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Peer reviewedSullins, Walter L. – Contemporary Education, 1973
Descriptors: Educational Research, Monte Carlo Methods, Probability, Research Methodology
Peer reviewedElshout, Jan J.; Roe, Robert A. – Educational and Psychological Measurement, 1973
Paper covers the first part of a study that is concerned with the inferential accuracy of the formulas that have been developed to correct'' several sample statistics for the effects of restriction of range. (Authors)
Descriptors: Mathematical Applications, Measurement Techniques, Sampling, Statistical Analysis
Marlin, Marjorie; Biddle, Bruce J. – Comp Educ Rev, 1970
Data processing problems encountered in a comparative study of teacher roles are discussed. (DB)
Descriptors: Analysis of Variance, Data Processing, Questionnaires, Sampling
Peer reviewedBolding, James T. – Educational and Psychological Measurement, 1972
Descriptors: Computer Programs, Data Processing, Models, Multiple Regression Analysis
Peer reviewedMoore, P. G. – Mathematical Spectrum, 1971
Descriptors: Probability, Public Opinion, Sampling, Statistical Bias
Peer reviewedSirotnik, Ken – Educational and Psychological Measurement, 1970
Descriptors: Analysis of Variance, Item Sampling, Mathematical Models, Statistical Analysis
Games, Paul A. – Educ Psychol Meas, 1969
One in a series of nine articles in a section entitled, "Electronic Computer Program and Accounting Machine Procedures.
Descriptors: Computer Programs, Data Analysis, Programing Languages, Sampling
Peer reviewedBurnett, J. Dale – Canadian Journal of Education, 1983
Illustrates the basic concepts of the loglinear approach to research analysis. Explains what type of research questions are answerable and what type of data will lend itself to a loglinear analysis approach. Three educational research examples illustrate this concept. (TLJ)
Descriptors: Data, Educational Researchers, Models, Research Tools
Peer reviewedGold, Robert S.; And Others – Journal of School Health, 1983
This article examines the utility of multi-matrix sampling as a technique in health education research that permits collection of large quantities of data without lengthy questionnaires or excessive time demands on respondents. Advantages and limitations of multi-matrix sampling are delineated through a hypothetical example. (Authors/CJ)
Descriptors: Data Collection, Health Education, Item Sampling, Matrices
Peer reviewedFriedman, Herbert – Educational and Psychological Measurement, 1982
A concise table is presented based on a general measure of magnitude of effect which allows direct determinations of statistical power over a practical range of values and alpha levels. The table also facilitates the setting of the research sample size needed to provide a given degree of power. (Author/CM)
Descriptors: Hypothesis Testing, Power (Statistics), Research Design, Sampling
Peer reviewedLuftig, Jeffrey T.; Norton, Willis P. – Journal of Studies in Technical Careers, 1982
This article builds on an earlier discussion of the importance of the Type II error (beta) and power to the hypothesis testing process (CE 511 484), and illustrates the methods by which sample size calculations should be employed so as to improve the research process. (Author/CT)
Descriptors: Hypothesis Testing, Research Design, Research Methodology, Research Problems
Peer reviewedSchautz, Donna; Lindeman, Carol, A. – Journal of Nursing Administration, 1982
The authors use examples to illustrate how the design of a study conveys the overall strategy and soundness of the investigation. Elements of research design that are discussed include setting, subjects, sample, treatment, measurement, and communication of results. (CT)
Descriptors: Data Analysis, Measurement Techniques, Research Design, Research Methodology
Peer reviewedRubin, Donald B. – Journal of Educational Statistics, 1978
A simple example is presented that illustrates advantages of Bayesian and likelihood methods of inference relative to sampling distribution methods of inference. It is argued that Bayesian and likelihood methods of inference should be utilized more generally to analyze real data. (Author/CTM)
Descriptors: Bayesian Statistics, Hypothesis Testing, Sampling, Statistical Data
Peer reviewedLee, Sik-Yum; Song, Xin-Yuan – Psychometrika, 2003
Proposed a new nonlinear structural equation model with fixed covariates to deal with some complicated substantive theory and developed a Bayesian path sampling procedure for model comparison. Illustrated the approach with an illustrative example using data from an international study. (SLD)
Descriptors: Bayesian Statistics, Comparative Analysis, Sampling, Structural Equation Models
Peer reviewedSutton, Gordon F. – Society, 1997
Explores whether sampling is better than head count for census taking and if there is a genuine undercount distinct from "floating" populations. Discusses whether the census should accommodate the various interests who have addressed the question of the quality of enumeration, as well as the larger responsibilities of demographers for…
Descriptors: Census Figures, Computation, Demography, Population Distribution


