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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
Teck Kiang Tan – Practical Assessment, Research & Evaluation, 2024
The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…
Descriptors: Bayesian Statistics, Factor Analysis, Programming Languages, Reliability
Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2022
This article develops new closed-form variance expressions for power analyses for commonly used difference-in-differences (DID) and comparative interrupted time series (CITS) panel data estimators. The main contribution is to incorporate variation in treatment timing into the analysis. The power formulas also account for other key design features…
Descriptors: Comparative Analysis, Statistical Analysis, Sample Size, Measurement Techniques
Luecht, Richard; Ackerman, Terry A. – Educational Measurement: Issues and Practice, 2018
Simulation studies are extremely common in the item response theory (IRT) research literature. This article presents a didactic discussion of "truth" and "error" in IRT-based simulation studies. We ultimately recommend that future research focus less on the simple recovery of parameters from a convenient generating IRT model,…
Descriptors: Item Response Theory, Simulation, Ethics, Error of Measurement
Gordon, Sheldon P.; Yang, Yajun – International Journal of Mathematical Education in Science and Technology, 2017
This article takes a closer look at the problem of approximating the exponential and logarithmic functions using polynomials. Either as an alternative to or a precursor to Taylor polynomial approximations at the precalculus level, interpolating polynomials are considered. A measure of error is given and the behaviour of the error function is…
Descriptors: Mathematical Formulas, Algebra, Mathematics Activities, Error of Measurement
Culpepper, Steven Andrew – Applied Psychological Measurement, 2013
A classic topic in the fields of psychometrics and measurement has been the impact of the number of scale categories on test score reliability. This study builds on previous research by further articulating the relationship between item response theory (IRT) and classical test theory (CTT). Equations are presented for comparing the reliability and…
Descriptors: Item Response Theory, Reliability, Scores, Error of Measurement
Kolen, Michael J.; Lee, Won-Chan – Educational Measurement: Issues and Practice, 2011
This paper illustrates that the psychometric properties of scores and scales that are used with mixed-format educational tests can impact the use and interpretation of the scores that are reported to examinees. Psychometric properties that include reliability and conditional standard errors of measurement are considered in this paper. The focus is…
Descriptors: Test Use, Test Format, Error of Measurement, Raw Scores
Fan, Xitao; Nowell, Dana L. – Gifted Child Quarterly, 2011
This methodological brief introduces the readers to the propensity score matching method, which can be used for enhancing the validity of causal inferences in research situations involving nonexperimental design or observational research, or in situations where the benefits of an experimental design are not fully realized because of reasons beyond…
Descriptors: Research Design, Educational Research, Statistical Analysis, Inferences
Broughman, Stephen P.; Swaim, Nancy L.; Hryczaniuk, Cassie A. – National Center for Education Statistics, 2011
In 1988, the National Center for Education Statistics (NCES) introduced a proposal to develop a private school data collection that would improve on the sporadic collection of private school data dating back to 1890 and improve on commercially available private school sampling frames. Since 1989, the U.S. Bureau of the Census has conducted the…
Descriptors: Private Schools, Statistical Significance, Sampling, Statistics
Briggs, Derek C. – Partnership for Assessment of Readiness for College and Careers, 2011
There is often confusion about distinctions between growth models and value-added models. The first half of this paper attempts to dispel some of these confusions by clarifying terminology and illustrating by example how the results from a large-scale assessment can and will be used to make inferences about student growth and the value-added…
Descriptors: Value Added Models, Language Usage, Measurement, Inferences

Williams, Valerie S. L.; Jones, Lyle V.; Tukey, John W. – Journal of Educational and Behavioral Statistics, 1999
Illustrates and compares three alternative procedures to adjust significance levels for multiplicity: (1) the traditional Bonferroni technique; (2) a sequential Bonferroni technique; and (3) a sequential approach to control the false discovery rate proposed by Y. Benjamini and Y. Hochberg (1995). Explains advantages of the Benjamini and Hochberg…
Descriptors: Academic Achievement, Comparative Analysis, Error of Measurement, Statistical Significance

Riniolo, Todd C. – Journal of Experimental Education, 1999
Presents an alternative statistical test, BOOT(subscript)med for the two-group situation when a small experimental group is being compared with a large control group. BOOTmed is a between-groups median test derived through bootstrapping techniques. Empirical validation indicates that BOOTmed maintains relatively robust error rates under a variety…
Descriptors: Comparative Analysis, Control Groups, Error of Measurement, Statistical Analysis
George, Carrie A. – 2001
Single studies, by themselves, rarely explain the effect of treatments or interventions definitively in the social sciences. Researchers created meta-analysis in the 1970s to address this need. Since then, meta-analytic techniques have been used to support certain treatment modalities and to influence policymakers. Although these techniques…
Descriptors: Comparative Analysis, Effect Size, Error of Measurement, Meta Analysis
Wang, Jichuan – Structural Equation Modeling, 2004
In addition to assessing the rate of change in outcome measures, it may be useful to test the significance of outcome changes during specific time periods within an entire observation period under study. While discussing the delta method and bootstrapping, this study demonstrates how to use these 2 methods to estimate the standard errors of the…
Descriptors: Longitudinal Studies, Error of Measurement, Measures (Individuals), Comparative Analysis
Eaton, Karen M.; Messer, Stephen C.; Garvey Wilson, Abigail L.; Hoge, Charles W. – Suicide and Life-Threatening Behavior, 2006
The objectives of this study were to generate precise estimates of suicide rates in the military while controlling for factors contributing to rate variability such as demographic differences and classification bias, and to develop a simple methodology for the determination of statistically derived thresholds for detecting significant rate…
Descriptors: Suicide, Mortality Rate, Comparative Analysis, Validity
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