Pub Date : 2013-01-01DOI: 10.1027/1614-2241/A000056
W. Zijlstra, L. V. D. Ark, K. Sijtsma
The sensitivity and the specificity of four outlier scores were studied for four different discordancy tests. The outlier scores were the Mahalanobis distance, a robust version of the Mahalanobis distance, and two measures tailored to discrete data, known as O+ and G+. The discordancy tests were Tukey’s fences (a.k.a. boxplot). Tukey’s fences with adjustment for skewness (adjusted boxplot), the generalized extreme studentized deviate (ESD), and the transformed ESD (ESD-T). Outlier scores O+ and G+ performed better than the Mahalanobis distance and its robust version. Discordancy tests ESD-T and adjusted boxplot were advocated for high specificity and ESD for high sensitivity.
{"title":"Discordancy Tests for Outlier Detection in Multi-Item Questionnaires","authors":"W. Zijlstra, L. V. D. Ark, K. Sijtsma","doi":"10.1027/1614-2241/A000056","DOIUrl":"https://doi.org/10.1027/1614-2241/A000056","url":null,"abstract":"The sensitivity and the specificity of four outlier scores were studied for four different discordancy tests. The outlier scores were the Mahalanobis distance, a robust version of the Mahalanobis distance, and two measures tailored to discrete data, known as O+ and G+. The discordancy tests were Tukey’s fences (a.k.a. boxplot). Tukey’s fences with adjustment for skewness (adjusted boxplot), the generalized extreme studentized deviate (ESD), and the transformed ESD (ESD-T). Outlier scores O+ and G+ performed better than the Mahalanobis distance and its robust version. Discordancy tests ESD-T and adjusted boxplot were advocated for high specificity and ESD for high sensitivity.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"9 1","pages":"69-77"},"PeriodicalIF":3.1,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293057","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 : 2013-01-01DOI: 10.1027/1614-2241/A000053
M. McAssey, J. Helm, F. Hsieh, D. Sbarra, E. Ferrer
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...
{"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}
Pub Date : 2013-01-01DOI: 10.1027/1614-2241/A000057
M. Blanca, J. Arnau, Dolores López-Montiel, Roser Bono, R. Bendayan
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.
{"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}
Pub Date : 2013-01-01DOI: 10.1027/1614-2241/A000060
P. J. Ferrando
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.
{"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}
Pub Date : 2013-01-01DOI: 10.1027/1614-2241/A000075
H. Boeije, Gordon B. Willis
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.
{"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}
Pub Date : 2013-01-01DOI: 10.1027/1614-2241/A000074
Gordon B. Willis, H. Boeije
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 ...
{"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}
Pub Date : 2013-01-01DOI: 10.1027/1614-2241/A000049
Holger Steinmetz
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...
{"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}
Pub Date : 2013-01-01DOI: 10.1027/1614-2241/A000051
Gilles Raîche, Theodore A. Walls, D. Magis, Martin Riopel, J. Blais
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
{"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}
Pub Date : 2013-01-01DOI: 10.1027/1614-2241/A000070
Gordon B. Willis, H. Boeije
{"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}
Pub Date : 2012-01-01DOI: 10.1027/1614-2241/A000041
C. Mara, R. Cribbie, D. Flora, Cathy Labrish, Laura Mills, L. Fiksenbaum
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.
随机前测、后测、随访(RPPF)设计常用于评估干预措施的有效性。这些设计通常解决两个主要的研究问题:(1)治疗组和对照组在测试前和测试后的变化量上是否不同?(2)治疗组和对照组从测试后到随访的变化量是否不同?本研究提出了一个模型来回答这些问题，并将其与最近提出的模型进行比较，该模型用于分析Mun, von Eye和White(2009)使用蒙特卡罗模拟的RPPF设计。所提出的模型在评估RPPF设计的组差异方面提供了比以前的模型更大的能力。
{"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}
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