Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 3 |
Descriptor
| Monte Carlo Methods | 4 |
| Research Design | 4 |
| Structural Equation Models | 4 |
| Correlation | 2 |
| Error of Measurement | 2 |
| Statistical Bias | 2 |
| Data Analysis | 1 |
| Effect Size | 1 |
| Error Correction | 1 |
| Investigations | 1 |
| Least Squares Statistics | 1 |
| More ▼ | |
Source
| Journal of Experimental… | 1 |
| Multivariate Behavioral… | 1 |
| ProQuest LLC | 1 |
| Structural Equation Modeling:… | 1 |
Author
| Ayse Busra Ceviren | 1 |
| Revilla, Melanie | 1 |
| Saris, Willem E. | 1 |
| Skrondal, Anders | 1 |
| Thompson, Bruce | 1 |
| Wang, Zhongmiao | 1 |
Publication Type
| Journal Articles | 3 |
| Dissertations/Theses -… | 1 |
| Information Analyses | 1 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
Audience
| Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Ayse Busra Ceviren – ProQuest LLC, 2024
Latent change score (LCS) models are a powerful class of structural equation modeling that allows researchers to work with latent difference scores that minimize measurement error. LCS models define change as a function of prior status, which makes it well-suited for modeling developmental theories or processes. In LCS models, like other latent…
Descriptors: Structural Equation Models, Error of Measurement, Statistical Bias, Monte Carlo Methods
Revilla, Melanie; Saris, Willem E. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Saris, Satorra, and Coenders (2004) proposed a new approach to estimate the quality of survey questions, combining the advantages of 2 existing approaches: the multitrait-multimethod (MTMM) and the split-ballot (SB) ones. Implemented in practice, this new approach led to frequent problems of nonconvergence and improper solutions. This article uses…
Descriptors: Multitrait Multimethod Techniques, Surveys, Monte Carlo Methods, Correlation
Peer reviewedSkrondal, Anders – Multivariate Behavioral Research, 2000
Discusses the design and analysis of Monte Carlo experiments, with special reference to structural equation modeling. Outlines three fundamental challenges of Monte Carlo approaches and suggests some alternative procedures that challenge conventional wisdom. Asserts that comprehensive Monte Carlo studies can be done with a personal computer if the…
Descriptors: Monte Carlo Methods, Research Design, Research Methodology, Structural Equation Models
Wang, Zhongmiao; Thompson, Bruce – Journal of Experimental Education, 2007
In this study the authors investigated the use of 5 (i.e., Claudy, Ezekiel, Olkin-Pratt, Pratt, and Smith) R[squared] correction formulas with the Pearson r[squared]. The authors estimated adjustment bias and precision under 6 x 3 x 6 conditions (i.e., population [rho] values of 0.0, 0.1, 0.3, 0.5, 0.7, and 0.9; population shapes normal, skewness…
Descriptors: Effect Size, Correlation, Mathematical Formulas, Monte Carlo Methods

Direct link
