Pub Date : 2006-01-01DOI: 10.1027/1614-2241.2.1.48
C. Steglich, T. Snijders, P. West
We give a non-technical introduction into recently developed methods for analyzing the co-evolution of social networks and behavior(s) of the network actors. This co-evolution is crucial for a variety of research topics that currently receive a lot of attention, such as the role of peer groups in adolescent development. A family of dynamic actor-driven models for the co-evolution process is sketched, and it is shown how the SIENA software can be used for estimating these models. We illustrate the method by analyzing the co-evolution of friendship networks, taste in music, and alcohol consumption of teenagers.
{"title":"Applying SIENA: An illustrative analysis of the co-evolution of adolescents’ friendship networks, taste in music, and alcohol consumption","authors":"C. Steglich, T. Snijders, P. West","doi":"10.1027/1614-2241.2.1.48","DOIUrl":"https://doi.org/10.1027/1614-2241.2.1.48","url":null,"abstract":"We give a non-technical introduction into recently developed methods for analyzing the co-evolution of social networks and behavior(s) of the network actors. This co-evolution is crucial for a variety of research topics that currently receive a lot of attention, such as the role of peer groups in adolescent development. A family of dynamic actor-driven models for the co-evolution process is sketched, and it is shown how the SIENA software can be used for estimating these models. We illustrate the method by analyzing the co-evolution of friendship networks, taste in music, and alcohol consumption of teenagers.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"2 1","pages":"48-56"},"PeriodicalIF":3.1,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292616","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 : 2005-12-01DOI: 10.1027/1614-1881.1.1.18
J. Vermunt, Carolyn J. Anderson
Abstract. Parameter estimation in joint correspondence analysis (JCA) is typically performed by weighted least squares using the Burt matrix as the data matrix. In this paper, we show how to estimate the JCA model by means of maximum likelihood. For that purpose, JCA is defined as a model for the full K-way distribution by generalizing the correspondence analysis model for three-way tables proposed by Choulakian (1988a, 1988b). The advantage of placing JCA in a more formal statistical framework is that standard chi-squared tests can be applied to assess the goodness-of-fit of unrestricted and restricted models.
{"title":"Joint Correspondence Analysis (JCA) by Maximum Likelihood","authors":"J. Vermunt, Carolyn J. Anderson","doi":"10.1027/1614-1881.1.1.18","DOIUrl":"https://doi.org/10.1027/1614-1881.1.1.18","url":null,"abstract":"Abstract. Parameter estimation in joint correspondence analysis (JCA) is typically performed by weighted least squares using the Burt matrix as the data matrix. In this paper, we show how to estimate the JCA model by means of maximum likelihood. For that purpose, JCA is defined as a model for the full K-way distribution by generalizing the correspondence analysis model for three-way tables proposed by Choulakian (1988a, 1988b). The advantage of placing JCA in a more formal statistical framework is that standard chi-squared tests can be applied to assess the goodness-of-fit of unrestricted and restricted models.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"1 1","pages":"18-26"},"PeriodicalIF":3.1,"publicationDate":"2005-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292379","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 : 2005-01-01DOI: 10.1027/1614-2241.1.4.143
A. Beauducel
Abstract. Because of factor score indeterminacy, there can be substantial shifts in the theoretical meaning of factors and their corresponding score estimates. Therefore, the original factor pattern should be compared with the regression-component loadings (Schonemann & Steiger, 1976) corresponding to the factor-score estimates in order to detect possible shifts in the theoretical meaning. Especially with large loading matrices the similarity of the original factor pattern and the regression components of the score estimates may be ascertained by means of congruency coefficients. It is shown that these congruencies contain information that is not already given by measures of factor-score indeterminacy. Two examples illustrate the use of regression-component analysis for different types of factor-score estimates. The analyses reveal that the Bartlett-score estimates are most appropriate when factor interpretation is based on the factor pattern, which is usually the case in confirmatory factor analysis.
