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) | 1 |
Descriptor
| Adjustment (to Environment) | 1 |
| Adoption | 1 |
| Child Development | 1 |
| Correlation | 1 |
| Data | 1 |
| Data Analysis | 1 |
| Fathers | 1 |
| Maximum Likelihood Statistics | 1 |
| Multivariate Analysis | 1 |
| Satisfaction | 1 |
| Structural Equation Models | 1 |
| More ▼ | |
Author
| Blozis, Shelley A. | 1 |
| Ge, Xiaojia | 1 |
| Leve, Leslie D. | 1 |
| Natsuaki, Misaki N. | 1 |
| Neiderhiser, Jenae M. | 1 |
| Reiss, David | 1 |
| Scaramella, Laura V. | 1 |
| Shaw, Daniel S. | 1 |
| Xu, Shu | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Blozis, Shelley A.; Ge, Xiaojia; Xu, Shu; Natsuaki, Misaki N.; Shaw, Daniel S.; Neiderhiser, Jenae M.; Scaramella, Laura V.; Leve, Leslie D.; Reiss, David – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Missing data are common in studies that rely on multiple informant data to evaluate relationships among variables for distinguishable individuals clustered within groups. Estimation of structural equation models using raw data allows for incomplete data, and so all groups can be retained for analysis even if only 1 member of a group contributes…
Descriptors: Data, Structural Equation Models, Correlation, Data Analysis

Peer reviewed
Direct link
