Accommodating a Latent XM Interaction in Statistical Mediation Analysis [0.03%]
统计介体分析中潜在的XM交互作用的处理方法
Oscar Gonzalez,Matthew J Valente
Oscar Gonzalez
Statistical mediation analysis is used in the social sciences and public health to uncover potential mechanisms, known as mediators, by which a treatment led to a change in an outcome. Recently, the estimation of the treatment-by-mediator i...
The Impact of Functional Form Complexity on Model Overfitting for Nonlinear Mixed-Effects Models [0.03%]
非线性混合效应模型中函数形式复杂度对模型过拟合的影响分析
Corissa T Rohloff,Nidhi Kohli,Seungwon Chung
Corissa T Rohloff
Nonlinear mixed-effects models (NLMEMs) allow researchers to model curvilinear patterns of growth, but there is ambiguity as to what functional form the data follow. Often, researchers fit multiple nonlinear functions to data and use model ...
Collinearity Issues in Autoregressive Models with Time-Varying Serially Dependent Covariates [0.03%]
具有时变序列相关协变量的自回归模型中的多重共线性问题
Sigert Ariens,Janne K Adolf,Eva Ceulemans
Sigert Ariens
First-order autoregressive models are popular to assess the temporal dynamics of a univariate process. Researchers often extend these models to include time-varying covariates, such as contextual factors, to investigate how they moderate pr...
A Cautionary Note about Having the Right Mixture Model but Classifying the Wrong People [0.03%]
关于拥有正确的混合模型但错误分类的警示注意
Dakota W Cintron,Eric Loken,D Betsy McCoach
Dakota W Cintron
Mixture models can be used for explanation or individual prediction and classification. In practice, researchers are often tempted to make the class membership manifest by classifying cases according to their class of maximum posterior prob...
Accounting for Heteroskedasticity Resulting from Between-Group Differences in Multilevel Models [0.03%]
考虑来源于组间差异的异方差性的多层次模型的会计处理方法
Francis L Huang,Wolfgang Wiedermann,Bixi Zhang
Francis L Huang
Homogeneity of variance (HOV) is a well-known but often untested assumption in the context of multilevel models (MLMs). However, depending on how large the violation is, how different group sizes are, and the variance pairing, standard erro...
Selecting a Within- or Between-Subject Design for Mediation: Validity, Causality, and Statistical Power [0.03%]
关于因果性、统计功效的中介分析的组内设计与组间设计的选择问题研究
Amanda K Montoya
Amanda K Montoya
Researchers with mediation hypotheses must consider which design to use: within-subject or between-subject? In this paper, I argue that three factors should influence design choice: validity, causality, and statistical power. Threats to val...
On the Relationship between ANOVA Main Effects and Average Treatment Effects [0.03%]
关于方差分析主效应与平均处理效应之间的关系
Linda Graefe,Sonja Hahn,Axel Mayer
Linda Graefe
We adopt a causal inference perspective to shed light into which ANOVA type of sums of squares (SS) should be used for testing main effects and whether main effects should be considered at all in the presence of interactions. We consider ba...
Christy Brown,Jonathan Templin
Christy Brown
Diagnostic classification models (DCMs) are psychometric models for evaluating a student's mastery of the essential skills in a content domain based upon their responses to a set of test items. Currently, diagnostic model and/or Q-matrix mi...
Jason D Rights,Sonya K Sterba
Jason D Rights
Applications of multilevel models (MLMs) with three or more levels have increased alongside expanding software capability and dataset availability. Though researchers often express interest in R-squared measures as effect sizes for MLMs, R-...
Identifying and Estimating Causal Moderation for Treated and Targeted Subgroups [0.03%]
处理组和目标子群的因果调节效应的识别与估计
Nianbo Dong,Benjamin Kelcey,Jessaca Spybrook
Nianbo Dong
Extant literature on moderation effects narrowly focuses on the average moderated treatment effect across the entire sample (AMTE). Missing is the average moderated treatment effect on the treated (AMTT) and other targeted subgroups (AMTS)....