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Direct linkNajera, Hector – Measurement: Interdisciplinary Research and Perspectives, 2023
Measurement error affects the quality of population orderings of an index and, hence, increases the misclassification of the poor and the non-poor groups and affects statistical inferences from binary regression models. Hence, the conclusions about the extent, profile, and distribution of poverty are likely to be misleading. However, the size and…
Descriptors: Poverty, Error of Measurement, Classification, Statistical Inference
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
Haimiao Yuan – ProQuest LLC, 2022
The application of diagnostic classification models (DCMs) in the field of educational measurement is getting more attention in recent years. To make a valid inference from the model, it is important to ensure that the model fits the data. The purpose of the present study was to investigate the performance of the limited information…
Descriptors: Goodness of Fit, Educational Assessment, Educational Diagnosis, Models
Conger, Anthony J. – Educational and Psychological Measurement, 2017
Drawing parallels to classical test theory, this article clarifies the difference between rater accuracy and reliability and demonstrates how category marginal frequencies affect rater agreement and Cohen's kappa. Category assignment paradigms are developed: comparing raters to a standard (index) versus comparing two raters to one another…
Descriptors: Interrater Reliability, Evaluators, Accuracy, Statistical Analysis
DiStefano, Christine; McDaniel, Heather L.; Zhang, Liyun; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2019
A simulation study was conducted to investigate the model size effect when confirmatory factor analysis (CFA) models include many ordinal items. CFA models including between 15 and 120 ordinal items were analyzed with mean- and variance-adjusted weighted least squares to determine how varying sample size, number of ordered categories, and…
Descriptors: Factor Analysis, Effect Size, Data, Sample Size
Stamey, James D.; Beavers, Daniel P.; Sherr, Michael E. – Sociological Methods & Research, 2017
Survey data are often subject to various types of errors such as misclassification. In this article, we consider a model where interest is simultaneously in two correlated response variables and one is potentially subject to misclassification. A motivating example of a recent study of the impact of a sexual education course for adolescents is…
Descriptors: Bayesian Statistics, Classification, Models, Correlation
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
Molenaar, Dylan; Dolan, Conor V.; de Boeck, Paul – Psychometrika, 2012
The Graded Response Model (GRM; Samejima, "Estimation of ability using a response pattern of graded scores," Psychometric Monograph No. 17, Richmond, VA: The Psychometric Society, 1969) can be derived by assuming a linear regression of a continuous variable, Z, on the trait, [theta], to underlie the ordinal item scores (Takane & de Leeuw in…
Descriptors: Simulation, Regression (Statistics), Psychometrics, Item Response Theory
Han, Bing; Dalal, Siddhartha R.; McCaffrey, Daniel F. – Journal of Educational and Behavioral Statistics, 2012
There is widespread interest in using various statistical inference tools as a part of the evaluations for individual teachers and schools. Evaluation systems typically involve classifying hundreds or even thousands of teachers or schools according to their estimated performance. Many current evaluations are largely based on individual estimates…
Descriptors: Statistical Inference, Error of Measurement, Classification, Statistical Analysis
Ludtke, Oliver; Marsh, Herbert W.; Robitzsch, Alexander; Trautwein, Ulrich – Psychological Methods, 2011
In multilevel modeling, group-level variables (L2) for assessing contextual effects are frequently generated by aggregating variables from a lower level (L1). A major problem of contextual analyses in the social sciences is that there is no error-free measurement of constructs. In the present article, 2 types of error occurring in multilevel data…
Descriptors: Simulation, Educational Psychology, Social Sciences, Measurement
Yang, Manshu; Chow, Sy-Miin – Psychometrika, 2010
Facial electromyography (EMG) is a useful physiological measure for detecting subtle affective changes in real time. A time series of EMG data contains bursts of electrical activity that increase in magnitude when the pertinent facial muscles are activated. Whereas previous methods for detecting EMG activation are often based on deterministic or…
Descriptors: Test Bias, Error of Measurement, Human Body, Diagnostic Tests
Sullivan, Paul – Journal of Human Resources, 2009
This paper develops an empirical occupational choice model that corrects for misclassification in occupational choices and measurement error in occupation-specific work experience. The model is used to estimate the extent of measurement error in occupation data and quantify the bias that results from ignoring measurement error in occupation codes…
Descriptors: Computation, Models, Career Choice, Error Correction
Ivanova, Masha Y.; Achenbach, Thomas M.; Rescorla, Leslie A.; Harder, Valerie S.; Ang, Rebecca P.; Bilenberg, Niels; Bjarnadottir, Gudrun; Capron, Christiane; De Pauw, Sarah S. W.; Dias, Pedro; Dobrean, Anca; Doepfner, Manfred; Duyme, Michele; Eapen, Valsamma; Erol, Nese; Esmaeili, Elaheh Mohammad; Ezpeleta, Lourdes; Frigerio, Alessandra; Goncalves, Miguel M.; Gudmundsson, Halldor S.; Jeng, Suh-Fang; Jetishi, Pranvera; Jusiene, Roma; Kim, Young-Ah; Kristensen, Solvejg; Lecannelier, Felipe; Leung, Patrick W. L.; Liu, Jianghong; Montirosso, Rosario; Oh, Kyung Ja; Plueck, Julia; Pomalima, Rolando; Shahini, Mimoza; Silva, Jaime R.; Simsek, Zynep; Sourander, Andre; Valverde, Jose; Van Leeuwen, Karla G.; Woo, Bernardine S. C.; Wu, Yen-Tzu; Zubrick, Stephen R.; Verhulst, Frank C. – Journal of the American Academy of Child & Adolescent Psychiatry, 2010
Objective: To test the fit of a seven-syndrome model to ratings of preschoolers' problems by parents in very diverse societies. Method: Parents of 19,106 children 18 to 71 months of age from 23 societies in Asia, Australasia, Europe, the Middle East, and South America completed the Child Behavior Checklist for Ages 1.5-5 (CBCL/1.5-5). Confirmatory…
Descriptors: Check Lists, Social Problems, Psychopathology, Child Behavior
Meyers, Jason L.; Beretvas, S. Natasha – Multivariate Behavioral Research, 2006
Cross-classified random effects modeling (CCREM) is used to model multilevel data from nonhierarchical contexts. These models are widely discussed but infrequently used in social science research. Because little research exists assessing when it is necessary to use CCREM, 2 studies were conducted. A real data set with a cross-classified structure…
Descriptors: Social Science Research, Computation, Models, Data Analysis
Olsson, Henrik; Wennerholm, Pia; Lyxzen, Urban – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2004
J. P. Minda and J. D. Smith (2001) showed that a prototype model outperforms an exemplar model, especially in larger categories or categories that contained more complex stimuli. R. M. Nosofsky and S. R. Zaki (2002) showed that an exemplar model with a response-scaling mechanism outperforms a prototype model. The authors of the current study…
Descriptors: Error of Measurement, Stimuli, Models, Classification
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