NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
No Child Left Behind Act 20011
Assessments and Surveys
What Works Clearinghouse Rating
Showing all 15 results Save | Export
Christopher E. Shank – ProQuest LLC, 2024
This dissertation compares the performance of equivalence test (EQT) and null hypothesis test (NHT) procedures for identifying invariant and noninvariant factor loadings under a range of experimental manipulations. EQT is the statistically appropriate approach when the research goal is to find evidence of group similarity rather than group…
Descriptors: Factor Analysis, Goodness of Fit, Intervals, Comparative Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Kulinskaya, Elena; Hoaglin, David C. – Research Synthesis Methods, 2023
For estimation of heterogeneity variance T[superscript 2] in meta-analysis of log-odds-ratio, we derive new mean- and median-unbiased point estimators and new interval estimators based on a generalized Q statistic, Q[subscript F], in which the weights depend on only the studies' effective sample sizes. We compare them with familiar estimators…
Descriptors: Q Methodology, Statistical Analysis, Meta Analysis, Intervals
Peer reviewed Peer reviewed
Direct linkDirect link
Paek, Insu; Lin, Zhongtian; Chalmers, Robert Philip – Educational and Psychological Measurement, 2023
To reduce the chance of Heywood cases or nonconvergence in estimating the 2PL or the 3PL model in the marginal maximum likelihood with the expectation-maximization (MML-EM) estimation method, priors for the item slope parameter in the 2PL model or for the pseudo-guessing parameter in the 3PL model can be used and the marginal maximum a posteriori…
Descriptors: Models, Item Response Theory, Test Items, Intervals
Peer reviewed Peer reviewed
Direct linkDirect link
Silva Diaz, John Alexander; Köhler, Carmen; Hartig, Johannes – Applied Measurement in Education, 2022
Testing item fit is central in item response theory (IRT) modeling, since a good fit is necessary to draw valid inferences from estimated model parameters. "Infit" and "outfit" fit statistics, widespread indices for detecting deviations from the Rasch model, are affected by data factors, such as sample size. Consequently, the…
Descriptors: Intervals, Item Response Theory, Item Analysis, Inferences
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Koçak, Duygu – Pedagogical Research, 2020
Iteration number in Monte Carlo simulation method used commonly in educational research has an effect on Item Response Theory test and item parameters. The related studies show that the number of iteration is at the discretion of the researcher. Similarly, there is no specific number suggested for the number of iteration in the related literature.…
Descriptors: Monte Carlo Methods, Item Response Theory, Educational Research, Test Items
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Li, Xin; Beretvas, S. Natasha – Structural Equation Modeling: A Multidisciplinary Journal, 2013
This simulation study investigated use of the multilevel structural equation model (MLSEM) for handling measurement error in both mediator and outcome variables ("M" and "Y") in an upper level multilevel mediation model. Mediation and outcome variable indicators were generated with measurement error. Parameter and standard…
Descriptors: Sample Size, Structural Equation Models, Simulation, Multivariate Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Gilliland, Dennis; Melfi, Vince – Journal of Statistics Education, 2010
Confidence interval estimation is a fundamental technique in statistical inference. Margin of error is used to delimit the error in estimation. Dispelling misinterpretations that teachers and students give to these terms is important. In this note, we give examples of the confusion that can arise in regard to confidence interval estimation and…
Descriptors: Statistical Inference, Surveys, Intervals, Sample Size
Peer reviewed Peer reviewed
Direct linkDirect link
Reichardt, Charles S. – Multivariate Behavioral Research, 2011
Maxwell, Cole, and Mitchell (2011) demonstrated that simple structural equation models, when used with cross-sectional data, generally produce biased estimates of meditated effects. I extend those results by showing how simple structural equation models can produce biased estimates of meditated effects when used even with longitudinal data. Even…
Descriptors: Structural Equation Models, Statistical Data, Longitudinal Studies, Error of Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Chan, Wai – Educational and Psychological Measurement, 2009
A typical question in multiple regression analysis is to determine if a set of predictors gives the same degree of predictor power in two different populations. Olkin and Finn (1995) proposed two asymptotic-based methods for testing the equality of two population squared multiple correlations, [rho][superscript 2][subscript 1] and…
Descriptors: Multiple Regression Analysis, Intervals, Correlation, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Jamshidian, M.; Khatoonabadi, M. – International Journal of Mathematical Education in Science and Technology, 2007
Almost all introductory and intermediate level statistics textbooks include the topic of confidence interval for the population mean. Almost all these texts introduce the median as a robust measure of central tendency. Only a few of these books, however, cover inference on the population median and in particular confidence interval for the median.…
Descriptors: Intervals, Simulation, Computation, Error of Measurement
Rosenthal, James A. – Springer, 2011
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…
Descriptors: Statistics, Data Interpretation, Social Work, Social Science Research
Peer reviewed Peer reviewed
Direct linkDirect link
Bonett, Douglas G.; Price, Robert M. – Journal of Educational and Behavioral Statistics, 2005
The tetrachoric correlation describes the linear relation between two continuous variables that have each been measured on a dichotomous scale. The treatment of the point estimate, standard error, interval estimate, and sample size requirement for the tetrachoric correlation is cursory and incomplete in modern psychometric and behavioral…
Descriptors: Correlation, Predictor Variables, Measures (Individuals), Error of Measurement
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Mulvenon, Sean W.; Stegman, Charles E. – Journal of Educational Research & Policy Studies, 2006
As part of No Child Left Behind (NCLB) legislation, many states are using confidence intervals to determine a range of scores for evaluating a school system. More specifically, the states are employing confidence intervals to help minimize measurement error in determining a school system's performance. The methodology and techniques employed in…
Descriptors: Federal Legislation, Computation, Intervals, Error of Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Smith, Margaret H. – Journal of Statistics Education, 2004
Unless the sample encompasses a substantial portion of the population, the standard error of an estimator depends on the size of the sample, but not the size of the population. This is a crucial statistical insight that students find very counterintuitive. After trying several ways of convincing students of the validity of this principle, I have…
Descriptors: Sample Size, Error of Measurement, Mathematics Instruction, College Mathematics