Methodology: European Journal of Research Methods for The Behavioral and Social Sciences最新文献_第5页

Internet Panels, Professional Respondents, and Data Quality 互联网小组、专业受访者和数据质量

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2015-10-30 DOI: 10.1027/1614-2241/A000094

S. Matthijsse, E. D. Leeuw, J. Hox

引用次数: 42

Assessing Model Fit in Latent Class Analysis When Asymptotics Do Not Hold 当渐近性不成立时，评估潜在类分析中的模型拟合

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2015-01-01 DOI: 10.1027/1614-2241/A000093

Geert H. van Kollenburg, J. Mulder, J. Vermunt

引用次数: 27

How Low Can You Go? An Investigation of the Influence of Sample Size and Model Complexity on Point and Interval Estimates in Two-Level Linear Models 你能走多低?二水平线性模型中样本大小和模型复杂度对点和区间估计影响的研究

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2014-01-01 DOI: 10.1027/1614-2241/A000062

B. Bell, G. Morgan, J. Schoeneberger, J. Kromrey, J. Ferron

{"title":"How Low Can You Go? An Investigation of the Influence of Sample Size and Model Complexity on Point and Interval Estimates in Two-Level Linear Models","authors":"B. Bell, G. Morgan, J. Schoeneberger, J. Kromrey, J. Ferron","doi":"10.1027/1614-2241/A000062","DOIUrl":"https://doi.org/10.1027/1614-2241/A000062","url":null,"abstract":"Whereas general sample size guidelines have been suggested when estimating multilevel models, they are only generalizable to a relatively limited number of data conditions and model structures, both of which are not very feasible for the applied researcher. In an effort to expand our understanding of two-level multilevel models under less than ideal conditions, Monte Carlo methods, through SAS/IML, were used to examine model convergence rates, parameter point estimates (statistical bias), parameter interval estimates (confidence interval accuracy and precision), and both Type I error control and statistical power of tests associated with the fixed effects from linear two-level models estimated with PROC MIXED. These outcomes were analyzed as a function of: (a) level-1 sample size, (b) level-2 sample size, (c) intercept variance, (d) slope variance, (e) collinearity, and (f) model complexity. Bias was minimal across nearly all conditions simulated. The 95% confidence interval coverage and Type I error rate tended to be slightly conservative. The degree of statistical power was related to sample sizes and level of fixed effects; higher power was observed with larger sample sizes and level-1 fixed effects. Hierarchically organized data are commonplace in educa- tional, clinical, and other settings in which research often occurs. Students are nested within classrooms or teachers, and teachers are nested within schools. Alternatively, service recipients are nested within social workers providing ser- vices, who may in turn be nested within local civil service entities. Conducting research at any of these levels while ignoring the more detailed levels (students) or contextual levels (schools) can lead to erroneous conclusions. As such, multilevel models have been developed to properly account","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"84 1","pages":"1-11"},"PeriodicalIF":3.1,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293598","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: 156

The Impact of Using Incorrect Weights With the Multiple Membership Random Effects Model 多隶属度随机效应模型中权重不正确的影响

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2014-01-01 DOI: 10.1027/1614-2241/A000066

L. Smith, S. N. Beretvas

引用次数: 19

Sample Size Requirements of the Robust Weighted Least Squares Estimator 鲁棒加权最小二乘估计的样本量要求

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2014-01-01 DOI: 10.1027/1614-2241/A000068

Morten Moshagen, J. Musch

{"title":"Sample Size Requirements of the Robust Weighted Least Squares Estimator","authors":"Morten Moshagen, J. Musch","doi":"10.1027/1614-2241/A000068","DOIUrl":"https://doi.org/10.1027/1614-2241/A000068","url":null,"abstract":"The present study investigated sample size requirements of maximum likelihood (ML) and robust weighted least squares (robust WLS) estimation for ordinal data with confirmatory factor analysis (CFA) models with 3-10 indicators per factor, primary loadings between .4 and .9, and four different levels of categorization (2, 3, 5, and 7). Additionally, the utility of the H-measure of construct reliability (an index combining the number of indicators and the magnitude of loadings) in predicting sample size requirements was examined. Results indicated that a higher number of indicators per factors and higher factor loadings increased the rates of proper convergence and solution propriety. However, the H-measure could only partly account for the results. Moreover, it was demonstrated that robust WLS was mostly superior to ML, suggesting that there is little reason to prefer ML over robust WLS when the data are ordinal. Sample size recommendations for the robust WLS estimator are provided. Confirmatory factor analysis (CFA), as a special case of structural equation models, is a powerful technique to model and test relationships between manifest variables and latent constructs. Estimation of CFA models usually proceeds using normal-theory estimators with the most commonly used being maximum likelihood (ML). Nor- mal-theory estimation methods assume continuous and multivariate normally distributed observed variables; how- ever, many measures in the social and behavioral sciences are characterized by a dichotomous or an ordinal level of measurement. Although the items of a test or a question- naire are conceived to be measures of a theoretically contin- uous construct, the observed responses are discrete realizations of a small number of categories and, thus, lack the scale and distributional properties assumed by normal- theory estimators.","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"421 1","pages":"60-70"},"PeriodicalIF":3.1,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293649","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: 105

A Hierarchical Bayesian Model With Correlated Residuals for Investigating Stability and Change in Intensive Longitudinal Data Settings 一种具有相关残差的层次贝叶斯模型用于研究密集纵向数据设置的稳定性和变化

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2014-01-01 DOI: 10.1027/1614-2241/A000083

F. Gasimova, A. Robitzsch, O. Wilhelm, G. Hülür

{"title":"A Hierarchical Bayesian Model With Correlated Residuals for Investigating Stability and Change in Intensive Longitudinal Data Settings","authors":"F. Gasimova, A. Robitzsch, O. Wilhelm, G. Hülür","doi":"10.1027/1614-2241/A000083","DOIUrl":"https://doi.org/10.1027/1614-2241/A000083","url":null,"abstract":"The present paper’s focus is the modeling of interindividual and intraindividual variability in longitudinal data. We propose a hierarchical Bayesian model with correlated residuals, employing an autoregressive parameter AR(1) for focusing on intraindividual variability. The hierarchical model possesses four individual random effects: intercept, slope, variability, and autocorrelation. The performance of the proposed Bayesian estimation is investigated in simulated longitudinal data with three different sample sizes (N = 100, 200, 500) and three different numbers of measurement points (T = 10, 20, 40). The initial simulation values are selected according to the results of the first 20 measurement occasions from a longitudinal study on working memory capacity in 9th graders. Within this simulation study, we investigate the root mean square error (RMSE), bias, relative percentage bias, and the 90% coverage probability of parameter estimates. Results indicate that more accurate estimates are associated with ...","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":"10 1","pages":"126-137"},"PeriodicalIF":3.1,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"57293255","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: 8

Discordancy Tests for Outlier Detection in Multi-Item Questionnaires 多项目问卷离群值检测的不一致性检验

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2013-01-01 DOI: 10.1027/1614-2241/A000056

W. Zijlstra, L. V. D. Ark, K. Sijtsma

引用次数: 11

Methodological Advances for Detecting Physiological Synchrony During Dyadic Interactions 在二元相互作用中检测生理同步的方法学进展

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2013-01-01 DOI: 10.1027/1614-2241/A000053

M. McAssey, J. Helm, F. Hsieh, D. Sbarra, E. Ferrer

引用次数: 46

Skewness and Kurtosis in Real Data Samples 真实数据样本中的偏度和峰度