Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 10 |
Descriptor
Comparative Analysis | 10 |
Goodness of Fit | 10 |
Hierarchical Linear Modeling | 10 |
Statistical Analysis | 4 |
Bayesian Statistics | 3 |
Computation | 3 |
Academic Achievement | 2 |
Correlation | 2 |
Grade 9 | 2 |
Item Response Theory | 2 |
Longitudinal Studies | 2 |
More ▼ |
Source
Journal of Educational and… | 2 |
ProQuest LLC | 2 |
Applied Measurement in… | 1 |
International Journal of… | 1 |
Journal of Experimental… | 1 |
Journal of Psychoeducational… | 1 |
Practical Assessment,… | 1 |
Psychometrika | 1 |
Author
Luo, Wen | 2 |
Allen, Jeff | 1 |
Azen, Razia | 1 |
Baek, Eunkyeng | 1 |
Boedeker, Peter | 1 |
Brown, Gregory G. | 1 |
Canivez, Gary L. | 1 |
Cui, Ying | 1 |
Duong, Thao | 1 |
Hedges, Larry V. | 1 |
Henri, Maria | 1 |
More ▼ |
Publication Type
Journal Articles | 8 |
Reports - Research | 7 |
Dissertations/Theses -… | 2 |
Information Analyses | 1 |
Opinion Papers | 1 |
Reports - Evaluative | 1 |
Education Level
Elementary Education | 2 |
Grade 9 | 2 |
High Schools | 2 |
Junior High Schools | 2 |
Middle Schools | 2 |
Secondary Education | 2 |
Early Childhood Education | 1 |
Grade 1 | 1 |
Grade 10 | 1 |
Grade 11 | 1 |
Kindergarten | 1 |
More ▼ |
Audience
Location
Canada | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Early Childhood Longitudinal… | 1 |
Wechsler Adult Intelligence… | 1 |
Wechsler Intelligence Scale… | 1 |
What Works Clearinghouse Rating
Baek, Eunkyeng; Luo, Wen; Henri, Maria – Journal of Experimental Education, 2022
It is common to include multiple dependent variables (DVs) in single-case experimental design (SCED) meta-analyses. However, statistical issues associated with multiple DVs in the multilevel modeling approach (i.e., possible dependency of error, heterogeneous treatment effects, and heterogeneous error structures) have not been fully investigated.…
Descriptors: Meta Analysis, Hierarchical Linear Modeling, Comparative Analysis, Statistical Inference
Boedeker, Peter – Practical Assessment, Research & Evaluation, 2017
Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…
Descriptors: Hierarchical Linear Modeling, Maximum Likelihood Statistics, Bayesian Statistics, Computation
Zhu, Xiaoshu – ProQuest LLC, 2013
The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…
Descriptors: Item Response Theory, Models, Comparative Analysis, Goodness of Fit
Allen, Jeff – Applied Measurement in Education, 2017
Using a sample of schools testing annually in grades 9-11 with a vertically linked series of assessments, a latent growth curve model is used to model test scores with student intercepts and slopes nested within school. Missed assessments can occur because of student mobility, student dropout, absenteeism, and other reasons. Missing data…
Descriptors: Achievement Gains, Academic Achievement, Growth Models, Scores
Pustejovsky, James E.; Hedges, Larry V.; Shadish, William R. – Journal of Educational and Behavioral Statistics, 2014
In single-case research, the multiple baseline design is a widely used approach for evaluating the effects of interventions on individuals. Multiple baseline designs involve repeated measurement of outcomes over time and the controlled introduction of a treatment at different times for different individuals. This article outlines a general…
Descriptors: Hierarchical Linear Modeling, Effect Size, Maximum Likelihood Statistics, Computation
Zhou, Bo; Konstorum, Anna; Duong, Thao; Tieu, Kinh H.; Wells, William M.; Brown, Gregory G.; Stern, Hal S.; Shahbaba, Babak – Psychometrika, 2013
We propose a hierarchical Bayesian model for analyzing multi-site experimental fMRI studies. Our method takes the hierarchical structure of the data (subjects are nested within sites, and there are multiple observations per subject) into account and allows for modeling between-site variation. Using posterior predictive model checking and model…
Descriptors: Brain, Diagnostic Tests, Bayesian Statistics, Hierarchical Linear Modeling
Canivez, Gary L.; Kush, Joseph C. – Journal of Psychoeducational Assessment, 2013
Weiss, Keith, Zhu, and Chen (2013a) and Weiss, Keith, Zhu, and Chen (2013b), this issue, report examinations of the factor structure of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV), respectively; comparing Wechsler Hierarchical Model (W-HM) and…
Descriptors: Intelligence Tests, Factor Structure, Comparative Analysis, Arithmetic
Cui, Ying; Mousavi, Amin – International Journal of Testing, 2015
The current study applied the person-fit statistic, l[subscript z], to data from a Canadian provincial achievement test to explore the usefulness of conducting person-fit analysis on large-scale assessments. Item parameter estimates were compared before and after the misfitting student responses, as identified by l[subscript z], were removed. The…
Descriptors: Measurement, Achievement Tests, Comparative Analysis, Test Items
Luo, Wen; Azen, Razia – Journal of Educational and Behavioral Statistics, 2013
Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…
Descriptors: Predictor Variables, Hierarchical Linear Modeling, Statistical Analysis, Regression (Statistics)
Preston, Andrew James – ProQuest LLC, 2013
Response to intervention (RtI) is an approach to assist students with learning difficulties. There is limited research into the effectiveness of RtI within rural school districts. To address that gap, this quantitative, experimental study tested the theory of RtI, comparing the tier of intervention to oral reading fluency, controlling for…
Descriptors: Oral Reading, Reading Fluency, Reading Improvement, Hierarchical Linear Modeling