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Krejcie, Robert V.; Morgan, Daryle W. – Educ Psychol Meas, 1970
A formula for determining sample size, which originally appeared in 1960, has lacked a table for easy reference. This article supplies a graph of the function and a table of values which permits easy determination of the size of sample needed to be representative of a given population. (DG)
Descriptors: Data Collection, Research Methodology, Sampling, Statistical Analysis
Haywood, H. Carl – Amer J Ment Deficiency, 1970
Descriptors: Classification, Exceptional Child Research, Mental Retardation, Research Design
Clarke, Michael J.; Venezky, David L. – J Chem Educ, 1969
Descriptors: Chemistry, College Science, Instrumentation, Laboratory Equipment
Owens, Thomas R.; Stufflebeam, Daniel L. – J Educ Meas, 1969
Descriptors: Academic Ability, Item Analysis, Sampling, Statistical Analysis
Nitko, Anthony J.; Feldt, Leonard S. – Amer Educ Res J, 1969
Descriptors: Difficulty Level, Factor Analysis, Hypothesis Testing, Item Analysis
Peer reviewedMayer, John D. – Perceptual and Motor Skills, 1983
Kelly's formula estimates sampling variance of correlation corrected for attenuation by using split-half reliabilities. In some cases, coefficient alpha estimate of reliability is preferable. A simulation study suggests a variation of Kelly's formula can be used appropriately with coefficient alpha. Kelly's formula is modified to accept…
Descriptors: Correlation, Measurement Techniques, Reliability, Sampling
Peer reviewedSmith, Philip L. – Educational and Psychological Measurement, 1982
Monte Carlo methods are used to explore the accuracy of a method for establishing confidence intervals for variance component estimates in generalizability studies. Previous research has shown that variance component estimation errors due to sampling are often larger than suspected. (Author/CM)
Descriptors: Estimation (Mathematics), Monte Carlo Methods, Reliability, Research Problems
Peer reviewedCallender, John C.; Osburn, H. G. – Journal of Educational Measurement, 1979
Some procedures for estimating internal consistency reliability may be superior mathematically to the more commonly used methods such as Coefficient Alpha. One problem is computational difficulty; the other is the possibility of overestimation due to capitalization on chance. (Author/CTM)
Descriptors: Higher Education, Mathematical Formulas, Research Problems, Sampling
Wall, Terry – Library Research, 1980
Reports a study of the distribution of use among users of a short loan collection in an academic library. Results indicate the most active one-third of all users generate between two-thirds and three-quarters of all use. A brief list of references is provided. (Author/SW)
Descriptors: Academic Libraries, Information Utilization, Library Circulation, Library Research
Peer reviewedLevy, Kenneth J. – Journal of Experimental Education, 1978
The purpose of this paper is to demonstrate how many more subjects are required to achieve equal power when testing certain hypotheses concerning proportions if the randomized response technique is employed for estimating a population proportion instead of the conventional technique. (Author)
Descriptors: Experimental Groups, Hypothesis Testing, Research Design, Response Style (Tests)
Peer reviewedMyerberg, N. James – Educational and Psychological Measurement, 1979
The effect of stratified sampling of items based on item difficulty and/or interitem correlations on the estimation of test score distribution parameters using multiple matrix sampling was studied. Results indicated that stratification did not consistently improve the stability of parameter estimation. (Author/JKS)
Descriptors: Item Analysis, Item Sampling, Matrices, Technical Reports
King, Harry A. – Research Quarterly, 1978
Some statistical considerations in applying survey sampling methods to small populations are explored. (DS)
Descriptors: Error of Measurement, Program Development, Reliability, Sampling
Peer reviewedKnapp, Thomas R. – Journal of Educational Statistics, 1979
This paper presents the generalized symmetric means approach to the estimation of population covariances, complete with derivations and examples. Particular attention is paid to the problem of missing data, which is handled very naturally in the incidence sampling framework. (CTM)
Descriptors: Analysis of Covariance, Matrices, Sampling, Statistical Analysis
Peer reviewedHsu, Louis – Educational and Psychological Measurement, 1979
This paper describes an exact small sample test, and provides a table of critical values for an approximate large sample test, to determine if a sample of Likert-Type ratings indicates significant agreement or disagreement in a population of such ratings. (Author)
Descriptors: Expectancy Tables, Hypothesis Testing, Nonparametric Statistics, Rating Scales
Peer reviewedDuncan, Terry E.; Duncan, Susan C.; Alpert, Anthony; Hops, Hyman; Stoolmiller, Mike; Muthen, Bengt – Multivariate Behavioral Research, 1997
Demonstrates the use of a general model for latent variable growth analysis that takes into account cluster sampling. Multilevel Latent Growth Modeling was used to analyze longitudinal and multilevel data for adolescent and parent substance use measured at four annual time points for 435 families. (SLD)
Descriptors: Adolescents, Cluster Analysis, Longitudinal Studies, Mathematical Models


