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Duane Knudson – Measurement in Physical Education and Exercise Science, 2025
Small sample sizes contribute to several problems in research and knowledge advancement. This conceptual replication study confirmed and extended the inflation of type II errors and confidence intervals in correlation analyses of small sample sizes common in kinesiology/exercise science. Current population data (N = 18, 230, & 464) on four…
Descriptors: Kinesiology, Exercise, Biomechanics, Movement Education
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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
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Boodoo, Gwyneth M. – Journal of Educational Statistics, 1982
Incidence sampling is a parsimonious method whereby a large number of examinees can be measured on many variables (such as test items) to assess group characteristics. Parameters used to describe an incidence sample are estimated using the theory of generalized symmetric means and generalizability theory. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Error of Measurement, Measurement Techniques
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Basch, Charles E.; Gold, Robert S. – Journal of School Health, 1985
Reliability guides research design and is used as a standard for judging the credibility of findings and inferences. Using data gathered in a school health education curriculum evaluation as an example, possible errors in hypothesis testing are examined. Appropriateness of internal consistency as a measure of reliability is discussed and…
Descriptors: Cognitive Tests, Elementary Secondary Education, Error of Measurement, Health Education
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Levin, Joel R.; Subkoviak, Michael J. – Applied Psychological Measurement, 1977
Textbook calculations of statistical power or sample size follow from formulas that assume that the variables under consideration are measured without error. However, in the real world of behavioral research, errors of measurement cannot be neglected. The determination of sample size is discussed, and an example illustrates blocking strategy.…
Descriptors: Analysis of Covariance, Analysis of Variance, Error of Measurement, Hypothesis Testing
Naizer, Gilbert – 1992
A measurement approach called generalizability theory (G-theory) is an important alternative to the more familiar classical measurement theory that yields less useful coefficients such as alpha or the KR-20 coefficient. G-theory is a theory about the dependability of behavioral measurements that allows the simultaneous estimation of multiple…
Descriptors: Error of Measurement, Estimation (Mathematics), Generalizability Theory, Higher Education
Schumacker, Randall E. – 1992
The regression-discontinuity approach to evaluating educational programs is reviewed, and regression-discontinuity post-program mean differences under various conditions are discussed. The regression-discontinuity design is used to determine whether post-program differences exist between an experimental program and a control group. The difference…
Descriptors: Comparative Analysis, Computer Simulation, Control Groups, Cutting Scores
Olejnik, Stephen F.; Porter, Andrew C. – 1978
The statistical properties of two methods of estimating gain scores for groups in quasi-experiments are compared: (1) gains in scores standardized separately for each group; and (2) analysis of covariance with estimated true pretest scores. The fan spread hypothesis is assumed for groups but not necessarily assumed for members of the groups.…
Descriptors: Academic Achievement, Achievement Gains, Analysis of Covariance, Analysis of Variance