A comparison of multiple imputation strategies for handling missing data in multi‐item scales: guidance for longitudinal studies
R Mainzer, J Apajee, CD Nguyen… - Statistics in …, 2021 - Wiley Online Library
Medical research often involves using multi‐item scales to assess individual characteristics,
disease severity, and other health‐related outcomes. It is common to observe missing data …
disease severity, and other health‐related outcomes. It is common to observe missing data …
Multiple Imputation When Variables Exceed Observations: An Overview of Challenges and Solutions
Missing data are a prevalent problem in psychological research that can reduce statistical
power and bias parameter estimates. These problems can be mostly resolved with multiple …
power and bias parameter estimates. These problems can be mostly resolved with multiple …
A factored regression model for composite scores with item-level missing data.
Composite scores are an exceptionally important psychometric tool for behavioral science
research applications. A prototypical example occurs with self-report data, where …
research applications. A prototypical example occurs with self-report data, where …
Multiple imputation of missing data in large studies with many variables: A fully conditional specification approach using partial least squares.
S Grund, O Lüdtke, A Robitzsch - Psychological Methods, 2024 - psycnet.apa.org
Multiple imputation (MI) is one of the most popular methods for handling missing data in
psychological research. However, many imputation approaches are poorly equipped to …
psychological research. However, many imputation approaches are poorly equipped to …
Addressing Missing Data in Latent Class Analysis When Using a Three-Step Estimation Approach
This study specifically focuses on addressing the challenges related to employing missing
data techniques when estimating a conditional Latent Class Analysis (LCA) model. In the …
data techniques when estimating a conditional Latent Class Analysis (LCA) model. In the …
Assessing alternative imputation strategies for infrequently missing items on multi-item scales
P Hayati Rezvan, WS Comulada… - … in Statistics: Case …, 2022 - Taylor & Francis
Health-science researchers often measure psychological constructs using multi-item scales
and encounter missing items on some participants. Multiple imputation (MI) has emerged as …
and encounter missing items on some participants. Multiple imputation (MI) has emerged as …
[图书][B] Addressing Common Covariate Modeling Issues in Latent Class Analysis Models
MA Visser - 2022 - search.proquest.com
This dissertation is organized into two studies investigating common modeling issues that
occur when including a covariate in a latent class analysis (LCA) model. When estimating a …
occur when including a covariate in a latent class analysis (LCA) model. When estimating a …