Sample size planning for composite reliability coefficients: accuracy in parameter estimation via narrow confidence intervals [0.03%]
参数估计中的窄置信区间：组合可靠性系数的样本量规划
Leann Terry,Ken Kelley
Leann Terry
Composite measures play an important role in psychology and related disciplines. Composite measures almost always have error. Correspondingly, it is important to understand the reliability of the scores from any particular composite measure...
Accuracy in parameter estimation for ANCOVA and ANOVA contrasts: sample size planning via narrow confidence intervals [0.03%]
通过窄置信区间进行方差分析和协方差分析检验的参数估计准确性：样本量的确定
Keke Lai,Ken Kelley
Keke Lai
Contrasts of means are often of interest because they describe the effect size among multiple treatments. High-quality inference of population effect sizes can be achieved through narrow confidence intervals (CIs). Given the close relation ...
Using SAS PROC TCALIS for multigroup structural equation modelling with mean structures [0.03%]
使用SAS的TCALIS过程进行均值结构的多组结构方程模型分析
Fei Gu,Wei Wu
Fei Gu
Multigroup structural equation modelling (SEM) is a technique frequently used to evaluate measurement invariance in social and behavioural science research. Before version 9.2, SAS was incapable of handling multigroup SEM. However, this lim...
Constructing bootstrap confidence intervals for principal component loadings in the presence of missing data: a multiple-imputation approach [0.03%]
多重插补法在缺失数据情况下用于主成分载荷的自助置信区间构建的方法研究
Joost R van Ginkel,Henk A L Kiers
Joost R van Ginkel
Earlier research has shown that bootstrap confidence intervals from principal component loadings give a good coverage of the population loadings. However, this only applies to complete data. When data are incomplete, missing data have to be...
Plausible measurement analogies to some psychometric models of test performance [0.03%]
几种心理测量模型的测验表现的可能的度量类比关系
Andrew Kyngdon
Andrew Kyngdon
Psychometricians hypothesize that cognitive abilities such as reading, writing and spelling are measurable. However, they prefer to model item response probabilities than to study the internal structure of cognitive attributes. The theory o...
Clarifying the role of mean centring in multicollinearity of interaction effects [0.03%]
均值中心化在交互效应共线性中的作用澄清
Gwowen Shieh
Gwowen Shieh
Moderated multiple regression (MMR) is frequently employed to analyse interaction effects between continuous predictor variables. The procedure of mean centring is commonly recommended to mitigate the potential threat of multicollinearity b...
Scale validity evaluation with congeneric measures in hierarchical designs [0.03%]
分层设计中的同质测量尺度有效性评价
Tenko Raykov
Tenko Raykov
A procedure for validity estimation of multi-component measuring instruments in hierarchical designs is outlined. The method is developed within the framework of the popular latent variable modelling methodology. The approach is readily app...
A closer look at the effect of preliminary goodness-of-fit testing for normality for the one-sample t-test [0.03%]
单样本t检验中用于考察正态性前提的拟合优度检验效应的研究
Justine Rochon,Meinhard Kieser
Justine Rochon
Student's one-sample t-test is a commonly used method when inference about the population mean is made. As advocated in textbooks and articles, the assumption of normality is often checked by a preliminary goodness-of-fit (GOF) test. In a p...
A simple and effective decision rule for choosing a significance test to protect against non-normality [0.03%]
一个简单的有效决策规则，用于选择显著性检验以防止非正态性
Donald W Zimmerman
Donald W Zimmerman
There is no formal and generally accepted procedure for choosing an appropriate significance test for sample data when the assumption of normality is doubtful. Various tests of normality that have been proposed over the years have been foun...
Bootstrap standard error and confidence intervals for the correlations corrected for indirect range restriction [0.03%]
关于间接范围限制校正相关性的bootstrap标准误和置信区间
Johnson Ching-Hong Li,Wai Chan,Ying Cui
Johnson Ching-Hong Li
The standard Pearson correlation coefficient, r, is a biased estimator of the population correlation coefficient, ρ(XY) , when predictor X and criterion Y are indirectly range-restricted by a third variable Z (or S). Two correction algorit...