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Rudner, Lawrence M.; Schafer, William D. – 2001
This digest discusses sources of error in testing, several approaches to estimating reliability, and several ways to increase test reliability. Reliability has been defined in different ways by different authors, but the best way to look at reliability may be the extent to which measurements resulting from a test are characteristics of those being…
Descriptors: Educational Testing, Error of Measurement, Reliability, Scores
Tsai, Tsung-Hsun – 1997
The primary objective of this study was to find the smallest sample size for which equating based on a random groups design could be expected to result in less overall equating error than had no equating been conducted. Mean, linear, and equipercentile equating methods were considered. Some of the analyses presented in this paper assumed that the…
Descriptors: Equated Scores, Error of Measurement, Estimation (Mathematics), Sample Size
Li, Yuan H.; Schafer, William D. – 2002
An empirical study of the Yen (W. Yen, 1997) analytic formula for the standard error of a percent-above-cut [SE(PAC)] was conducted. This formula was derived from variance component information gathered in the context of generalizability theory. SE(PAC)s were estimated by different methods of estimating variance components (e.g., W. Yens…
Descriptors: Cutting Scores, Error of Measurement, Generalizability Theory, Simulation
PDF pending restorationDimitrov, Dimiter M. – 2002
Exact formulas for classical error variance are provided for Rasch measurement with logistic distributions. An approximation formula with the normal ability distribution is also provided. With the proposed formulas, the additive contribution of individual items to the population error variance can be determined without knowledge of the other test…
Descriptors: Ability, Error of Measurement, Item Response Theory, Test Items
Lee, Guemin – 1999
Previous studies have indicated that the reliability of test scores composed of testlets is overestimated by conventional item-based reliability estimation methods (S. Sireci, D. Thissen, and H. Wainer, 1991; H. Wainer, 1995; H. Wainer and D. Thissen, 1996; G. Lee and D. Frisbie). In light of these studies, it seems reasonable to ask whether the…
Descriptors: Definitions, Error of Measurement, Estimation (Mathematics), Reliability
Lee, Guemin – 1998
The primary purpose of this study was to investigate the appropriateness and implication of incorporating a testlet definition into the estimation of the conditional standard error of measurement (SEM) for tests composed of testlets. The five conditional SEM estimation methods used in this study were classified into two categories: item-based and…
Descriptors: Definitions, Error of Measurement, Estimation (Mathematics), Reliability
Henson, Robin K.; Kogan, Lori R.; Vacha-Haase, Tammi – 2000
Teacher efficacy has proven to be an important variable in teacher effectiveness. It is consistently related to positive teaching behaviors and student outcomes. However, the measurement of this construct is the subject of current debate, which includes critical examination of predominant instruments used to assess teacher efficacy. The present…
Descriptors: Error of Measurement, Generalization, Measurement Techniques, Meta Analysis
Cousin, Sherri L.; Henson, Robin K. – 2000
Researchers consistently fail to report reliability estimates for data used in their studies. This lack of reporting hinders appropriate evaluation and interpretation of data and may lead to inappropriate conclusions. Because reliability is inured to scores obtained from a test, and not the test itself, it is important to report score reliability…
Descriptors: Data Analysis, Error of Measurement, Estimation (Mathematics), Generalization
Peer reviewedLytton, Hugh; And Others – Developmental Psychology, 1973
This reply refers to PS 502 345 which in turn is a criticism of EJ 045 083. (CB)
Descriptors: Error of Measurement, Reading Difficulty, Research Methodology, Statistical Analysis
Peer reviewedFurby, Lita – Developmental Psychology, 1973
Purpose of this article is to explain the fundamental nature and sources of regression toward the mean. The ultimate goal is that developmental psychologists understand regression effects well enough so that they will not make erroneous interpretations of such effects in their empirical data. (Author)
Descriptors: Developmental Psychology, Error of Measurement, Measurement, Multiple Regression Analysis
Peer reviewedCureton, Edward E.; And Others – Educational and Psychological Measurement, 1973
Study based on F. M. Lord's arguments in 1957 and 1959 that tests of the same length do have the same standard error of measurement. (CB)
Descriptors: Error of Measurement, Statistical Analysis, Test Interpretation, Test Length
Peer reviewedNaglieri, Jack A. – Journal of Consulting and Clinical Psychology, 1982
Computed confidence intervals for the Wechsler Adult Intelligence Scale-Revised for the Verbal, Performance, and Full Scale IQ scores. Reports IQ intervals for the 85 percent, 90 percent, 95 percent, and 99 percent levels of confidence for each of the nine standardization sample age groups and the entire sample. (Author)
Descriptors: Error of Measurement, Intelligence Quotient, Intelligence Tests, Statistical Analysis
Peer reviewedLuftig, Jeffrey T.; Norton, Willis P. – Journal of Studies in Technical Careers, 1981
The purpose of this article is to review applications of reliability formulas and to recommend more appropriate methods of determining the reliability of affective instruments. (SK)
Descriptors: Affective Measures, Error of Measurement, Measurement Techniques, Test Reliability
Peer reviewedZimmerman, Donald W.; Williams, Richard H. – Psychometrika, 1982
Formulas for the standard error of measurement of three measures of change (simple differences; residualized difference scores; and a measure introduced by Tucker, Damarin, and Messick) are derived. A practical guide for determining the relative error of the three measures is developed. (Author/JKS)
Descriptors: Achievement Gains, Algorithms, Differences, Error of Measurement
Peer reviewedWilcox, Rand R. – Journal of Educational Statistics, 1981
Both the binomial and beta-binomial models are applied to various problems occurring in mental test theory. The paper reviews and critiques these models. The emphasis is on the extensions of the models that have been proposed in recent years, and that might not be familiar to many educators. (Author)
Descriptors: Error of Measurement, Item Analysis, Mathematical Models, Test Reliability


