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20132019
most citedThe Expected Parameter Change (EPC) for Local Dependence Assessment in Binary Data Latent Class Models

9 citations · 16 across the 5 of their papers we have counts for

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6 papers · 1 filter

stat.ME20193 cited

A Permutation Test for Assessing the Presence of Individual Differences in Treatment Effects

Chi Chang, Thomas Jaki, Muhammad Saad Sadiq +7

One size fits all approaches to medicine have become a thing of the past as the understanding of individual differences grows. The paper introduces a test for the presence of heter…

stat.ME20191 cited

Rank-deficiencies in a reduced information latent variable model

Daniel L. Oberski

Latent variable models are well-known to suffer from rank deficiencies, causing problems with convergence and stability. Such problems are compounded in the "reduced-group split-ba…

stat.ME2019

Structural Equation Models as Computation Graphs

Erik-Jan van Kesteren, Daniel L. Oberski

Structural equation modeling (SEM) is a popular tool in the social and behavioural sciences, where it is being applied to ever more complex data types. The high-dimensional data pr…

stat.ME2018

Exploratory Mediation Analysis with Many Potential Mediators

Erik-Jan van Kesteren, Daniel L. Oberski

Social and behavioral scientists are increasingly employing technologies such as fMRI, smartphones, and gene sequencing, which yield 'high-dimensional' datasets with more columns t…

stat.ME20189 cited

The Expected Parameter Change (EPC) for Local Dependence Assessment in Binary Data Latent Class Models

Daniel L. Oberski, Jeroen K. Vermunt

Binary data latent class models crucially assume local independence, violations of which can seriously bias the results. We present two tools for monitoring local dependence in bin…

stat.ME2013

Individual Differences in Structural Equation Model Parameters

Daniel Leonard Oberski

Individuals may differ in their parameter values. This article discusses a three-step method of studying such differences by calculating and then modeling "individual parameter con…