style is a concern.
{"title":"Moving beyond Likert and Traditional Forced-Choice Scales: A Comprehensive Investigation of the Graded Forced-Choice Format.","authors":"Bo Zhang, Jing Luo, Jian Li","doi":"10.1080/00273171.2023.2235682","DOIUrl":"10.1080/00273171.2023.2235682","url":null,"abstract":"<p><p>The graded forced-choice (FC) format has recently emerged as an alternative that may preserve the advantages and overcome the issues of the dichotomous FC measures. The current study presented the first large-scale evaluation of the performance of three types of FC measures (FC2, FC4 and FC5 with 2, 4 and 5 response options, respectively) and compared their performance to their Likert (LK) counterparts (LK2, LK4, and LK5) on (1) psychometric properties, (2) respondent reactions, and (3) susceptibility to response styles. Results showed that, compared to LK measures with the same number of response options, the three FC scales provided better support for the hypothesized factor structure, were perceived as more faking-resistant and cognitive demanding, and were less susceptible to response styles. FC4/5 and LK4/5 demonstrated similarly good reliability, while LK2 provided more reliable scores than FC2. When compared across the three FC measures, FC4 and FC5 displayed comparable psychometric performance and respondent reactions. FC4 exhibited a moderate presence of extreme response style, while FC5 had a weak presence of both extreme and middle response styles. Based on these findings, the study recommends the use of graded FC over dichotomous FC and LK, particularly FC5 when extreme response style is a concern.</p>","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":" ","pages":"434-460"},"PeriodicalIF":3.8,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10129370","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}
Pub Date : 2024-04-12DOI: 10.1080/00273171.2024.2325210
Published in Multivariate Behavioral Research (Vol. 59, No. 2, 2024)
发表于《多元行为研究》（第 59 卷第 2 期，2024 年）
{"title":"2023 List of Reviewers","authors":"","doi":"10.1080/00273171.2024.2325210","DOIUrl":"https://doi.org/10.1080/00273171.2024.2325210","url":null,"abstract":"Published in Multivariate Behavioral Research (Vol. 59, No. 2, 2024)","PeriodicalId":53155,"journal":{"name":"Multivariate Behavioral Research","volume":"42 1","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140577652","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}
Pub Date : 2024-04-11DOI: 10.1080/00273171.2024.2328381
Marcel C. Schmitt, Leonie V. D. E. Vogelsmeier, Yasemin Erbas, Simon Stuber, Tanja Lischetzke
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...
{"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}
Pub Date : 2024-04-09DOI: 10.1080/00273171.2024.2307518
Esther Ulitzsch, Susu Zhang, Steffi Pohl
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...
{"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}
Pub Date : 2024-04-09DOI: 10.1080/00273171.2024.2335405
Marie Stadel, Marijtje A. J. van Duijn, Aidan G. C. Wright, Laura F. Bringmann, Timon Elmer
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...
{"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}
Pub Date : 2024-04-09DOI: 10.1080/00273171.2024.2330148
Edward E. Rigdon
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...
{"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}
Pub Date : 2024-04-08DOI: 10.1080/00273171.2024.2317928
Lourens Waldorp, Jonas Haslbeck
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...
计算网络中边缘的置信区间和 p 值有助于确定其存在与否，也是量化不确定性的一种自然方法。由于套索估算经常被用于...
{"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}
Pub Date : 2024-03-25DOI: 10.1080/00273171.2024.2310430
Sijing (SJ) Shao
Published in Multivariate Behavioral Research (Ahead of Print, 2024)
发表于《多元行为研究》（2024 年提前出版）
{"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}
Pub Date : 2024-03-01Epub Date: 2024-02-15DOI: 10.1080/00273171.2023.2254767
Michael Brusco, Douglas Steinley, Ashley L Watts
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 K-means clustering. Three simulation studies and analyses of empirical networks were completed to assess the impact of better sum-of-squares solutions.
{"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}
Pub Date : 2024-03-01Epub Date: 2023-09-30DOI: 10.1080/00273171.2023.2248979
Luning Sun, Zijie Qin, Shan Wang, Xuetao Tian, Fang Luo
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.
{"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}
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