NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Type
Reports - Descriptive58
Journal Articles53
Numerical/Quantitative Data2
Opinion Papers1
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 58 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Huang, Francis L. – Journal of Educational and Behavioral Statistics, 2022
The presence of clustered data is common in the sociobehavioral sciences. One approach that specifically deals with clustered data but has seen little use in education is the generalized estimating equations (GEEs) approach. We provide a background on GEEs, discuss why it is appropriate for the analysis of clustered data, and provide worked…
Descriptors: Multivariate Analysis, Computation, Correlation, Error of Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Raykov, Tenko; Marcoulides, George A. – Measurement: Interdisciplinary Research and Perspectives, 2023
This article outlines a readily applicable procedure for point and interval estimation of the population discrepancy between reliability and the popular Cronbach's coefficient alpha for unidimensional multi-component measuring instruments with uncorrelated errors, which are widely used in behavioral and social research. The method is developed…
Descriptors: Measurement, Test Reliability, Measurement Techniques, Error of Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Noma, Hisashi; Hamura, Yasuyuki; Gosho, Masahiko; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average…
Descriptors: Network Analysis, Meta Analysis, Regression (Statistics), Error of Measurement
Dan Soriano; Eli Ben-Michael; Peter Bickel; Avi Feller; Samuel D. Pimentel – Grantee Submission, 2023
Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to…
Descriptors: Statistical Analysis, Computation, Mathematical Formulas, Monte Carlo Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Victoria Savalei; Yves Rosseel – Structural Equation Modeling: A Multidisciplinary Journal, 2022
This article provides an overview of different computational options for inference following normal theory maximum likelihood (ML) estimation in structural equation modeling (SEM) with incomplete normal and nonnormal data. Complete data are covered as a special case. These computational options include whether the information matrix is observed or…
Descriptors: Structural Equation Models, Computation, Error of Measurement, Robustness (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
von Hippel, Paul T. – Sociological Methods & Research, 2020
When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imputations if, in addition to efficient point estimates, you also want standard error (SE) estimates that would…
Descriptors: Computation, Error of Measurement, Data Analysis, Children
Peer reviewed Peer reviewed
Direct linkDirect link
Yang, Shitao; Black, Ken – Teaching Statistics: An International Journal for Teachers, 2019
Summary Employing a Wald confidence interval to test hypotheses about population proportions could lead to an increase in Type I or Type II errors unless the hypothesized value, p0, is used in computing its standard error rather than the sample proportion. Whereas the Wald confidence interval to estimate a population proportion uses the sample…
Descriptors: Error Patterns, Evaluation Methods, Error of Measurement, Measurement Techniques
Peer reviewed Peer reviewed
Direct linkDirect link
Howe, Roger – ZDM: The International Journal on Mathematics Education, 2019
This paper makes a proposal, from the perspective of a research mathematician interested in mathematics education, for broadening and deepening whole number arithmetic instruction, to make it more relevant for the twenty-first century, in particular, to enable students to deal with large numbers, arguably an essential skill for modern citizenship.…
Descriptors: Number Concepts, Numbers, Error of Measurement, Computation
Oranje, Andreas; Kolstad, Andrew – Journal of Educational and Behavioral Statistics, 2019
The design and psychometric methodology of the National Assessment of Educational Progress (NAEP) is constantly evolving to meet the changing interests and demands stemming from a rapidly shifting educational landscape. NAEP has been built on strong research foundations that include conducting extensive evaluations and comparisons before new…
Descriptors: National Competency Tests, Psychometrics, Statistical Analysis, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Bardhoshi, Gerta; Erford, Bradley T. – Measurement and Evaluation in Counseling and Development, 2017
Precision is a key facet of test development, with score reliability determined primarily according to the types of error one wants to approximate and demonstrate. This article identifies and discusses several primary forms of reliability estimation: internal consistency (i.e., split-half, KR-20, a), test-retest, alternate forms, interscorer, and…
Descriptors: Scores, Test Reliability, Accuracy, Pretests Posttests
Weiss, Michael J.; Lockwood, J. R.; McCaffrey, Daniel F. – MDRC, 2014
In many experimental evaluations in the social and medical sciences, individuals are randomly assigned to a treatment arm or a control arm of the experiment. After treatment assignment is determined, individuals within one or both experimental arms are frequently grouped together (e.g., within classrooms or schools, through shared case managers,…
Descriptors: Error of Measurement, Randomized Controlled Trials, Correlation, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Tellinghuisen, Joel – Journal of Chemical Education, 2015
The method of least-squares (LS) has a built-in procedure for estimating the standard errors (SEs) of the adjustable parameters in the fit model: They are the square roots of the diagonal elements of the covariance matrix. This means that one can use least-squares to obtain numerical values of propagated errors by defining the target quantities as…
Descriptors: Least Squares Statistics, Error of Measurement, Error Patterns, Chemistry
Peer reviewed Peer reviewed
Direct linkDirect link
Xi, Nuo; Browne, Michael W. – Journal of Educational and Behavioral Statistics, 2014
A promising "underlying bivariate normal" approach was proposed by Jöreskog and Moustaki for use in the factor analysis of ordinal data. This was a limited information approach that involved the maximization of a composite likelihood function. Its advantage over full-information maximum likelihood was that very much less computation was…
Descriptors: Factor Analysis, Maximum Likelihood Statistics, Data, Computation
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Moraveji, Behjat; Jafarian, Koorosh – International Journal of Education and Literacy Studies, 2014
The aim of this paper is to provide an introduction of new imputation algorithms for estimating missing values from official statistics in larger data sets of data pre-processing, or outliers. The goal is to propose a new algorithm called IRMI (iterative robust model-based imputation). This algorithm is able to deal with all challenges like…
Descriptors: Mathematics, Computation, Robustness (Statistics), Regression (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
Raykov, Tenko – Educational and Psychological Measurement, 2012
A latent variable modeling approach that permits estimation of propensity scores in observational studies containing fallible independent variables is outlined, with subsequent examination of treatment effect. When at least one covariate is measured with error, it is indicated that the conventional propensity score need not possess the desirable…
Descriptors: Computation, Probability, Error of Measurement, Observation
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4