NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 10 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Citkowicz, Martyna; Hedges, Larry V. – Society for Research on Educational Effectiveness, 2013
In some instances, intentionally or not, study designs are such that there is clustering in one group but not in the other. This paper describes methods for computing effect size estimates and their variances when there is clustering in only one group and the analysis has not taken that clustering into account. The authors provide the effect size…
Descriptors: Multivariate Analysis, Effect Size, Sampling, Sample Size
Peer reviewed Peer reviewed
Direct linkDirect link
Phillips, Gary W. – Applied Measurement in Education, 2015
This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…
Descriptors: State Programs, Sampling, Research Design, Error of Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
McCoach, D. Betsy; Adelson, Jill L. – Gifted Child Quarterly, 2010
This article provides a conceptual introduction to the issues surrounding the analysis of clustered (nested) data. We define the intraclass correlation coefficient (ICC) and the design effect, and we explain their effect on the standard error. When the ICC is greater than 0, then the design effect is greater than 1. In such a scenario, the…
Descriptors: Statistical Significance, Error of Measurement, Correlation, Data Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
What Works Clearinghouse, 2014
This "What Works Clearinghouse Procedures and Standards Handbook (Version 3.0)" provides a detailed description of the standards and procedures of the What Works Clearinghouse (WWC). The remaining chapters of this Handbook are organized to take the reader through the basic steps that the WWC uses to develop a review protocol, identify…
Descriptors: Educational Research, Guides, Intervention, Classification
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Shirbagi, Naser – Quality of Higher Education, 2011
The main purpose of this research is to examine the effectiveness of Student Evaluation of Teaching (SET) from a sample of university teachers' and students' view. The study adopts exploratory descriptive design. Participants of this research were 300 teachers and 600 graduate students from 3 Iranian higher education institutions. A 30-item format…
Descriptors: Higher Education, Student Evaluation of Teacher Performance, Faculty Evaluation, Likert Scales
Peer reviewed Peer reviewed
Onwuegbuzie, Anthony J.; Roberts, J. Kyle; Daniel, Larry G. – Measurement and Evaluation in Counseling and Development, 2005
In this article, the authors (a) illustrate how displaying disattenuated correlation coefficients alongside their unadjusted counterparts will allow researchers to assess the impact of unreliability on bivariate relationships and (b) demonstrate how a proposed new "what if reliability" analysis can complement null hypothesis significance…
Descriptors: Correlation, Statistical Significance, Reliability, Error of Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Marsh, Herbert W.; Hau, Kit-Tai; Wen, Zhonglin – Structural Equation Modeling, 2004
Goodness-of-fit (GOF) indexes provide "rules of thumb"?recommended cutoff values for assessing fit in structural equation modeling. Hu and Bentler (1999) proposed a more rigorous approach to evaluating decision rules based on GOF indexes and, on this basis, proposed new and more stringent cutoff values for many indexes. This article discusses…
Descriptors: Statistical Significance, Structural Equation Models, Evaluation Methods, Evaluation Research
Peer reviewed Peer reviewed
Cohen, Patricia – Evaluation and Program Planning: An International Journal, 1982
The various costs of Type I and Type II errors of inference from data are discussed. Six methods for minimizing each error type are presented, which may be employed even after data collection for Type I and which minimizes Type II errors by a study design and analytical means combination. (Author/CM)
Descriptors: Analysis of Variance, Data Analysis, Data Collection, Error of Measurement
Dunivant, Noel – 1979
Eight different methods are reviewed for determining whether two or more tests are equivalent measures. These methods vary in restrictiveness from the Wilks-Votaw test of compound symmetry (which requires that all means, variances, and covariances are equal), to Joreskog's theory of congeneric tests (which requires only that the tests are measures…
Descriptors: Analysis of Variance, Comparative Analysis, Error of Measurement, Evaluation Methods
Lefebvre, Daniel J.; Suen, Hoi K. – 1990
An empirical investigation of methodological issues associated with evaluating treatment effect in single-subject research (SSR) designs is presented. This investigation: (1) conducted a generalizability (G) study to identify the sources of systematic and random measurement error (SRME); (2) used an analytic approach based on G theory to integrate…
Descriptors: Classroom Observation Techniques, Disabilities, Educational Research, Error of Measurement