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Lu Qin; Shishun Zhao; Wenlai Guo; Tiejun Tong; Ke Yang – Research Synthesis Methods, 2024
The application of network meta-analysis is becoming increasingly widespread, and for a successful implementation, it requires that the direct comparison result and the indirect comparison result should be consistent. Because of this, a proper detection of inconsistency is often a key issue in network meta-analysis as whether the results can be…
Descriptors: Meta Analysis, Network Analysis, Bayesian Statistics, Comparative Analysis
Skinner, Christopher H.; Fowler, Kristen; Cates, Gary L.; Poncy, Brain; Duhon, Gary J.; Solomon, Benjamin G.; Belfiore, Phillip J. – Psychology in the Schools, 2023
Measures of learning speed (i.e., the amount of learning/cumulative time learner spends engaged in an intervention) are rarely included in research designed to evaluate and compare academic interventions. We build a case that includes analyses of learning speed metrics in academic intervention research can provide more useful information for…
Descriptors: Learning Processes, Intervention, Measures (Individuals), Comparative Analysis
Sohee Kim; Ki Lynn Cole – International Journal of Testing, 2025
This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…
Descriptors: Item Response Theory, Comparative Analysis, Models, Item Analysis
Liyang Sun; Eli Ben-Michael; Avi Feller – Grantee Submission, 2024
The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…
Descriptors: Evaluation Methods, Comparative Analysis, Computation, Data Analysis
Yasuhiro Yamamoto; Yasuo Miyazaki – Journal of Experimental Education, 2025
Bayesian methods have been said to solve small sample problems in frequentist methods by reflecting prior knowledge in the prior distribution. However, there are dangers in strongly reflecting prior knowledge or situations where much prior knowledge cannot be used. In order to address the issue, in this article, we considered to apply two Bayesian…
Descriptors: Sample Size, Hierarchical Linear Modeling, Bayesian Statistics, Prior Learning
Nathan A. Call; Alec M. Bernstein; Matthew J. O'Brien; Kelly M. Schieltz; Loukia Tsami; Dorothea C. Lerman; Wendy K. Berg; Scott D. Lindgren; Mark A. Connelly; David P. Wacker – Journal of Applied Behavior Analysis, 2024
Clinicians report primarily using functional behavioral assessment (FBA) methods that do not include functional analyses. However, studies examining the correspondence between functional analyses and other types of FBAs have produced inconsistent results. In addition, although functional analyses are considered the gold standard, their…
Descriptors: Functional Behavioral Assessment, Evaluation Methods, Young Children, Autism Spectrum Disorders
Johan Lyrvall; Zsuzsa Bakk; Jennifer Oser; Roberto Di Mari – Structural Equation Modeling: A Multidisciplinary Journal, 2024
We present a bias-adjusted three-step estimation approach for multilevel latent class models (LC) with covariates. The proposed approach involves (1) fitting a single-level measurement model while ignoring the multilevel structure, (2) assigning units to latent classes, and (3) fitting the multilevel model with the covariates while controlling for…
Descriptors: Hierarchical Linear Modeling, Statistical Bias, Error of Measurement, Simulation
Bartholomew, Scott R.; Jones, Matthew D. – International Journal of Technology and Design Education, 2022
Adaptive Comparative Judgment (ACJ), an approach to the assessment of open-ended problems which utilizes a series of comparisons to produce a standardized score, rank order, and a variety of other statistical measures, has demonstrated high levels of reliability and validity and the potential for application in a wide variety of areas. Further,…
Descriptors: Higher Education, Educational Research, Evaluation Methods, Comparative Analysis
Kazuhiro Yamaguchi – Journal of Educational and Behavioral Statistics, 2025
This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…
Descriptors: Models, Classification, Bayesian Statistics, Evaluation Methods
Lingbo Tong; Wen Qu; Zhiyong Zhang – Grantee Submission, 2025
Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…
Descriptors: Factor Analysis, Monte Carlo Methods, Statistical Analysis, Sample Size
Jiaying Xiao; Chun Wang; Gongjun Xu – Grantee Submission, 2024
Accurate item parameters and standard errors (SEs) are crucial for many multidimensional item response theory (MIRT) applications. A recent study proposed the Gaussian Variational Expectation Maximization (GVEM) algorithm to improve computational efficiency and estimation accuracy (Cho et al., 2021). However, the SE estimation procedure has yet to…
Descriptors: Error of Measurement, Models, Evaluation Methods, Item Analysis
Tenko Raykov – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This note demonstrates that measurement invariance does not guarantee meaningful and valid group comparisons in multiple-population settings. The article follows on a recent critical discussion by Robitzsch and Lüdtke, who argued that measurement invariance was not a pre-requisite for such comparisons. Within the framework of common factor…
Descriptors: Error of Measurement, Prerequisites, Factor Analysis, Evaluation Methods
Leal, Sharon; Vrij, Aldert; Deeb, Haneen; Fisher, Ronald P. – Applied Cognitive Psychology, 2023
Interviewees sometimes deliberately omit reporting some information. Such omission lies differ from other lies because all the information interviewees present may be entirely truthful. Truth tellers and lie tellers carried out a mission. Truth tellers reported the entire mission truthfully. Lie tellers were also entirely truthful but left out one…
Descriptors: Interviews, Deception, Ethics, Disclosure
Hussain, Zawar; Cheema, Salman Arif; Hussain, Ishtiaq – Sociological Methods & Research, 2022
This article is about making correction in Tarray, Singh, and Zaizai model and further improving it when stratified random sampling is necessary. This is done by using optional randomized response technique in stratified sampling using a combination of Mangat and Singh, Mangat, and Greenberg et al. models. The suggested model has been studied…
Descriptors: Comparative Analysis, Models, Surveys, Questionnaires
Ian Greener – International Journal of Social Research Methodology, 2024
This paper argues for three aspects of tolerance with respect to QCA research: tolerance with respect to different approaches to QCA; producing QCA research with tolerance (work that is resistant to criticism); and for QCA researchers to be clear about the tolerance of the solutions they present -- especially in terms of calibration and truth…
Descriptors: Qualitative Research, Research Methodology, Comparative Analysis, Research Design