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Shoemaker, David M. – 1970
A norm distribution consisting of test scores received by 810 college students on a 150 item dichotomously-scored four-alternative multiple-choice test was empirically estimated through several item-examinee sampling procedures. The post mortem item-sampling investigation was specifically designed to manipulate systematically the variables of…
Descriptors: Item Sampling, Multiple Choice Tests, National Norms, Norms
Shoemaker, David M. – 1970
Selected parameters for a negatively-skewed and a normally distributed normative distribution were estimated in a post-mortem item-examinee sampling investigation. Manipulated systematically were number of subtests, number of items per subtest, and number of examinees responding to each subtest. Each item-examinee sampling procedure was replicated…
Descriptors: Error Patterns, Item Sampling, Research, Sampling
Shoemaker, David M. – 1972
Investigated empirically through post mortem item-examinee sampling were the relative merits of two alternative procedures for allocating items to subtests in multiple matrix sampling and the feasibility of using the jackknife in approximating standard errors of estimate. The results indicate clearly that a partially balanced incomplete block…
Descriptors: Error of Measurement, Item Sampling, Matrices, Sampling
Mandeville, Garrett K. – 1973
An investigation is conducted which presents extensive Monte Carlo results which indicate the conditions under which a procedure using the F distribution can be used to study the robustness of the confidence interval procedures for small samples. A review of the literature is presented. Procedure uses a binary data matrix. Results indicate that…
Descriptors: Confidence Testing, Item Sampling, Literature Reviews, Monte Carlo Methods
Myerberg, N. James – 1975
The effect of stratified sampling of items on the estimation of test score distribution parameters by multiple matrix sampling was studied. Item difficulty and/or interitem correlations were the bases of stratification. Various item iniverses were created by computer simulation and sampled according to several plans. The results indicate that…
Descriptors: Computer Programs, Item Analysis, Item Sampling, Matrices
Peer reviewed Peer reviewed
Pascale, Pietro J. – Journal of Drug Education, 1976
This paper presents a procedure called multiple matrix sampling which simplifies data collection for drug incidence surveys. Advantages for the use of multiple matrix sampling with drug surveys are discussed and a practical example is outlined presenting the guidelines for a sampling plan. (Author)
Descriptors: Data Collection, Drug Abuse, Guidelines, Item Sampling
Peer reviewed Peer reviewed
Sirotnik, Kenneth; Wellington, Roger – Journal of Educational Measurement, 1977
A single conceptual and theoretical framework for sampling any configuration of data from one or more population matrices is presented, integrating past designs and discussing implications for more general designs. The theory is based upon a generalization of the generalized symmetric mean approach for single matrix samples. (Author/CTM)
Descriptors: Analysis of Variance, Data Analysis, Item Sampling, Mathematical Models
Peer reviewed Peer reviewed
van der Linden, Wim J. – Applied Psychological Measurement, 1979
The restrictions on item difficulties that must be met when binomial models are applied to domain-referenced testing are examined. Both a deterministic and a stochastic conception of item responses are discussed with respect to difficulty and Guttman-type items. (Author/BH)
Descriptors: Difficulty Level, Item Sampling, Latent Trait Theory, Mathematical Models
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Estes, Carole; Estes, Gary D. – 1980
Multiple matrix sampling is a sampling design in which both test items and examinees are randomly sampled from their respective populations. This study was designed to develop and assess a method for computing an estimate of a correlation coefficient when a multiple matrix sampling design is used. The examinee populations included 212 third-grade…
Descriptors: Correlation, Elementary Secondary Education, Evaluation Methods, Grade 3
Scheetz, James P.; Forsyth, Robert A. – 1977
Empirical evidence is presented related to the effects of using a stratified sampling of items in multiple matrix sampling on the accuracy of estimates of the population mean. Data were obtained from a sample of 600 high school students for a 36-item mathematics test and a 40-item vocabulary test, both subtests of the Iowa Tests of Educational…
Descriptors: Achievement Tests, Difficulty Level, Item Analysis, Item Sampling
Pandey, Tej N. – 1978
The concept under investigation was the reliability of estimates of mean scores of groups under various assumptions of multiple-matrix sampling when reliabilities are computed according to procedures based on generalizability theory. Four different cases were compared with respect to the generalizability coefficients depending upon whether pupils…
Descriptors: Achievement Tests, Analysis of Variance, Basic Skills, Elementary Secondary Education
Ward, Barbara – 1980
The National Assessment of Educational Progress (NAEP) has completed two assessments of mathematics, the first conducted in 1972-73 and the second during 1977-78. Each assessment surveyed the mathematics achievement of American 9-, 13-, and 17-year-olds, using a deeply stratified, multi-stage probability sample design. This report documents…
Descriptors: Academic Achievement, Data Analysis, Data Collection, Educational Assessment
Beaton, Albert E. – 1987
In 1982, the Educational Testing Service (ETS) proposed to implement a new, complex design for the National Assessment of Educational Progress (NAEP). The major features of this design are described in "A New Design for a New Era" (Messick, Beaton, and Lord, 1983). The purpose of this document is to describe the actual implementation of…
Descriptors: Academic Achievement, Data Analysis, Data Collection, Data Interpretation
Penfield, Douglas A. – 1972
Thirty-four papers on educational statistics which were presented at the 1971 AERA Conference are summarized. Six major interest areas are covered: (a) general information; (b) non-parametric methods; (c) errors of measurement and correlation techniques; (d) regression theory; (e) univariate and multivariate analysis; (f) factor analysis. (MS)
Descriptors: Analysis of Variance, Bayesian Statistics, Behavioral Science Research, Computers