Methodology: European Journal of Research Methods for The Behavioral and Social Sciences最新文献

{"title":"Methodological Advances for Detecting Physiological Synchrony During Dyadic Interactions","authors":"M. McAssey, J. Helm, F. Hsieh, D. Sbarra, E. Ferrer","doi":"10.1027/1614-2241/A000053","DOIUrl":"https://doi.org/10.1027/1614-2241/A000053","url":null,"abstract":"A defining feature of many physiological systems is their synchrony and reciprocal influence. An important challenge, however, is how to measure such features. This paper presents two new approaches for identifying synchrony between the physiological signals of individuals in dyads. The approaches are adaptations of two recently-developed techniques, depending on the nature of the physiological time series. For respiration and thoracic impedance, signals that are measured continuously, we use Empirical Mode Decomposition to extract the low-frequency components of a nonstationary signal, which carry the signal’s trend. We then compute the maximum cross-correlation between the trends of two signals within consecutive overlapping time windows of fixed width throughout each of a number of experimental tasks, and identify the proportion of large values of this measure occurring during each task. For heart rate, which is output discretely, we use a structural linear model that takes into account heteroscedastic...","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"9 1","pages":"41-53"},"PeriodicalIF":3.1,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293044","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}

{"title":"Skewness and Kurtosis in Real Data Samples","authors":"M. Blanca, J. Arnau, Dolores López-Montiel, Roser Bono, R. Bendayan","doi":"10.1027/1614-2241/A000057","DOIUrl":"https://doi.org/10.1027/1614-2241/A000057","url":null,"abstract":"Parametric statistics are based on the assumption of normality. Recent findings suggest that Type I error and power can be adversely affected when data are non-normal. This paper aims to assess the distributional shape of real data by examining the values of the third and fourth central moments as a measurement of skewness and kurtosis in small samples. The analysis concerned 693 distributions with a sample size ranging from 10 to 30. Measures of cognitive ability and of other psychological variables were included. The results showed that skewness ranged between −2.49 and 2.33. The values of kurtosis ranged between −1.92 and 7.41. Considering skewness and kurtosis together the results indicated that only 5.5% of distributions were close to expected values under normality. Although extreme contamination does not seem to be very frequent, the findings are consistent with previous research suggesting that normality is not the rule with real data.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"9 1","pages":"78-84"},"PeriodicalIF":3.1,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1027/1614-2241/A000057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293578","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}

{"title":"A General Linear Framework for Modeling Continuous Responses With Error in Persons and Items","authors":"P. J. Ferrando","doi":"10.1027/1614-2241/A000060","DOIUrl":"https://doi.org/10.1027/1614-2241/A000060","url":null,"abstract":"This study develops a general linear model intended for personality and attitude items with (approximately) continuous responses that is based on a double source of measurement error: items and persons. Two restricted sub-models are then obtained from the general model by placing restrictions on the item and person parameters. And it follows that the standard unidimensional factor-analytic model is one of these sub-models. Procedures for (a) calibrating the items, (b) obtaining individual estimates of location and fluctuation, (c) assessing model-data fit, and (d) assessing measurement precision are discussed for all the models considered, and illustrated with two empirical examples in the personality domain.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"9 1","pages":"150-161"},"PeriodicalIF":3.1,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293589","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}

{"title":"The Cognitive Interviewing Reporting Framework (CIRF): towards the harmonization of cognitive testing reports.","authors":"H. Boeije, Gordon B. Willis","doi":"10.1027/1614-2241/A000075","DOIUrl":"https://doi.org/10.1027/1614-2241/A000075","url":null,"abstract":"Cognitive interviewing is an important qualitative tool for the testing, development, and evaluation of survey questionnaires. Despite the widespread adoption of cognitive testing, there remain large variations in the manner in which specific procedures are implemented, and it is not clear from reports and publications that have utilized cognitive interviewing exactly what procedures have been used, as critical details are often missing. Especially for establishing the effectiveness of procedural variants, it is essential that cognitive interviewing reports contain a comprehensive description of the methods used. One approach to working toward more complete reporting would be to develop and adhere to a common framework for reporting these results. In this article we introduce the Cognitive Interviewing Reporting Framework (CIRF), which applies a checklist approach, and which is based on several existing checklists for reviewing and reporting qualitative research. We propose that researchers apply the CIRF in order to test its usability and to suggest potential adjustments. Over the longer term, the CIRF can be evaluated with respect to its utility in improving the quality of cognitive interviewing reports.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"9 1","pages":"87-95"},"PeriodicalIF":3.1,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293239","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}

{"title":"Reflections on the Cognitive Interviewing Reporting Framework: Efficacy, expectations, and promise for the future.","authors":"Gordon B. Willis, H. Boeije","doi":"10.1027/1614-2241/A000074","DOIUrl":"https://doi.org/10.1027/1614-2241/A000074","url":null,"abstract":"Based on the experiences of three research groups using and evaluating the Cognitive Interviewing Reporting Framework (CIRF), we draw conclusions about the utility of the CIRF as a guide to creating cognitive testing reports. Authors generally found the CIRF checklist to be usable, and that it led to a more complete description of key steps involved. However, despite the explicit direction by the CIRF to include a full explanation of major steps and features (e.g., research objectives and research design), the three cognitive testing reports tended to simply state what was done, without further justification. Authors varied in their judgments concerning whether the CIRF requires the appropriate level of detail. Overall, we believe that current cognitive interviewing practice will benefit from including, within cognitive testing reports, the 10 categories of information specified by the CIRF. Future use of the CIRF may serve to direct the overall research project from the start, and to further the goal of ...","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"9 1","pages":"123-128"},"PeriodicalIF":3.1,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293203","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}

