Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 6 |
Since 2016 (last 10 years) | 21 |
Since 2006 (last 20 years) | 34 |
Descriptor
Computer Software | 34 |
Hierarchical Linear Modeling | 34 |
Statistical Analysis | 16 |
Computation | 11 |
Models | 9 |
Sample Size | 8 |
Correlation | 7 |
Achievement Tests | 6 |
Foreign Countries | 6 |
Monte Carlo Methods | 6 |
Scores | 6 |
More ▼ |
Source
Author
Anthony, Jason L. | 2 |
Clements, Doug H. | 2 |
Dong, Nianbo | 2 |
Foster, Matthew E. | 2 |
Leckie, George | 2 |
Li, Wei | 2 |
Sarama, Julie | 2 |
Williams, Jeffrey M. | 2 |
Amy Kemp-Inman | 1 |
Andrew Gelman | 1 |
Angela I. Preston | 1 |
More ▼ |
Publication Type
Journal Articles | 34 |
Reports - Research | 27 |
Reports - Descriptive | 4 |
Reports - Evaluative | 3 |
Tests/Questionnaires | 1 |
Education Level
Audience
Laws, Policies, & Programs
Elementary and Secondary… | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Meets WWC Standards without Reservations | 1 |
Meets WWC Standards with or without Reservations | 1 |
Steffen Nestler; Sarah Humberg – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Several variants of the autoregressive structural equation model were suggested over the past years, including, for example, the random intercept autoregressive panel model, the latent curve model with structured residuals, and the STARTS model. The present work shows how to place these models into a mixed-effects model framework and how to…
Descriptors: Structural Equation Models, Computer Software, Models, Measurement
Tomek, Sara; Robinson, Cecil – Measurement: Interdisciplinary Research and Perspectives, 2021
Typical longitudinal growth models assume constant functional growth over time. However, there are often conditions where trajectories may not be constant over time. For example, trajectories of psychological behaviors may vary based on a participant's age, or conversely, participants may experience an intervention that causes trajectories to…
Descriptors: Growth Models, Statistical Analysis, Hierarchical Linear Modeling, Computation
Li, Wei; Dong, Nianbo; Maynarad, Rebecca; Spybrook, Jessaca; Kelcey, Ben – Journal of Research on Educational Effectiveness, 2023
Cluster randomized trials (CRTs) are commonly used to evaluate educational interventions, particularly their effectiveness. Recently there has been greater emphasis on using these trials to explore cost-effectiveness. However, methods for establishing the power of cluster randomized cost-effectiveness trials (CRCETs) are limited. This study…
Descriptors: Research Design, Statistical Analysis, Randomized Controlled Trials, Cost Effectiveness
Nagy, Gabriel; Ulitzsch, Esther – Educational and Psychological Measurement, 2022
Disengaged item responses pose a threat to the validity of the results provided by large-scale assessments. Several procedures for identifying disengaged responses on the basis of observed response times have been suggested, and item response theory (IRT) models for response engagement have been proposed. We outline that response time-based…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Predictor Variables, Classification
Koster, Jeremy; Leckie, George; Aven, Brandy – Field Methods, 2020
The multilevel social relations model (SRM) is a commonly used statistical method for the analysis of social networks. In this article and accompanying supplemental materials, we demonstrate the estimation and interpretation of the SRM using Stat-JR software. Multiple software templates permit the analysis of different response types, including…
Descriptors: Statistical Analysis, Computer Software, Hierarchical Linear Modeling, Social Networks
Mang, Julia; Küchenhoff, Helmut; Meinck, Sabine; Prenzel, Manfred – Large-scale Assessments in Education, 2021
Background: Standard methods for analysing data from large-scale assessments (LSA) cannot merely be adopted if hierarchical (or multilevel) regression modelling should be applied. Currently various approaches exist; they all follow generally a design-based model of estimation using the pseudo maximum likelihood method and adjusted weights for the…
Descriptors: Sampling, Hierarchical Linear Modeling, Simulation, Scaling
Luo, Wen; Li, Haoran; Baek, Eunkyeng; Chen, Siqi; Lam, Kwok Hap; Semma, Brandie – Review of Educational Research, 2021
Multilevel modeling (MLM) is a statistical technique for analyzing clustered data. Despite its long history, the technique and accompanying computer programs are rapidly evolving. Given the complexity of multilevel models, it is crucial for researchers to provide complete and transparent descriptions of the data, statistical analyses, and results.…
