Publication Date
| In 2026 | 0 |
| Since 2025 | 17 |
| Since 2022 (last 5 years) | 141 |
| Since 2017 (last 10 years) | 360 |
| Since 2007 (last 20 years) | 1002 |
Descriptor
Source
Author
| Rousseau, Ronald | 20 |
| Egghe, L. | 14 |
| Gordon, Sheldon P. | 11 |
| Egghe, Leo | 9 |
| Burrell, Quentin L. | 8 |
| Chen, Hongwei | 7 |
| Lord, Frederic M. | 7 |
| Mathews, John H. | 7 |
| Ayoub, Ayoub B. | 6 |
| Dana-Picard, Thierry | 6 |
| Lockwood, Elise | 6 |
| More ▼ | |
Publication Type
Education Level
Audience
| Practitioners | 355 |
| Teachers | 340 |
| Administrators | 50 |
| Researchers | 46 |
| Students | 33 |
| Policymakers | 11 |
| Media Staff | 2 |
Location
| Australia | 46 |
| Turkey | 18 |
| Indonesia | 12 |
| South Africa | 10 |
| United Kingdom | 10 |
| California | 9 |
| Spain | 9 |
| China | 8 |
| Netherlands | 8 |
| Canada | 7 |
| Italy | 7 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
| Does not meet standards | 1 |
Peer reviewedTerrell, Colin D. – Educational and Psychological Measurement, 1982
A table is presented that directly converts any known point biserial coefficient to the biserial coefficient, providing the largest proportion of the dichotomous variable is also known. (Author)
Descriptors: Computation, Correlation, Data Analysis, Mathematical Formulas
Peer reviewedVegelius, Jan – Educational and Psychological Measurement, 1981
The G index is a measure of the similarity between individuals over dichotomous items. Some tests for the G-index are described. For each case an example is included. (Author/GK)
Descriptors: Hypothesis Testing, Mathematical Formulas, Mathematical Models, Nonparametric Statistics
Peer reviewedRaju, Nambury S. – Psychometrika, 1979
An important relationship is given for two generalizations of coefficient alpha: (1) Rajaratnam, Cronbach, and Gleser's generalizability formula for stratified-parallel tests, and (2) Raju's coefficient beta. (Author/CTM)
Descriptors: Item Analysis, Mathematical Formulas, Test Construction, Test Items
Peer reviewedBlair, R. Clifford; Higgins, James J. – Journal of Educational Statistics, 1980
Monte Carlo techniques were used to compare the power of Wilcoxon's rank-sum test to the power of the two independent means t test for situations in which samples were drawn from (1) uniform, (2) Laplace, (3) half-normal, (4) exponential, (5) mixed-normal, and (6) mixed-uniform distributions. (Author/JKS)
Descriptors: Data Analysis, Hypothesis Testing, Mathematical Formulas, Nonparametric Statistics
Peer reviewedBradshaw, Charles W., Jr. – Educational and Psychological Measurement, 1980
Two alternative procedures to Rogers' method of using control charts to display item statistics are discussed. The data itself determines limit and centerline values, thus permitting these values to be compared to any criterion difficulty level(s) deemed appropriate for a given set of test items. (Author/RL)
Descriptors: Flow Charts, Item Analysis, Mathematical Formulas, Quality Control
Peer reviewedDe Leeuw, Jan; Pruzansky, Sandra – Psychometrika, 1978
A computational method for weighted euclidean distance scaling (a method of multidimensional scaling) which combines aspects of an "analytic" solution with an approach using loss functions is presented. (Author/JKS)
Descriptors: Computer Programs, Mathematical Formulas, Mathematical Models, Multidimensional Scaling
Peer reviewedAlba, Richard D. – American Behavioral Scientist, 1981
Cites the importance of computers and of mathematical graph theory in describing the key features of group structures and compares research based on these methods to research carried out by social psychologists in the 1940s and 1950s. Identifies major problems in the collection of network data about large groups whose boundaries are not…
Descriptors: Behavioral Science Research, Computers, Group Dynamics, Mathematical Formulas
Peer reviewedRaaijmakers, Jeroen G. W.; Shiffrin, Richard M. – Psychological Review, 1981
A general theory of retrieval from long-term memory which combines features of associative network models and random search models is presented. It posits cue-dependent probabilistic sampling and recovery from an associative network, but the network is specified as a retrieval structure rather than a storage structure. (Author/JKS)
Descriptors: Association (Psychology), Epistemology, Mathematical Formulas, Memory
Peer reviewedWakefield, James A., Jr. – Educational and Psychological Measurement, 1980
Studies in applied behavior analysis have used two expressions of reliability for human observations: percentage agreement and correlational techniques (including the phi coefficient). Formulas for converting percentage agreement scores to phi coefficients and vice versa are presented. (Author/RL)
Descriptors: Behavioral Science Research, Comparative Analysis, Correlation, Mathematical Formulas
Peer reviewedTa Lin Liau; Bassin, Carolyn B. – Journal of Reading Behavior, 1976
Reports four new readability formulas which account for a higher percentage of variance than the Coleman formulas and which can also be used for readers below college level.
Descriptors: Higher Education, Mathematical Formulas, Measurement, Readability
Peer reviewedAizawa, Akiko – Information Processing & Management, 2003
Presents a mathematical definition of the probability-weighted amount of information (PWI), a measure of term specificity in documents that is based on an information-theoretic view of retrieval events. Corresponds with the term frequency-inverse document frequency (tf-idf) measures that are used in information retrieval systems. (Author/LRW)
Descriptors: Information Retrieval, Mathematical Formulas, Measurement Techniques, Probability
Peer reviewedEgghe, Leo; Rousseau, Ronald – Journal of the American Society for Information Science and Technology, 2003
Discusses graph theory in information science, focusing on measures for the cohesion of networks. Illustrates how a set of weights between connected nodes can be transformed into a set of dissimilarity measures and presents an example of the new compactness measures for a cocitation and a bibliographic coupling network. (Author/LRW)
Descriptors: Bibliographic Coupling, Citations (References), Information Science, Mathematical Formulas
Peer reviewedLaird, Nan M.; Louis, Thomas A. – Journal of Educational Statistics, 1989
Based on the Gaussian model, methods for using measurements that depend on the true attribute to compute rankings are proposed and compared. Measurements based on an empirical Bayes model produce estimates that differ from ranking observed data. Ranking methods are illustrated with school achievement data. (TJH)
Descriptors: Bayesian Statistics, Class Rank, Mathematical Formulas, Mathematical Models
Peer reviewedBartell, Brian T.; And Others – Journal of the American Society for Information Science, 1995
Discussion of the failure of individual keywords to identify conceptual content of documents in retrieval systems highlights Metric Similarity Modeling, a method for creating vector space representation of documents based on modeling target interdocument similarity values. Semantic relatedness, latent semantic indexing, an indexing and retrieval…
Descriptors: Algorithms, Databases, Documentation, Indexing
Peer reviewedAkman, K. Ibhrahim – Journal of Information Science, 1995
Describes a new data compression technique that utilizes the common morphological structure of languages. Topics include classification of languages and their morphological structure; structured text compression; the algorithm and an example using Turkish; theoretical implications; and implementation. (LRW)
Descriptors: Algorithms, Language Classification, Mathematical Formulas, Morphology (Languages)


