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

The Impact of the Number of Dyads on Estimation of Dyadic Data Analysis Using Multilevel Modeling 二元数对多层次模型二元数据分析估计的影响

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2016-04-01 DOI: 10.1027/1614-2241/A000105

H. Du, Lijuan Wang

引用次数: 23

Modeling Likert scale outcomes with trend-proportional odds with and without cluster data. 建模李克特量表结果与趋势比例的优势，有无集群数据。

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2016-04-01 DOI: 10.1027/1614-2241/a000106

Ana W Capuano, Jeffrey D Dawson, Marizen R Ramirez, Robert S Wilson, Lisa L Barnes, R William Fields

{"title":"Modeling Likert scale outcomes with trend-proportional odds with and without cluster data.","authors":"Ana W Capuano, Jeffrey D Dawson, Marizen R Ramirez, Robert S Wilson, Lisa L Barnes, R William Fields","doi":"10.1027/1614-2241/a000106","DOIUrl":"https://doi.org/10.1027/1614-2241/a000106","url":null,"abstract":"<p><p>Likert scales are commonly used in epidemiological studies employing surveys. In this tutorial we demonstrate how the proportional odds model and the trend odds model can be applied simultaneously to data measured in Likert scales, allowing for random cluster effects. We use two datasets as examples: an epidemiological study on aging and cognition among community-dwelling Black persons, and a clustered large survey data from 28,882 students in 81 middle schools. The first example models the Likert outcome from the question: \"People act as if they think you are dishonest\". The trend-proportional odds model indicates that Black men have higher odds than Black women of reporting being perceived dishonest. The second example models the Likert outcome from the question: \"How often have you been beaten up at school?\". The trend-proportional odds model indicates that children with disability have a higher odds of severe violence than other children. For both examples, the cumulative odds ratio increases by more than 60% at the higher Likert levels.</p>","PeriodicalId":18476,"journal":{"name":"Methodology: European Journal of Research Methods for The Behavioral and Social Sciences","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10426790/pdf/nihms-1914107.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10068888","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}

引用次数: 7

Methodological Challenges of Mixed Methods Intervention Evaluations 混合方法干预评估的方法学挑战

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2015-12-23 DOI: 10.1027/1614-2241/A000101

H. Boeije, S. Drabble, A. O’Cathain

引用次数: 15

Methodological Issues in Categorical Data Analysis 分类数据分析中的方法问题

IF 3.1 3区心理学

Methodology: European Journal of Research Methods for The Behavioral and Social Sciences Pub Date : 2015-12-23 DOI: 10.1027/1614-2241/A000102

J. Hagenaars

引用次数: 5

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":null,"pages":null},"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

Validity Concerns with Multiplying Ordinal Items Defined by Binned Counts: An Application to a Quantity-Frequency Measure of Alcohol Use. 用分类计数定义的数项相乘的效度问题:酒精使用数量-频率测量的应用。

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/a000081

James S McGinley, Patrick J Curran

引用次数: 11

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":null,"pages":null},"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