Descriptors: Hierarchical Linear Modeling, Multivariate Analysis, Prediction, Research Problems
Li, Wei; Dong, Nianbo; Maynard, Rebecca A. – Journal of Educational and Behavioral Statistics, 2020
Cost-effectiveness analysis is a widely used educational evaluation tool. The randomized controlled trials that aim to evaluate the cost-effectiveness of the treatment are commonly referred to as randomized cost-effectiveness trials (RCETs). This study provides methods of power analysis for two-level multisite RCETs. Power computations take…
Descriptors: Statistical Analysis, Cost Effectiveness, Randomized Controlled Trials, Educational Research
Kim, Minjung; Hsu, Hsien-Yuan – Journal of Educational and Behavioral Statistics, 2019
Given the natural hierarchical structure in school-setting data, multilevel modeling (MLM) has been widely employed in education research using a number of different statistical software packages. The purpose of this article is to review a recent feature of Stat-JR, the statistical analysis assistants (SAAs) embedded in Stat-JR (Version 1.0.5),…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Computer Software, Computer Software Evaluation
Papadimitropoulou, Katerina; Stijnen, Theo; Dekkers, Olaf M.; le Cessie, Saskia – Research Synthesis Methods, 2019
The vast majority of meta-analyses uses summary/aggregate data retrieved from published studies in contrast to meta-analysis of individual participant data (IPD). When the outcome is continuous and IPD are available, linear mixed modelling methods can be employed in a one-stage approach. This allows for flexible modelling of within-study…
Descriptors: Meta Analysis, Outcome Measures, Hierarchical Linear Modeling, Sample Size
McCoach, D. Betsy; Rifenbark, Graham G.; Newton, Sarah D.; Li, Xiaoran; Kooken, Janice; Yomtov, Dani; Gambino, Anthony J.; Bellara, Aarti – Journal of Educational and Behavioral Statistics, 2018
This study compared five common multilevel software packages via Monte Carlo simulation: HLM 7, M"plus" 7.4, R (lme4 V1.1-12), Stata 14.1, and SAS 9.4 to determine how the programs differ in estimation accuracy and speed, as well as convergence, when modeling multiple randomly varying slopes of different magnitudes. Simulated data…
Descriptors: Hierarchical Linear Modeling, Computer Software, Comparative Analysis, Monte Carlo Methods
Harel, Daphna; McAllister, Tara – Journal of Speech, Language, and Hearing Research, 2019
Purpose: Research in communication sciences and disorders frequently involves the collection of clusters of observations, such as a series of scores for each individual receiving treatment over the course of an intervention study. However, little discipline-specific guidance is currently available on the subject of building and interpreting…
Descriptors: Communication Disorders, Intervention, Scores, Guidance
Andrew Gelman; Daniel Lee; Jiqiang Guo – Journal of Educational and Behavioral Statistics, 2015
Stan is a free and open-source C++ program that performs Bayesian inference or optimization for arbitrary user-specified models and can be called from the command line, R, Python, Matlab, or Julia and has great promise for fitting large and complex statistical models in many areas of application. We discuss Stan from users' and developers'…
Descriptors: Programming Languages, Bayesian Statistics, Inferences, Monte Carlo Methods
Chen, Kuanchin; Rea, Alan – Journal of Information Systems Education, 2018
Agile methods and approaches such as eXtreme programming (XP) have become the norm for successful organizations not only in the software industry but also for businesses seeking to improve internal software processes. Pair programming in some form is touted as a major functionality and productivity improvement. However, numerous studies show that…
Descriptors: Computer Software, Programming, Coding, Information Systems
McNeish, Daniel M. – Journal of Educational and Behavioral Statistics, 2016
Mixed-effects models (MEMs) and latent growth models (LGMs) are often considered interchangeable save the discipline-specific nomenclature. Software implementations of these models, however, are not interchangeable, particularly with small sample sizes. Restricted maximum likelihood estimation that mitigates small sample bias in MEMs has not been…
Descriptors: Models, Statistical Analysis, Hierarchical Linear Modeling, Sample Size