Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 6 |
Since 2006 (last 20 years) | 6 |
Descriptor
Classification | 6 |
Growth Models | 6 |
Accuracy | 3 |
Goodness of Fit | 2 |
Grade 3 | 2 |
Grade 4 | 2 |
Grade 5 | 2 |
Grade 6 | 2 |
Longitudinal Studies | 2 |
Posttraumatic Stress Disorder | 2 |
Sample Size | 2 |
More ▼ |
Source
Grantee Submission | 3 |
Applied Measurement in… | 1 |
Educational and Psychological… | 1 |
Journal of Special Education | 1 |
Author
Daniel J. Bauer | 1 |
Daniel McNeish | 1 |
Elliott, Stephen N. | 1 |
Guerra-Peña, Kiero | 1 |
Harring, Jeffrey R. | 1 |
Jeffrey R. Harring | 1 |
Lin, Qiao | 1 |
McNeish, Daniel | 1 |
Nese, Joseph F. T. | 1 |
Park, Yoon Soo | 1 |
Schulte, Ann C. | 1 |
More ▼ |
Publication Type
Reports - Research | 6 |
Journal Articles | 4 |
Education Level
Early Childhood Education | 2 |
Elementary Education | 2 |
Grade 3 | 2 |
Grade 4 | 2 |
Grade 5 | 2 |
Grade 6 | 2 |
Intermediate Grades | 2 |
Middle Schools | 2 |
Primary Education | 2 |
Grade 7 | 1 |
Grade 8 | 1 |
More ▼ |
Audience
Location
Oregon | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Daniel McNeish; Jeffrey R. Harring; Daniel J. Bauer – Grantee Submission, 2022
Growth mixture models (GMMs) are a popular method to identify latent classes of growth trajectories. One shortcoming of GMMs is nonconvergence, which often leads researchers to apply covariance equality constraints to simplify estimation, though this may be a dubious assumption. Alternative model specifications have been proposed to reduce…
Descriptors: Growth Models, Classification, Accuracy, Sample Size
McNeish, Daniel; Harring, Jeffrey R. – Grantee Submission, 2021
Growth mixture models (GMMs) are a popular method to uncover heterogeneity in growth trajectories. Harnessing the power of GMMs in applications is difficult given the prevalence of nonconvergence when fitting GMMs to empirical data. GMMs are rooted in the random effect tradition and nonconvergence often leads researchers to modify their intended…
Descriptors: Growth Models, Classification, Posttraumatic Stress Disorder, Sample Size
Lin, Qiao; Xing, Kuan; Park, Yoon Soo – Grantee Submission, 2020
During the past decade, cognitive diagnostic models (CDMs) have become prevalent in providing diagnostic information for learning. Cognitive diagnostic models have generally focused on single cross-sectional time points. However, longitudinal assessments have been commonly used in education to assess students' learning progress as well as…
Descriptors: Cognitive Measurement, Growth Models, Educational Diagnosis, Longitudinal Studies
Wells, Craig S.; Sireci, Stephen G. – Applied Measurement in Education, 2020
Student growth percentiles (SGPs) are currently used by several states and school districts to provide information about individual students as well as to evaluate teachers, schools, and school districts. For SGPs to be defensible for these purposes, they should be reliable. In this study, we examine the amount of systematic and random error in…
Descriptors: Growth Models, Reliability, Scores, Error Patterns
Guerra-Peña, Kiero; Steinley, Douglas – Educational and Psychological Measurement, 2016
Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…
Descriptors: Growth Models, Bayesian Statistics, Sampling, Statistical Inference
Nese, Joseph F. T.; Stevens, Joseph J.; Schulte, Ann C.; Tindal, Gerald; Elliott, Stephen N. – Journal of Special Education, 2017
Our purpose was to examine different approaches to modeling the time-varying nature of exceptionality classification. Using longitudinal data from one state's mathematics achievement test for 28,829 students in Grades 3 to 8, we describe the reclassification rate within special education and between general and special education, and compare four…
Descriptors: Classification, Achievement Gains, Special Needs Students, Mathematics Achievement