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Carpentras, Dino; Quayle, Michael – International Journal of Social Research Methodology, 2023
Agent-based models (ABMs) often rely on psychometric constructs such as 'opinions', 'stubbornness', 'happiness', etc. The measurement process for these constructs is quite different from the one used in physics as there is no standardized unit of measurement for opinion or happiness. Consequently, measurements are usually affected by 'psychometric…
Descriptors: Psychometrics, Error of Measurement, Models, Prediction
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2023
Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…
Descriptors: Educational Research, Data Analysis, Error of Measurement, Computation
Ziying Li; A. Corinne Huggins-Manley; Walter L. Leite; M. David Miller; Eric A. Wright – Educational and Psychological Measurement, 2022
The unstructured multiple-attempt (MA) item response data in virtual learning environments (VLEs) are often from student-selected assessment data sets, which include missing data, single-attempt responses, multiple-attempt responses, and unknown growth ability across attempts, leading to a complex and complicated scenario for using this kind of…
Descriptors: Sequential Approach, Item Response Theory, Data, 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
Li, Tongyun; Jiao, Hong; Macready, George B. – Educational and Psychological Measurement, 2016
The present study investigates different approaches to adding covariates and the impact in fitting mixture item response theory models. Mixture item response theory models serve as an important methodology for tackling several psychometric issues in test development, including the detection of latent differential item functioning. A Monte Carlo…
Descriptors: Item Response Theory, Psychometrics, Test Construction, Monte Carlo Methods
McNeish, Daniel – Review of Educational Research, 2017
In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…
Descriptors: Models, Statistical Analysis, Sampling, Sample Size
Levy, Roy – Educational Psychologist, 2016
In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…
Descriptors: Bayesian Statistics, Models, Educational Research, Innovation
Rhemtulla, Mijke; Jia, Fan; Wu, Wei; Little, Todd D. – International Journal of Behavioral Development, 2014
We examine the performance of planned missing (PM) designs for correlated latent growth curve models. Using simulated data from a model where latent growth curves are fitted to two constructs over five time points, we apply three kinds of planned missingness. The first is item-level planned missingness using a three-form design at each wave such…
Descriptors: Data Analysis, Error of Measurement, Models, Longitudinal Studies
Pampaka, Maria; Hutcheson, Graeme; Williams, Julian – International Journal of Research & Method in Education, 2016
Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
Jia, Fan; Moore, E. Whitney G.; Kinai, Richard; Crowe, Kelly S.; Schoemann, Alexander M.; Little, Todd D. – International Journal of Behavioral Development, 2014
Utilizing planned missing data (PMD) designs (ex. 3-form surveys) enables researchers to ask participants fewer questions during the data collection process. An important question, however, is just how few participants are needed to effectively employ planned missing data designs in research studies. This article explores this question by using…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
Lang, Kyle M.; Little, Todd D. – International Journal of Behavioral Development, 2014
We present a new paradigm that allows simplified testing of multiparameter hypotheses in the presence of incomplete data. The proposed technique is a straight-forward procedure that combines the benefits of two powerful data analytic tools: multiple imputation and nested-model ?2 difference testing. A Monte Carlo simulation study was conducted to…
Descriptors: Hypothesis Testing, Data Analysis, Error of Measurement, Computation
Cheema, Jehanzeb R. – Review of Educational Research, 2014
Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…
Descriptors: Educational Research, Data, Data Collection, Data Processing

Tinsley, Howard E. A. – Journal of Vocational Behavior, 2000
A research review supports the validity of the person-environment fit (PEF) model in vocational psychology; however, sampling inadequacies have influenced results. One PEF example, Holland's hexagonal model, is unsupported due to lack of commensurate measurement; most hexagonal congruence indices are invalid. (Contains 110 references.) (SK)
Descriptors: Career Counseling, Congruence (Psychology), Error of Measurement, Industrial Psychology

Dawis, Rene V.; Gati, Itamar; Hesketh, Beryl; Prediger, Dale J.; Rounds, James; McKenna, Molly C.; Hubert, Lawrence; Day, Susan X.; Tracey, Terence J. G.; Darcy, Maria; Kovalski, Theresa M. – Journal of Vocational Behavior, 2000
Includes "P-E [Person-Environment] Fit as Paradigm" (Dawis); "Pitfalls of Congruence Research" (Gati); "The Next Millennium of 'Fit' Research" (Hesketh); "Holland's Hexagon Is Alive and Well--Though Somewhat out of Shape" (Prediger); "Tinsley on Holland: A Misshapen Argument" (Rounds, McKenna,…
Descriptors: Career Counseling, Congruence (Psychology), Error of Measurement, Industrial Psychology
Herzog, Serge – New Directions for Institutional Research, 2008
Among the varied analytical challenges institutional researchers face, examining faculty pay may be one of the most vexing. Although the literature on faculty compensation analysis dates back to the 1970s (Loeb and Ferber, 1971; Gordon, Morton, and Braden, 1974; Scott, 1977; Braskamp and Johnson, 1978; McLaughlin, Smart, and Montgomery, 1978),…
Descriptors: Teacher Salaries, Land Grant Universities, Compensation (Remuneration), Workers Compensation
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