betaDelta and betaSandwich: Confidence Intervals for Standardized Regression Coefficients in R [0.03%]
BetaDelta和betaSandwich：R中的标准回归系数的置信区间
Ivan Jacob Agaloos Pesigan,Rong Wei Sun,Shu Fai Cheung
Ivan Jacob Agaloos Pesigan
The multivariate delta method was used by Yuan and Chan to estimate standard errors and confidence intervals for standardized regression coefficients. Jones and Waller extended the earlier work to situations where data are nonnormal by util...
Pay Attention to the Ignorable Missing Data Mechanisms! An Exploration of Their Impact on the Efficiency of Regression Coefficients [0.03%]
重视可忽略的缺失数据机制！对其对回归系数效率的影响进行探索
Lihan Chen,Victoria Savalei,Mijke Rhemtulla
Lihan Chen
The use of modern missing data techniques has become more prevalent with their increasing accessibility in statistical software. These techniques focus on handling data that are missing at random (MAR). Although all MAR mechanisms are routi...
Marcos Jiménez,Francisco J Abad,Eduardo Garcia-Garzon et al.
Marcos Jiménez et al.
Exploratory bi-factor analysis (EBFA) is a very popular approach to estimate models where specific factors are concomitant to a single, general dimension. However, the models typically encountered in fields like personality, intelligence, a...
On the Common but Problematic Specification of Conflated Random Slopes in Multilevel Models [0.03%]
混杂随机斜率在多层模型中的常见但有问题的规范
Jason D Rights,Sonya K Sterba
Jason D Rights
For multilevel models (MLMs) with fixed slopes, it has been widely recognized that a level-1 variable can have distinct between-cluster and within-cluster fixed effects, and that failing to disaggregate these effects yields a conflated, uni...
CLC Estimator: A Tool for Latent Construct Estimation via Congeneric Approaches in Survey Research [0.03%]
CLC估算器：一种通过同构方法进行问卷调查研究的潜在结构估计工具
Giacomo Marzi,Marco Balzano,Leonardo Egidi et al.
Giacomo Marzi et al.
This article proposes the Shiny app 'CLC Estimator' -Congeneric Latent Construct Estimator- to address the problem of estimating latent unidimensional constructs via congeneric approaches. While congeneric approaches provide more rigorous r...
Which is Better for Individual Participant Data Meta-Analysis of Zero-Inflated Count Outcomes, One-Step or Two-Step Analysis? A Simulation Study [0.03%]
一步法与两步法在零膨胀计数结局个体患者数据荟萃分析中哪个更好？一项模拟研究
David Huh,Scott A Baldwin,Zhengyang Zhou et al.
David Huh et al.
Meta-analysis using individual participant data (IPD) is an important methodology in intervention research because it (a) increases accuracy and precision of estimates, (b) allows researchers to investigate mediators and moderators of treat...
Fitting Bayesian Stochastic Differential Equation Models with Mixed Effects through a Filtering Approach [0.03%]
基于滤波的混合效应贝叶斯随机微分方程模型拟合方法研究
Meng Chen,Sy-Miin Chow,Zita Oravecz et al.
Meng Chen et al.
Recent advances in technology contribute to a fast-growing number of studies utilizing intensive longitudinal data, and call for more flexible methods to address the demands that come with them. One issue that arises from collecting longitu...
Disentangling Different Aspects of Change in Tests with the D-Diffusion Model [0.03%]
利用D-扩散模型解开测验中变化的不同方面
Jochen Ranger,Anett Wolgast,Sören Much et al.
Jochen Ranger et al.
Diffusion-based item response theory models are measurement models that link parameters of the diffusion model (drift rate, boundary separation) to latent traits of test takers. Similar to standard latent trait models, they assume the invar...
Generalizability of Dynamic Fit Index, Equivalence Testing, and Hu & Bentler Cutoffs for Evaluating Fit in Factor Analysis [0.03%]
用于因素分析拟合评估的动态适应指数、等价检验及Hu和Bentler临界值的普适性
Daniel McNeish
Daniel McNeish
Factor analysis is often used to model scales created to measure latent constructs, and internal structure validity evidence is commonly assessed with indices like RMSEA, and CFI. These indices are essentially effect size measures and defin...
dynamic : An R Package for Deriving Dynamic Fit Index Cutoffs for Factor Analysis [0.03%]
动态拟合指数临界值的R软件实现动态包(dynamic)
Melissa G Wolf,Daniel McNeish
Melissa G Wolf
To evaluate the fit of a confirmatory factor analysis model, researchers often rely on fit indices such as SRMR, RMSEA, and CFI. These indices are frequently compared to benchmark values of .08, .06, and .96, respectively, established by Hu...