{"title":"Analyzing observed composite differences across groups: Is partial measurement invariance enough?","authors":"Holger Steinmetz","doi":"10.1027/1614-2241/A000049","DOIUrl":"https://doi.org/10.1027/1614-2241/A000049","url":null,"abstract":"Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that...","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"9 1","pages":"1-12"},"PeriodicalIF":3.1,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292977","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}

{"title":"Non-Graphical Solutions for Cattell’s Scree Test","authors":"Gilles Raîche, Theodore A. Walls, D. Magis, Martin Riopel, J. Blais","doi":"10.1027/1614-2241/A000051","DOIUrl":"https://doi.org/10.1027/1614-2241/A000051","url":null,"abstract":"Most of the strategies that have been proposed to determine the number of components that account for the most variation in a principal components analysis of a correlation matrix rely on the analysis of the eigenvalues and on numerical solutions. The Cattell's scree test is a graphical strategy with a nonnumerical solution to determine the number of components to retain. Like Kaiser's rule, this test is one of the most frequently used strategies for determining the number of components to retain. However, the graphical nature of the scree test does not definitively establish the number of components to retain. To circumvent this issue, some numerical solutions are proposed, one in the spirit of Cattell's work and dealing with the scree part of the eigenvalues plot, and one focusing on the elbow part of this plot. A simulation study compares the efficiency of these solutions to those of other previously proposed methods. Extensions to factor analysis are possible and may be particularly useful with many low-dimensional components. Several strategies have been proposed to determine the num- ber of components that account for the most variation in a principal components analysis of a correlation matrix. Most of these rely on the analysis of the eigenvalues of the corre- lation matrix and on numerical solutions. For example, Kaiser's eigenvalue greater than one rule (Guttman, 1954; Kaiser, 1960), parallel analysis (Buja & Eyuboglu, 1992; Horn, 1965; Hoyle & Duvall, 2004), or hypothesis signifi- cance tests, like Bartlett's test (1950), make use of numerical criteria for comparison or statistical significance criteria. Independently of these numerical solutions, Cattell (1966) proposed the scree test, a graphical strategy to determine the number of components to retain. Along with the Kaiser's rule, the scree test is probably the most used strategy and it is included in almost all statistical software dealing with principal components analysis. Unfortunately, it is generally recognized that the graphical nature of the Cattell's scree test does not enable clear decision-making about the number of components to retain. The previously proposed non-graphical solutions for","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"9 1","pages":"23-29"},"PeriodicalIF":3.1,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1027/1614-2241/A000051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293033","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}

{"title":"The Survey Field Needs a Framework for the Systematic Reporting of Questionnaire Development and Pretesting","authors":"Gordon B. Willis, H. Boeije","doi":"10.1027/1614-2241/A000070","DOIUrl":"https://doi.org/10.1027/1614-2241/A000070","url":null,"abstract":"","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"9 1","pages":"85-86"},"PeriodicalIF":3.1,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293190","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}

{"title":"An Improved Model for Evaluating Change in Randomized Pretest, Posttest, Follow-Up Designs","authors":"C. Mara, R. Cribbie, D. Flora, Cathy Labrish, Laura Mills, L. Fiksenbaum","doi":"10.1027/1614-2241/A000041","DOIUrl":"https://doi.org/10.1027/1614-2241/A000041","url":null,"abstract":"Randomized pretest, posttest, follow-up (RPPF) designs are often used for evaluating the effectiveness of an intervention. These designs typically address two primary research questions: (1) Do the treatment and control groups differ in the amount of change from pretest to posttest? and (2) Do the treatment and control groups differ in the amount of change from posttest to follow-up? This study presents a model for answering these questions and compares it to recently proposed models for analyzing RPPF designs due to Mun, von Eye, and White (2009) using Monte Carlo simulation. The proposed model provides increased power over previous models for evaluating group differences in RPPF designs.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"8 1","pages":"97-103"},"PeriodicalIF":3.1,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292917","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}

{"title":"Estimation of and Confidence Interval Formation for Reliability Coefficients of Homogeneous Measurement Instruments","authors":"Ken Kelley, Ying Cheng","doi":"10.1027/1614-2241/A000036","DOIUrl":"https://doi.org/10.1027/1614-2241/A000036","url":null,"abstract":"The reliability of a composite score is a fundamental and important topic in the social and behavioral sciences. The most commonly used reliability estimate of a composite score is coefficient a. However, under regularity conditions, the population value of coefficient a is only a lower bound on the population reliability, unless the items are essentially s-equivalent, an assumption that is likely violated in most applications. A generalization of coefficient a, termed x, is discussed and generally recommended. Furthermore, a point estimate itself almost certainly differs from the population value. Therefore, it is important to provide confidence interval limits so as not to overinterpret the point estimate. Analytic and bootstrap methods are described in detail for confidence interval construction for x .W e go on to recommend the bias-corrected bootstrap approach for x and provide open source and freely available R functions via the MBESS package to implement the methods discussed.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"8 1","pages":"39-50"},"PeriodicalIF":3.1,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292855","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}