Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 4 |
Since 2006 (last 20 years) | 4 |
Descriptor
Monte Carlo Methods | 7 |
Multivariate Analysis | 7 |
Probability | 7 |
Simulation | 3 |
Computation | 2 |
Data Analysis | 2 |
Error of Measurement | 2 |
Maximum Likelihood Statistics | 2 |
Power (Statistics) | 2 |
Research Methodology | 2 |
Research Problems | 2 |
More ▼ |
Source
Sociological Methods &… | 2 |
Journal of Experimental… | 1 |
Mid-Western Educational… | 1 |
Multivariate Behavioral… | 1 |
Practical Assessment,… | 1 |
Author
Barcikowski, Robert S. | 2 |
Blackwell, Matthew | 2 |
Elliott, Ronald S. | 2 |
Honaker, James | 2 |
King, Gary | 2 |
Alamri, Abeer | 1 |
Chun, Seokjoon | 1 |
Collier, Zachary K. | 1 |
Everitt, B. S. | 1 |
Joo, Seang-Hwane | 1 |
Kim, Eunsook | 1 |
More ▼ |
Publication Type
Journal Articles | 6 |
Reports - Research | 6 |
Reports - Evaluative | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Audience
Researchers | 3 |
Location
Laws, Policies, & Programs
Assessments and Surveys
Trends in International… | 1 |
What Works Clearinghouse Rating
Collier, Zachary K.; Zhang, Haobai; Liu, Liu – Practical Assessment, Research & Evaluation, 2022
Although educational research and evaluation generally occur in multilevel settings, many analyses ignore cluster effects. Neglecting the nature of data from educational settings, especially in non-randomized experiments, can result in biased estimates with long-term consequences. Our manuscript improves the availability and understanding of…
Descriptors: Artificial Intelligence, Probability, Scores, Educational Research
Wang, Yan; Kim, Eunsook; Joo, Seang-Hwane; Chun, Seokjoon; Alamri, Abeer; Lee, Philseok; Stark, Stephen – Journal of Experimental Education, 2022
Multilevel latent class analysis (MLCA) has been increasingly used to investigate unobserved population heterogeneity while taking into account data dependency. Nonparametric MLCA has gained much popularity due to the advantage of classifying both individuals and clusters into latent classes. This study demonstrated the need to relax the…
Descriptors: Nonparametric Statistics, Hierarchical Linear Modeling, Monte Carlo Methods, Simulation
Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…
Descriptors: Error of Measurement, Monte Carlo Methods, Data Collection, Simulation
Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…
Descriptors: Error of Measurement, Correlation, Simulation, Bayesian Statistics

Everitt, B. S. – Multivariate Behavioral Research, 1981
Results show that the proposed sampling distribution of the test appears to be appropriate only for sample sizes above 50, and for data where the sample size is 10 times the number of variables. For such cases the power of the test is found to be fairly low. (Author/RL)
Descriptors: Mathematical Formulas, Maximum Likelihood Statistics, Monte Carlo Methods, Multivariate Analysis

Elliott, Ronald S.; Barcikowski, Robert S. – Mid-Western Educational Researcher, 1994
In multivariate analysis of variance studies with small numbers of subjects (15 or less) per treatment level, probability values reported by the commercial statistical packages SAS and SPSS are conservative for F approximations based on Pillai's trace and liberal for F approximations based on the Hotelling-Lawley trace. Discusses results in terms…
Descriptors: Monte Carlo Methods, Multivariate Analysis, Power (Statistics), Probability
Elliott, Ronald S.; Barcikowski, Robert S. – 1993
This Monte Carlo study examines whether, given various numbers of variables, treatments, and sample sizes, in a one-way multivariate analysis of variance, Type I error rates of the test approximations provided by the BMDP program, the Statistical Analysis System (SAS), and the Statistical Package for the Social Sciences (SPSS) for Roy's largest…
Descriptors: Analysis of Variance, Computer Simulation, Estimation (Mathematics), Monte Carlo Methods