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Glas, C. A. W. – 2001
In a previous study (1998), how to evaluate whether adaptive testing data used for online calibration sufficiently fit the item response model used by C. Glas was studied. Three approaches were suggested, based on a Lagrange multiplier (LM) statistic, a Wald statistic, and a cumulative sum (CUMSUM) statistic respectively. For all these methods,…
Descriptors: Adaptive Testing, Computer Assisted Testing, Error of Measurement, Estimation (Mathematics)
Hill, Richard – 1997
In the Spring, 1996, issue of "CRESST Line," E. Baker and R. Linn commented that, in efforts to measure the progress of schools, "the fluctuations due to differences in the students themselves could conceal differences in instructional effects." This is particularly true in the context of the evaluation of adequate yearly…
Descriptors: Academic Achievement, Compensatory Education, Disadvantaged Youth, Educational Improvement
Arenson, Ethan – 2000
This paper is the first of a series that will compare estimates of error that arises when state assessments are linked to the National Assessment of Educational Progress (NAEP). Different forms of linkage are discussed. Comparisons are made between whole-sample regression, repeated half-sample replication, bootstrap, and jackknife estimates of the…
Descriptors: Elementary Secondary Education, Equated Scores, Error of Measurement, Estimation (Mathematics)
Sterling, Donna R.; Hall, Alfred L., II – 2000
This study was conceived when it was observed that in the laboratory, with few exceptions, college freshmen chemistry students did not know how to make accurate measurements. Once the students were made aware of this, they easily learned how. From this experience and in the interest of breaking the cycle, it was decided to assess the ability of…
Descriptors: Curriculum Development, Error of Measurement, Hands on Science, Higher Education
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
Peer reviewed Peer reviewed
Huck, Schuyler W.; And Others – Educational and Psychological Measurement, 1981
Believing that examinee-by-item interaction should be conceptualized as true score variability rather than as a result of errors of measurement, Lu proposed a modification of Hoyt's analysis of variance reliability procedure. Via a computer simulation study, it is shown that Lu's approach does not separate interaction from error. (Author/RL)
Descriptors: Analysis of Variance, Comparative Analysis, Computer Programs, Difficulty Level
Cummings, Oliver W. – Measurement and Evaluation in Guidance, 1981
Examined the effects on their test performance of junior high school students changing responses. Results indicated that changing answers neither increases the reliability nor decreases the standard error of measurement of the test. (Author/RC)
Descriptors: Change, Comparative Analysis, Error of Measurement, Junior High Schools
Peer reviewed Peer reviewed
Lord, Frederic M. – Applied Psychological Measurement, 1977
A broad-range tailored test of verbal ability, appropriate at any level from fifth grade upwards, is briefly described. The test score places persons at all levels directly on the same score scale. (Author/RC)
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Computer Oriented Programs
Peer reviewed Peer reviewed
Rusling, James F. – Journal of Chemical Education, 1988
Investigates minimizing errors in computational methods commonly used in chemistry. Provides a series of examples illustrating the propagation of errors, finite difference methods, and nonlinear regression analysis. Includes illustrations to explain these concepts. (MVL)
Descriptors: Chemistry, College Science, Computation, Computer Uses in Education
Peer reviewed Peer reviewed
Gross, Leon J. – Evaluation and the Health Professions, 1994
Whether adequate levels of interrater reliability could be obtained on a national, standardized examination using one examiner per observation was studied with 101 paired candidate observations on an examination for optometry. Results indicate that psychometrically sound judgments can be obtained with one examiner. (SLD)
Descriptors: Educational Assessment, Error of Measurement, Evaluation Methods, Evaluators
Peer reviewed Peer reviewed
Bergstrom, Betty A.; Lunz, Mary E. – Evaluation and the Health Professions, 1992
The level of confidence in pass/fail decisions obtained with computerized adaptive tests and paper-and-pencil tests was greater for 645 medical technology students when the computer adaptive test implemented a 90 percent confidence stopping rule than for paper-and-pencil tests of comparable length. (SLD)
Descriptors: Adaptive Testing, Comparative Testing, Computer Assisted Testing, Confidence Testing
Peer reviewed Peer reviewed
Trochim, William M. K.; And Others – Evaluation Review, 1991
The regression-discontinuity design involving a treatment interaction effect (TIE), pretest-posttest functional form specification, and choice of point-of-estimation of the TIE are examined. Formulas for controlling the magnitude of TIE in simulations can be used for simulating the randomized experimental case where estimation is not at the…
Descriptors: Computer Simulation, Control Groups, Equations (Mathematics), Error of Measurement
Peer reviewed Peer reviewed
Harvill, Leo M. – Educational Measurement: Issues and Practice, 1991
This paper discusses standard error of measurement (SEM), the amount of variation or spread in the measurement errors for a test, and gives information needed to interpret test scores using SEMs. SEMs at various score levels should be used in calculating score bands rather than a single SEM value. (SLD)
Descriptors: Definitions, Equations (Mathematics), Error of Measurement, Estimation (Mathematics)
Peer reviewed Peer reviewed
Cornwell, John M.; Ladd, Robert T. – Educational and Psychological Measurement, 1993
Simulated data typical of those from meta analyses are used to evaluate the reliability, Type I and Type II errors, bias, and standard error of the meta-analytic procedures of Schmidt and Hunter (1977). Concerns about power, reliability, and Type I errors are presented. (SLD)
Descriptors: Bias, Computer Simulation, Correlation, Effect Size
Peer reviewed Peer reviewed
Shavelson, Richard J.; And Others – Journal of Educational Measurement, 1993
Evidence is presented on the generalizability and convergent validity of performance assessments using data from six studies of student achievement that sampled a wide range of measurement facets and methods. Results at individual and school levels indicate that task-sampling variability is the major source of measurement error. (SLD)
Descriptors: Academic Achievement, Educational Assessment, Error of Measurement, Generalizability Theory
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