Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Inferences | 2 |
| Monte Carlo Methods | 2 |
| Structural Equation Models | 2 |
| Attribution Theory | 1 |
| Data Collection | 1 |
| Evaluation Methods | 1 |
| Goodness of Fit | 1 |
| Longitudinal Studies | 1 |
| Outcomes of Treatment | 1 |
| Psychological Studies | 1 |
| Sample Size | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 2 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkShin, Tacksoo; Davison, Mark L.; Long, Jeffrey D. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
The purpose of this study is to investigate the effects of missing data techniques in longitudinal studies under diverse conditions. A Monte Carlo simulation examined the performance of 3 missing data methods in latent growth modeling: listwise deletion (LD), maximum likelihood estimation using the expectation and maximization algorithm with a…
Descriptors: Sample Size, Monte Carlo Methods, Structural Equation Models, Data Collection
Jo, Booil – Psychological Methods, 2008
This article links the structural equation modeling (SEM) approach with the principal stratification (PS) approach, both of which have been widely used to study the role of intermediate posttreatment outcomes in randomized experiments. Despite the potential benefit of such integration, the 2 approaches have been developed in parallel with little…
Descriptors: Structural Equation Models, Monte Carlo Methods, Inferences, Outcomes of Treatment