{"title":"How to Describe the Difference between Factors and Corresponding Factor-Score Estimates","authors":"A. Beauducel","doi":"10.1027/1614-2241.1.4.143","DOIUrl":"https://doi.org/10.1027/1614-2241.1.4.143","url":null,"abstract":"Abstract. Because of factor score indeterminacy, there can be substantial shifts in the theoretical meaning of factors and their corresponding score estimates. Therefore, the original factor pattern should be compared with the regression-component loadings (Schonemann & Steiger, 1976) corresponding to the factor-score estimates in order to detect possible shifts in the theoretical meaning. Especially with large loading matrices the similarity of the original factor pattern and the regression components of the score estimates may be ascertained by means of congruency coefficients. It is shown that these congruencies contain information that is not already given by measures of factor-score indeterminacy. Two examples illustrate the use of regression-component analysis for different types of factor-score estimates. The analyses reveal that the Bartlett-score estimates are most appropriate when factor interpretation is based on the factor pattern, which is usually the case in confirmatory factor analysis.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"1 1","pages":"143-158"},"PeriodicalIF":3.1,"publicationDate":"2005-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292497","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":"Methodology - A European Perspective","authors":"Manuel Ato, M. Eid","doi":"10.1027/1614-1881.1.1.1","DOIUrl":"https://doi.org/10.1027/1614-1881.1.1.1","url":null,"abstract":"","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"1 1","pages":"1-1"},"PeriodicalIF":3.1,"publicationDate":"2005-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292322","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 : 2005-01-01DOI: 10.1027/1614-2241.1.3.104
V. Núñez-Antón, J. Orbe
Abstract. The relevance of statistical time to event analysis in the social sciences has proved to be of great importance in the last few years, especially in applications related to labor-market analysis, employment and/or unemployment issues, duration of strikes, and survival of new firms, and in financial applications related to the time a company spends in a given status, for example, bankruptcy. We review some of the techniques that have proved to be adequate for analyzing this type of data and the conditions they require for their proper use. In addition, we extend these techniques in order to be able to analyze specific and more complex situations by using a more general and flexible model. All of these techniques and their extensions are illustrated with an example that studies the duration of firms under bankruptcy in the United States.
{"title":"Statistical Time to Event Analysis in the Social Sciences: Modeling Hazard Rate and Duration in Finance","authors":"V. Núñez-Antón, J. Orbe","doi":"10.1027/1614-2241.1.3.104","DOIUrl":"https://doi.org/10.1027/1614-2241.1.3.104","url":null,"abstract":"Abstract. The relevance of statistical time to event analysis in the social sciences has proved to be of great importance in the last few years, especially in applications related to labor-market analysis, employment and/or unemployment issues, duration of strikes, and survival of new firms, and in financial applications related to the time a company spends in a given status, for example, bankruptcy. We review some of the techniques that have proved to be adequate for analyzing this type of data and the conditions they require for their proper use. In addition, we extend these techniques in order to be able to analyze specific and more complex situations by using a more general and flexible model. All of these techniques and their extensions are illustrated with an example that studies the duration of firms under bankruptcy in the United States.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"1 1","pages":"104-118"},"PeriodicalIF":3.1,"publicationDate":"2005-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292440","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 : 2005-01-01DOI: 10.1027/1614-1881.1.1.27
Holmes W. Finch
Abstract. Multivariate analysis of variance (MANOVA) is a useful tool for social scientists because it allows for the comparison of response-variable means across multiple groups. MANOVA requires that the observations are independent, the response variables are multivariate normally distributed, and the covariance matrix of the response variables is homogeneous across groups. When the assumptions of normality and homogeneous covariance matrices are not met, past research has shown that the type I error rate of the standard MANOVA test statistics can be inflated while their power can be attenuated. The current study compares the performance of a nonparametric alternative to one of the standard parametric test statistics when these two assumptions are not met. Results show that when the assumption of homogeneous covariance matrices is not met, the nonparametric approach has a lower type I error rate and higher power than the most robust parametric statistic. When the assumption of normality is untenable, th...
{"title":"Comparison of the Performance of Nonparametric and Parametric MANOVA Test Statistics when Assumptions Are Violated","authors":"Holmes W. Finch","doi":"10.1027/1614-1881.1.1.27","DOIUrl":"https://doi.org/10.1027/1614-1881.1.1.27","url":null,"abstract":"Abstract. Multivariate analysis of variance (MANOVA) is a useful tool for social scientists because it allows for the comparison of response-variable means across multiple groups. MANOVA requires that the observations are independent, the response variables are multivariate normally distributed, and the covariance matrix of the response variables is homogeneous across groups. When the assumptions of normality and homogeneous covariance matrices are not met, past research has shown that the type I error rate of the standard MANOVA test statistics can be inflated while their power can be attenuated. The current study compares the performance of a nonparametric alternative to one of the standard parametric test statistics when these two assumptions are not met. Results show that when the assumption of homogeneous covariance matrices is not met, the nonparametric approach has a lower type I error rate and higher power than the most robust parametric statistic. When the assumption of normality is untenable, th...","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"1 1","pages":"27-38"},"PeriodicalIF":3.1,"publicationDate":"2005-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1027/1614-1881.1.1.27","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292391","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 : 2005-01-01DOI: 10.1027/1614-1881.1.2.55
Nekane Balluerka, Juana Gómez, Dolores M. Hidalgo
Abstract. Null hypothesis significance testing (NHST) is one of the most widely used methods for testing hypotheses in psychological research. However, it has remained shrouded in controversy throughout the almost seventy years of its existence. The present article reviews both the main criticisms of the method as well as the alternatives which have been put forward to complement or replace it. It focuses basically on those alternatives whose use is recommended by the Task Force on Statistical Inference (TFSI) of the APA (Wilkinson and TFSI, 1999) in the interests of improving the working methods of researchers with respect to statistical analysis and data interpretation. In addition, the arguments used to reject each of the criticisms levelled against NHST are reviewed and the main problems with each of the alternatives are pointed out. It is concluded that rigorous research activity requires use of NHST in the appropriate context, the complementary use of other methods which provide information about as...
