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Thomas, Michael L.; Brown, Gregory G.; Patt, Virginie M.; Duffy, John R. – Educational and Psychological Measurement, 2021

The adaptation of experimental cognitive tasks into measures that can be used to quantify neurocognitive outcomes in translational studies and clinical trials has become a key component of the strategy to address psychiatric and neurological disorders. Unfortunately, while most experimental cognitive tests have strong theoretical bases, they can…

Descriptors: Adaptive Testing, Computer Assisted Testing, Cognitive Tests, Psychopathology

Zumbo, Bruno D.; Kroc, Edward – Educational and Psychological Measurement, 2019

Chalmers recently published a critique of the use of ordinal a[alpha] proposed in Zumbo et al. as a measure of test reliability in certain research settings. In this response, we take up the task of refuting Chalmers' critique. We identify three broad misconceptions that characterize Chalmers' criticisms: (1) confusing assumptions with…

Descriptors: Test Reliability, Statistical Analysis, Misconceptions, Mathematical Models

Lamprianou, Iasonas – Educational and Psychological Measurement, 2018

It is common practice for assessment programs to organize qualifying sessions during which the raters (often known as "markers" or "judges") demonstrate their consistency before operational rating commences. Because of the high-stakes nature of many rating activities, the research community tends to continuously explore new…

Descriptors: Social Networks, Network Analysis, Comparative Analysis, Innovation

Luo, Yong; Jiao, Hong – Educational and Psychological Measurement, 2018

Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the…

Descriptors: Bayesian Statistics, Item Response Theory, Probability, Computer Software

Andrich, David – Educational and Psychological Measurement, 2016

This article reproduces correspondence between Georg Rasch of The University of Copenhagen and Benjamin Wright of The University of Chicago in the period from January 1966 to July 1967. This correspondence reveals their struggle to operationalize a unidimensional measurement model with sufficient statistics for responses in a set of ordered…

Descriptors: Statistics, Item Response Theory, Rating Scales, Mathematical Models

Tran, Ulrich S.; Formann, Anton K. – Educational and Psychological Measurement, 2009

Parallel analysis has been shown to be suitable for dimensionality assessment in factor analysis of continuous variables. There have also been attempts to demonstrate that it may be used to uncover the factorial structure of binary variables conforming to the unidimensional normal ogive model. This article provides both theoretical and empirical…

Descriptors: Simulation, Factor Analysis, Correlation, Evaluation Methods

Liu, Yan; Zumbo, Bruno D. – Educational and Psychological Measurement, 2007

The impact of outliers on Cronbach's coefficient [alpha] has not been documented in the psychometric or statistical literature. This is an important gap because coefficient [alpha] is the most widely used measurement statistic in all of the social, educational, and health sciences. The impact of outliers on coefficient [alpha] is investigated for…

Descriptors: Psychometrics, Computation, Reliability, Monte Carlo Methods

Wilcox, Rand R. – Educational and Psychological Measurement, 2006

Consider the nonparametric regression model Y = m(X)+ [tau](X)[epsilon], where X and [epsilon] are independent random variables, [epsilon] has a median of zero and variance [sigma][squared], [tau] is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated…

Descriptors: Nonparametric Statistics, Mathematical Models, Regression (Statistics), Probability

Graham, James M. – Educational and Psychological Measurement, 2006

Coefficient alpha, the most commonly used estimate of internal consistency, is often considered a lower bound estimate of reliability, though the extent of its underestimation is not typically known. Many researchers are unaware that coefficient alpha is based on the essentially tau-equivalent measurement model. It is the violation of the…

Descriptors: Models, Test Theory, Reliability, Structural Equation Models

Rupp, Andre A.; Zumbo, Bruno D. – Educational and Psychological Measurement, 2004

Based on seminal work by Lord and Hambleton, Swaminathan, and Rogers, this article is an analytical, graphical, and conceptual reminder that item response theory (IRT) parameter invariance only holds for perfect model fit in multiple populations or across multiple conditions and is thus an ideal state. In practice, one attempts to quantify the…

Descriptors: Correlation, Item Response Theory, Statistical Analysis, Evaluation Methods

Peer reviewed

Linn, Robert L. – Educational and Psychological Measurement, 1971

Descriptors: Educational Environment, Educational Finance, Evaluation Methods, Expenditure per Student

Peer reviewed

Horn, John L. – Educational and Psychological Measurement, 1971

Descriptors: Analysis of Variance, Error of Measurement, Hypothesis Testing, Mathematical Models

Peer reviewed

Werts, Charles E.; Linn, Robert L. – Educational and Psychological Measurement, 1971

Descriptors: Analysis of Covariance, Correlation, Educational Environment, Error of Measurement

Peer reviewed

Shine, Lester C. , II; Bower, Samuel M. – Educational and Psychological Measurement, 1971

Descriptors: Analysis of Variance, Behavioral Science Research, Hypothesis Testing, Mathematical Models

Peer reviewed

Werts, Charles E.; Linn, Robert L. – Educational and Psychological Measurement, 1971

Descriptors: Analysis of Covariance, Analysis of Variance, Mathematical Models, Multiple Regression Analysis