Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 0 |
Since 2006 (last 20 years) | 1 |
Descriptor
Mathematical Models | 14 |
Monte Carlo Methods | 14 |
Statistical Distributions | 14 |
Computer Simulation | 7 |
Equations (Mathematics) | 6 |
Sample Size | 4 |
Estimation (Mathematics) | 3 |
Maximum Likelihood Statistics | 3 |
Power (Statistics) | 3 |
Comparative Analysis | 2 |
Correlation | 2 |
More ▼ |
Source
Educational and Psychological… | 3 |
Applied Psychological… | 2 |
Applied Measurement in… | 1 |
International Journal for the… | 1 |
Journal of Educational… | 1 |
Psychometrika | 1 |
Author
Publication Type
Reports - Evaluative | 12 |
Journal Articles | 9 |
Speeches/Meeting Papers | 6 |
Reports - Descriptive | 1 |
Reports - Research | 1 |
Education Level
Higher Education | 1 |
Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Kulick, George; Wright, Ronald – International Journal for the Scholarship of Teaching and Learning, 2008
Grading on the curve is a common practice in higher education. While there are many critics of the practice it still finds wide spread acceptance particularly in science classes. Advocates believe that in large classes student ability is likely to be normally distributed. If test scores are also normally distributed instructors and students tend…
Descriptors: Grading, Higher Education, Scores, Outcomes of Education

Snijders, Tom A. B. – Psychometrika, 1991
A complete enumeration method and a Monte Carlo method are presented to calculate the probability distribution of arbitrary statistics of adjacency matrices when these matrices have the uniform distribution conditional on given row and column sums, and possibly on a given set of structural zeros. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Mathematical Models, Matrices

Fowler, Robert L. – Applied Psychological Measurement, 1992
A Monte Carlo simulation explored how to optimize power in the extreme groups strategy when sampling from nonnormal distributions. Results show that the optimum percent for the extreme group selection was approximately the same for all population shapes, except the extremely platykurtic (uniform) distribution. (SLD)
Descriptors: Construct Validity, Equations (Mathematics), Mathematical Models, Monte Carlo Methods
Monte Carlo Based Null Distribution for an Alternative Goodness-of-Fit Test Statistic in IRT Models.

Stone, Clement A. – Journal of Educational Measurement, 2000
Describes a goodness-of-fit statistic that considers the imprecision with which ability is estimated and involves constructing item fit tables based on each examinee's posterior distribution of ability, given the likelihood of the response pattern and an assumed marginal ability distribution. Also describes a Monte Carlo resampling procedure to…
Descriptors: Goodness of Fit, Item Response Theory, Mathematical Models, Monte Carlo Methods

Noonan, Brian W.; And Others – Applied Psychological Measurement, 1992
Studied the extent to which three appropriateness indexes, Z(sub 3), ECIZ4, and W, are well standardized in a Monte Carlo study. The ECIZ4 most closely approximated a normal distribution, and its skewness and kurtosis were more stable and less affected by test length and item response theory model than the others. (SLD)
Descriptors: Comparative Analysis, Item Response Theory, Mathematical Models, Maximum Likelihood Statistics
Wang, Yuh-Yin Wu; Schafer, William D. – 1993
This Monte-Carlo study compared modified Newton (NW), expectation-maximization algorithm (EM), and minimum Cramer-von Mises distance (MD), used to estimate parameters of univariate mixtures of two components. Data sets were fixed at size 160 and manipulated by mean separation, variance ratio, component proportion, and non-normality. Results…
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
Sawilowsky, Shlomo S.; Hillman, Stephen B. – 1991
Psychology studies often have low statistical power. Sample size tables, as given by J. Cohen (1988), may be used to increase power, but they are based on Monte Carlo studies of relatively "tame" mathematical distributions, as compared to psychology data sets. In this study, Monte Carlo methods were used to investigate Type I and Type II…
Descriptors: Mathematical Models, Monte Carlo Methods, Power (Statistics), Psychological Studies

Broodbooks, Wendy J.; Elmore, Patricia B. – Educational and Psychological Measurement, 1987
The effects of sample size, number of variables, and population value of the congruence coefficient on the sampling distribution of the congruence coefficient were examined. Sample data were generated on the basis of the common factor model, and principal axes factor analyses were performed. (Author/LMO)
Descriptors: Factor Analysis, Mathematical Models, Monte Carlo Methods, Predictor Variables
Kaplan, David – 1993
The impact of the use of data arising from balanced incomplete block (BIB) spiralled designs on the chi-square goodness-of-fit test in factor analysis is considered. Data from BIB designs posses a unique pattern of missing data that can be characterized as missing completely at random (MCAR). Standard approaches to factor analyzing such data rest…
Descriptors: Chi Square, Computer Simulation, Correlation, Factor Analysis
Ankenmann, Robert D.; Stone, Clement A. – 1992
Effects of test length, sample size, and assumed ability distribution were investigated in a multiple replication Monte Carlo study under the 1-parameter (1P) and 2-parameter (2P) logistic graded model with five score levels. Accuracy and variability of item parameter and ability estimates were examined. Monte Carlo methods were used to evaluate…
Descriptors: Computer Simulation, Estimation (Mathematics), Item Bias, Mathematical Models
Chou, Tungshan; Huberty, Carl J. – 1992
The empirical performance of the technique proposed by P. O. Johnson and J. Neyman (1936) (the JN technique) and the modification of R. F. Potthoff (1964) was studied in simulated data settings. The robustness of the two JN techniques was investigated with respect to their ability to control Type I and Type III errors. Factors manipulated in the…
Descriptors: Analysis of Variance, Computer Simulation, Equations (Mathematics), Error Patterns

Brown, R. L. – Educational and Psychological Measurement, 1992
A Monte Carlo study explores the robustness assumption in structural equation modeling of using a full information normal theory generalized least-squares estimation procedure on Type I censored data. The efficacy of the following proposed alternate estimation procedures is assessed: asymptotically distribution free estimator and a latent…
Descriptors: Computer Simulation, Equations (Mathematics), Estimation (Mathematics), Least Squares Statistics

Schiel, Jeffrey L.; Shaw, Dale G. – Applied Measurement in Education, 1992
Changes in information retention resulting from changes in reliability and number of intervals in scale construction were studied to provide quantitative information to help in decisions about choosing intervals. Information retention reached a maximum when the number of intervals was about 8 or more and reliability was near 1.0. (SLD)
Descriptors: Decision Making, Knowledge Level, Mathematical Models, Monte Carlo Methods

Fowler, Robert L.; Clingman, Joy M. – Educational and Psychological Measurement, 1992
Monte Carlo techniques are used to examine the power of the "B" statistic of R. L. Brennan (1972) to detect negatively discriminating items drawn from a variety of nonnormal population distributions. A simplified procedure is offered for conducting an item-discrimination analysis on typical classroom objective tests. (SLD)
Descriptors: Classroom Techniques, Elementary Secondary Education, Equations (Mathematics), Item Analysis