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Millman, Jason – 1972
Procedures for establishing standards and determining the number of items needed in criterion-referenced measures are reviewed. The discussion of setting a passing score is organized around five factors: performance of others, item content, educational consequences, psychological and financial costs, and measurement error. Classical test theory,…
Descriptors: Academic Achievement, Criterion Referenced Tests, Error of Measurement, Models

Williams, Richard H.; And Others – Journal of Experimental Education, 1987
Because of limitations in simple gain scores, pychometrists have proposed alternate methods for measuring change, two of which are residualized difference and base-free change. This paper provides large sample empirical estimates of the reliability these change measures. It checks theoretical predictions derived from inequalities involving all…
Descriptors: Error of Measurement, Estimation (Mathematics), Measurement Techniques, Pretests Posttests

Bekker, Paul A.; de Leeuw, Jan – Psychometrika, 1987
Psychometricians working in factor analysis and econometricians working in regression with measurement error in all variables are both interested in the rank of dispersion matrices under variation of diagonal elements. This paper reviews both fields; points out various small errors; and presents a methodological comparision of factor analysis and…
Descriptors: Error of Measurement, Factor Analysis, Literature Reviews, Mathematical Models

Goldstein, Harvey A.; Cruze, Alvin M. – Monthly Labor Review, 1987
The article summarizes the results of an evaluation of the accuracy of statewide industry and occupational employment projections for 20 states. The authors provide some recommendations, based on evaluation results, to improve subsequent rounds of statewide projections. (CH)
Descriptors: Employment Patterns, Employment Projections, Error of Measurement, Evaluation Methods

Kingma, Johannes; Reuvekamp, Johan – Educational and Psychological Measurement, 1987
This paper describes a PASCAL program that computes both different types of transitions and learning statistics suitable for learning experiments in which a two-stage Markov model is used. The frequency counts of the different transitions are used for estimating the parameters of the two-stage Markov model. (Author/LMO)
Descriptors: Computer Software Reviews, Error of Measurement, Goodness of Fit, Input Output

Games, Paul A.; Hedges, Larry V. – Journal of Experimental Education, 1987
Variance stabilizing transformations yield statistics whose standard errors are only influenced by the number of observations on which they are based. A solution that can be extended to inference on all of these parameters is presented and illustrated via three examples. (TJH)
Descriptors: Correlation, Error of Measurement, Least Squares Statistics, Multivariate Analysis

Zimmerman, Donald W. – Educational and Psychological Measurement, 1985
A computer program simulated guessing on multiple-choice test items and calculated deviation IQ's from observed scores which contained a guessing component. Extensive variability in deviation IQ's due entirely to chance was found. (Author/LMO)
Descriptors: Computer Simulation, Error of Measurement, Guessing (Tests), Intelligence Quotient

Reichardt, Charles; Gollob, Harry – New Directions for Program Evaluation, 1986
Causal models often omit variables that should be included, use variables that are measured fallibly, and ignore time lags. Such practices can lead to severely biased estimates of effects. The discussion explains these biases and shows how to take them into account. (Author)
Descriptors: Effect Size, Error of Measurement, High Schools, Mathematical Models

Stevens, Joseph J.; Aleamoni, Lawrence, M. – Educational and Psychological Measurement, 1986
Prior standardization of scores when an aggregate score is formed has been criticized. This article presents a demonstration of the effects of differential weighting of aggregate components that clarifies the need for prior standardization. The role of standardization in statistics and the use of aggregate scores in research are discussed.…
Descriptors: Correlation, Error of Measurement, Factor Analysis, Raw Scores

Haase, Richard F. – Educational and Psychological Measurement, 1986
This paper describes a BASIC computer program that computes power for any combination of effect size, degrees of freedom for hypothesis, degrees of freedom for error, and alpha level. As a consequence of the algorithm, an approximation to the critical value of the Bonferroni F-test is also computed. (Author/JAZ)
Descriptors: Analysis of Variance, Effect Size, Error of Measurement, Input Output

Hartman, Bruce W.; And Others – Journal of Experimental Education, 1986
The detrimental effects of nonresponse bias are particularly significant given the widespread use of the survey data collection method in educational surveys. Current methods for remediating nonresponse bias in educational surveys are explored and critiqued. (Author/LMO)
Descriptors: Data Collection, Educational Assessment, Elementary Secondary Education, Error of Measurement

Seddon, G.M. – Journal of Educational Measurement, 1983
A method is described of deriving two alternative measures of divergent thinking ability as a single entity (avoiding the spurious effects of fluency) from student responses to open-ended questions traditionally used in tests of divergent thinking ability. (PN)
Descriptors: Creativity, Creativity Tests, Divergent Thinking, Error of Measurement

Olejnik, Stephen F. – Journal of Experimental Education, 1984
This paper discusses the sample size problem and four factors affecting its solution: significance level, statistical power, analysis procedure, and effect size. The interrelationship between these factors is discussed and demonstrated by calculating minimal sample size requirements for a variety of research conditions. (Author)
Descriptors: Effect Size, Error of Measurement, Hypothesis Testing, Research Design
van der Linden, Wim J. – 2002
Traditionally, error in equating observed scores on two versions of a test is defined as the difference between the transformations that equate the quantiles of their distributions in the sample and in the population of examinees. This definition underlies, for example, the well-known approximation to the standard error of equating by Lord (1982).…
Descriptors: College Entrance Examinations, Equated Scores, Error of Measurement, Estimation (Mathematics)
Tamada, Mike – 2002
National studies of students, and studies that compare institutions, have identified many predictors of students' graduation rates, including socioeconomic status and admission selectivity. When there predictive variables are applied to data from an individual school, it may be found that they have less predictive power. This paper presents a…
Descriptors: College Graduates, Error of Measurement, Graduation Rate, Higher Education