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Peer reviewedAxelson, Julein M. – Journal of Nutrition Education, 1984
Used data from nutrient intake recall divided according to body weight to demonstrate how variance in measurement may lead to incorrect conclusions in evaluation of nutrition education. Demonstrates need for incorporating methods of minimizing effects of measurement error, advocating random assignment to groups or statistical control if random…
Descriptors: Body Weight, Data Analysis, Error of Measurement, High Schools
Peer reviewedWilliams, Richard H.; And Others – Journal of Experimental Education, 1984
This paper describes the procedures and results of two studies designed to yield empirical comparisons of the error magnitude in three change measures: the simple gain score, the residualized difference score, and the base free measure (Tucker et al). Residualized scores possessed smaller standard errors of measurement. (Author/BS)
Descriptors: Achievement Gains, Achievement Tests, Algebra, Error of Measurement
Peer reviewedLord, Frederic M. – Psychometrika, 1983
Given known item parameters for a test, unbiased estimators are derived for an examinee's ability parameter, his or her proportion correct true score for the variances of these parameters and for the parallel forms reliability of the maximum likelihood estimator of the ability parameter. (Author/JKS)
Descriptors: Error of Measurement, Estimation (Mathematics), Item Analysis, Latent Trait Theory
Brick, Mike; Kim, Kwang; Nolin, Mary Jo; Collins, Mary – 1996
The National Household Education Survey (NHES) is a data collection system of the National Center for Education Statistics (NCES) designed to address a wide range of education-related issues. It is a telephone survey of the noninstitutionalized civilian population. In 1995, the NHES included a survey of adult education (AE). This report deals with…
Descriptors: Adult Education, Data Collection, Error of Measurement, Interviews
Johnson, Stephen; Dulaney, Chuck; Banks, Karen – 2000
No test, however well designed, can measure a student's true achievement because numerous factors interfere with the ability to measure achievement. These factors are sources of measurement error, and the goal in creating tests is to have as little measurement error as possible. Error can result from the test design, factors related to individual…
Descriptors: Academic Achievement, Elementary Education, Error of Measurement, Measurement Techniques
Peer reviewedLoo, Robert – Perceptual and Motor Skills, 1983
In examining considerations in determining sample sizes for factor analyses, attention was given to the effects of outliers; the standard error of correlations, and their effect on factor structure; sample heterogeneity; and the misuse of rules of thumb for sample sizes. (Author)
Descriptors: Correlation, Error of Measurement, Evaluation Methods, Factor Analysis
Peer reviewedRyan, Joseph J.; And Others – Journal of Consulting and Clinical Psychology, 1983
Wechsler Adult Intelligence Scale-Revised protocols from two vocational counseling clients were scored by 19 psychologists and 20 graduate students. Regardless of scorer's experience level, mechanical scoring error produced summary scores varying by as much as 4 to 18 IQ points. (Author/RC)
Descriptors: Error of Measurement, Graduate Students, Higher Education, Intelligence Tests
Peer reviewedBagozzi, Richard P.; Phillips, Lynn W. – Administrative Science Quarterly, 1982
Tests the "holistic construal" method of validating constructs and testing organizational hypotheses, using examples from organizational theory and data on wholesale distribution companies. Holistic construal is meant to explicitly represent theoretical and empirical concepts, nonobservational hypotheses, and correspondence rules and…
Descriptors: Charts, Error of Measurement, Holistic Approach, Hypothesis Testing
Peer reviewedHagglund, Gosta – Psychometrika, 1982
Three alternative estimation procedures for factor analysis based on the instrumental variables method are presented. Least squares estimation procedures are compared to maximum likelihood procedures. The conclusion, based on the data used in this study, is that two of the procedures seem to work well. (Author/JKS)
Descriptors: Data Analysis, Error of Measurement, Estimation (Mathematics), Factor Analysis
Peer reviewedBartz, Albert E.; Wenstrom, Lisa – Teaching of Psychology, 1981
The purpose of this survey was to identify the statistics texts most frequently used by psychology departments and to see if a typical survey of textbooks used by a partial sample of psychology departments would be accurate in describing the entire sample of departments. Partial returns resulted in a meaningful error. (RM)
Descriptors: Error of Measurement, Evaluation, Higher Education, Psychology
Peer reviewedLyon, A. J. – Physics Education, 1980
Discusses rapid, approximate methods for the calculation of errors estimates and other statistical results without using the computer. (SK)
Descriptors: College Science, Error of Measurement, Higher Education, Physics
Peer reviewedHuynh, Huynh; Saunders, Joseph C. – Journal of Educational Measurement, 1980
Single administration (beta-binomial) estimates for the raw agreement index p and the corrected-for-chance kappa index in mastery testing are compared with those based on two test administrations in terms of estimation bias and sampling variability. Bias is about 2.5 percent for p and 10 percent for kappa. (Author/RL)
Descriptors: Comparative Analysis, Error of Measurement, Mastery Tests, Mathematical Models
Peer reviewedAlwin, Duane F. – Sociometry, 1976
A structural equation model for attitude-behavior relationships is presented which conceptualizes attitude scales as congeneric measurements. The model represents a re-parameterization of an earlier one. (Author/RC)
Descriptors: Attitude Change, Attitude Measures, Behavior, Bias
Peer reviewedBan, Jae-Chun; Hanson, Bradley A.; Yi, Qing; Harris, Deborah J. – Journal of Educational Measurement, 2002
Compared three online pretest calibration scaling methods through simulation: (1) marginal maximum likelihood with one expectation maximization (EM) cycle (OEM) method; (2) marginal maximum likelihood with multiple EM cycles (MEM); and (3) M. Stocking's method B. MEM produced the smallest average total error in parameter estimation; OEM yielded…
Descriptors: Computer Assisted Testing, Error of Measurement, Maximum Likelihood Statistics, Online Systems
Peer reviewedFinch, John F.; And Others – Structural Equation Modeling, 1997
A Monte Carlo approach was used to examine bias in the estimation of indirect effects and their associated standard errors. Results illustrate the adverse effects of nonnormality on the accuracy of significance tests in latent variable models estimated using normal theory maximum likelihood statistics. (SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Maximum Likelihood Statistics, Monte Carlo Methods


