General Linear Model Journal最新文献

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Correction for Attenuation of the Multiple Correlation Coefficient Given Non-Independent Error Scores 给定非独立误差分数的多重相关系数衰减的校正
General Linear Model Journal Pub Date : 1900-01-01 DOI: 10.31523/glmj.046001.003
Brenna Curley, Debra Wetcher-Hendricks
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引用次数: 0
Testing Individual vs Group Mean Differences in Social Science Research 检验社会科学研究中的个体与群体平均差异
General Linear Model Journal Pub Date : 1900-01-01 DOI: 10.31523/glmj.046001.004
R. Schumacker, Lauren F. Holmes
{"title":"Testing Individual vs Group Mean Differences in Social Science Research","authors":"R. Schumacker, Lauren F. Holmes","doi":"10.31523/glmj.046001.004","DOIUrl":"https://doi.org/10.31523/glmj.046001.004","url":null,"abstract":"A true experimental design requires random selection and random assignment of subjects to control and experimental groups. A hypothesized statistically significant mean difference in the dependent variable between these two groups is typically specified. This methodology is also referred to as a randomized clinical trial when testing for group differences. Individual differences are generally not considered, rather the focus is on the average control group and experimental group difference. This article offers another approach that illustrates testing for individual differences over time. h e true experimental design conducts a test of control group versus experimental group average dependent variable difference using analysis of variance statistical tests (Maxwell & Delaney, 2004). This methodology is also referred to as a randomized clinical trial when testing for group mean differences (Machin & Fayers, 2010). Oftentimes a true experimental design is not possible, so the researcher uses a quasi-experimental design. A quasi-experimental design uses a comparison group rather than a control group. The typical quasi-experimental design considers a pre-test measure, followed by treatment, and then a similar post-test measure for the subjects in the comparison group and the experimental group. In the statistical analysis, individual post-test measure differences are adjusted for individual pre-test measure differences to control for bias. This adjustment is referred to as analysis of covariance and expressed in the general linear model as: are","PeriodicalId":259786,"journal":{"name":"General Linear Model Journal","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116236046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Comparison of Clustering Methods when Group Sizes are Unequal, Outliers are Present, and in the Presence of Noise Variables 分组大小不等、存在异常值和存在噪声变量时聚类方法的比较
General Linear Model Journal Pub Date : 1900-01-01 DOI: 10.31523/glmj.045001.003
W. H. Finch
{"title":"A Comparison of Clustering Methods when Group Sizes are Unequal, Outliers are Present, and in the Presence of Noise Variables","authors":"W. H. Finch","doi":"10.31523/glmj.045001.003","DOIUrl":"https://doi.org/10.31523/glmj.045001.003","url":null,"abstract":"","PeriodicalId":259786,"journal":{"name":"General Linear Model Journal","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115172482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
SEM Estimation in the Context of Small Samples: Comparison of Latent Variable Models, Single Indicator, Regularized 2-Stage Least Squares and Observed Variable Models 小样本背景下的SEM估计:潜在变量模型、单指标、正则化2阶段最小二乘和观测变量模型的比较
General Linear Model Journal Pub Date : 1900-01-01 DOI: 10.31523/glmj.046001.001
W. H. Finch
{"title":"SEM Estimation in the Context of Small Samples: Comparison of Latent Variable Models, Single Indicator, Regularized 2-Stage Least Squares and Observed Variable Models","authors":"W. H. Finch","doi":"10.31523/glmj.046001.001","DOIUrl":"https://doi.org/10.31523/glmj.046001.001","url":null,"abstract":"","PeriodicalId":259786,"journal":{"name":"General Linear Model Journal","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123569417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sample Size for Parallel Analysis and Not-So-Common Criteria for Dimensions in Factor Analysis: Modifying the Eigenvalue > 1 Kaiser Rule 平行分析的样本量和因子分析中不常见的维度标准:修改特征值> 1 Kaiser规则
General Linear Model Journal Pub Date : 1900-01-01 DOI: 10.31523/glmj.046001.002
Pornchanok Ruengvirayudh, Gordon Brooks
{"title":"Sample Size for Parallel Analysis and Not-So-Common Criteria for Dimensions in Factor Analysis: Modifying the Eigenvalue > 1 Kaiser Rule","authors":"Pornchanok Ruengvirayudh, Gordon Brooks","doi":"10.31523/glmj.046001.002","DOIUrl":"https://doi.org/10.31523/glmj.046001.002","url":null,"abstract":"","PeriodicalId":259786,"journal":{"name":"General Linear Model Journal","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131695201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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