摘要零假设显著性检验(NHST)是心理学研究中应用最广泛的假设检验方法之一。然而，在其存在的近七十年中，它一直笼罩在争议之中。本文回顾了对该方法的主要批评以及为补充或取代该方法而提出的替代方案。它主要关注那些由APA的统计推断工作组(TFSI)推荐使用的替代方法(Wilkinson and TFSI, 1999)，以改善研究人员在统计分析和数据解释方面的工作方法。此外，用于拒绝对NHST提出的每个批评的论据进行了审查，并指出了每个替代方案的主要问题。结论是，严谨的研究活动需要在适当的背景下使用NHST，补充使用其他方法来提供关于…
{"title":"The Controversy over Null Hypothesis Significance Testing Revisited","authors":"Nekane Balluerka, Juana Gómez, Dolores M. Hidalgo","doi":"10.1027/1614-1881.1.2.55","DOIUrl":"https://doi.org/10.1027/1614-1881.1.2.55","url":null,"abstract":"Abstract. Null hypothesis significance testing (NHST) is one of the most widely used methods for testing hypotheses in psychological research. However, it has remained shrouded in controversy throughout the almost seventy years of its existence. The present article reviews both the main criticisms of the method as well as the alternatives which have been put forward to complement or replace it. It focuses basically on those alternatives whose use is recommended by the Task Force on Statistical Inference (TFSI) of the APA (Wilkinson and TFSI, 1999) in the interests of improving the working methods of researchers with respect to statistical analysis and data interpretation. In addition, the arguments used to reject each of the criticisms levelled against NHST are reviewed and the main problems with each of the alternatives are pointed out. It is concluded that rigorous research activity requires use of NHST in the appropriate context, the complementary use of other methods which provide information about as...","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"49 1","pages":"55-70"},"PeriodicalIF":3.1,"publicationDate":"2005-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1027/1614-1881.1.2.55","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292429","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 : 2005-01-01DOI: 10.1027/1614-2241.1.3.86
C. Maas, J. Hox
An important problem in multilevel modeling is what constitutes a sufficient sample size for accurate estimation. In multilevel analysis, the major restriction is often the higher-level sample size. In this paper, a simulation study is used to determine the influence of different sample sizes at the group level on the accuracy of the estimates (regression coefficients and variances) and their standard errors. In addition, the influence of other factors, such as the lowest-level sample size and different variance distributions between the levels (different intraclass correlations), is examined. The results show that only a small sample size at level two (meaning a sample of 50 or less) leads to biased estimates of the second-level standard errors. In all of the other simulated conditions the estimates of the regression coefficients, the variance components, and the standard errors are unbiased and accurate.
{"title":"Sufficient Sample Sizes for Multilevel Modeling","authors":"C. Maas, J. Hox","doi":"10.1027/1614-2241.1.3.86","DOIUrl":"https://doi.org/10.1027/1614-2241.1.3.86","url":null,"abstract":"An important problem in multilevel modeling is what constitutes a sufficient sample size for accurate estimation. In multilevel analysis, the major restriction is often the higher-level sample size. In this paper, a simulation study is used to determine the influence of different sample sizes at the group level on the accuracy of the estimates (regression coefficients and variances) and their standard errors. In addition, the influence of other factors, such as the lowest-level sample size and different variance distributions between the levels (different intraclass correlations), is examined. The results show that only a small sample size at level two (meaning a sample of 50 or less) leads to biased estimates of the second-level standard errors. In all of the other simulated conditions the estimates of the regression coefficients, the variance components, and the standard errors are unbiased and accurate.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"1 1","pages":"86-92"},"PeriodicalIF":3.1,"publicationDate":"2005-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1027/1614-2241.1.3.86","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57292483","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：