Publication Date
| In 2026 | 0 |
| Since 2025 | 229 |
| Since 2022 (last 5 years) | 1561 |
| Since 2017 (last 10 years) | 4616 |
| Since 2007 (last 20 years) | 12033 |
Descriptor
| Factor Analysis | 17998 |
| Foreign Countries | 6663 |
| Correlation | 3906 |
| Measures (Individuals) | 3351 |
| Factor Structure | 3342 |
| Questionnaires | 3234 |
| Statistical Analysis | 3142 |
| Test Validity | 2936 |
| Student Attitudes | 2820 |
| Psychometrics | 2400 |
| Test Reliability | 2296 |
| More ▼ | |
Source
Author
Publication Type
Education Level
Audience
| Researchers | 276 |
| Practitioners | 85 |
| Teachers | 51 |
| Administrators | 40 |
| Policymakers | 22 |
| Counselors | 18 |
| Students | 16 |
| Parents | 3 |
| Community | 1 |
| Support Staff | 1 |
Location
| Turkey | 1093 |
| China | 451 |
| Australia | 422 |
| United States | 300 |
| Taiwan | 287 |
| Canada | 286 |
| Hong Kong | 227 |
| Spain | 226 |
| Germany | 206 |
| South Korea | 203 |
| Netherlands | 198 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
| Meets WWC Standards without Reservations | 6 |
| Meets WWC Standards with or without Reservations | 7 |
| Does not meet standards | 3 |
Druva, Cynthia Ann – 1985
Order Analysis is a multidimensional scaling (MDS) technique for determining order among items. This paper reviews articles by different authors describing various components of ordering theory. A common nomenclature is constructed to link together the various ideas and is applied to a fairly simple set of data. Topics discussed include a more…
Descriptors: Analysis of Variance, Developmental Stages, Factor Analysis, Learning Theories
Rubba, P. A.; Bakar, K. H. A. – 1985
The Science Teacher Inventory of Need (STIN) was developed specifically to assess the perceived needs of science teachers in developing nations. The purpose of this reported study was to apply factor analysis to the perceived needs data collected from a sample of Malaysian secondary science teachers in order to clarify further the factorial…
Descriptors: Construct Validity, Developing Nations, Educational Testing, Factor Analysis
Hambleton, Ronald K.; Rovinelli, Richard J. – 1986
Four methods for determining the dimensionality of a set of test items were compared: (1) linear factor analysis; (2) residual analysis; (3) nonlinear factor analysis; and (4) Bejar's method. Five artificial test data sets (for 40 items and 1500 examinees) were generated, consistent with the three-parameter logistic model and the assumption of…
Descriptors: Comparative Analysis, Computer Simulation, Correlation, Factor Analysis
Barbour, Ross Patrick – 1983
The question of dividing language proficiency into components was explored by determining which of three models best fit the experimental data: a model postulating numerous specific sources of variance (the extreme divisible model), one postulating a single, large source of variance (the unitary model), or one postulating a large general factor…
Descriptors: Comparative Analysis, English (Second Language), Factor Analysis, Language Proficiency
Sudlow, Robert E. – 1985
Although the topic of effective schools is a popular one among today's educators, researchers, and publishers, there still is no commonly agreed upon definition of an effective school. One definition given by Ronald Edmonds and Lawrence Lezotte is notably precise, measurable, attainable, and easy to determine. They defined an effective school as…
Descriptors: Academic Achievement, Academic Standards, Definitions, Elementary Secondary Education
Elmore, Patricia B.; Woehlke, Paula L. – 1988
Periodic summaries of research techniques used in important journals help professors of educational research teach each new generation of researchers. Literature published in "American Educational Research Journal" (AERJ), "Educational Researcher" (ER), and "Review of Educational Research (RER) is reviewed for the 10-year…
Descriptors: Content Analysis, Educational Research, Evaluation Methods, Factor Analysis
Byrne, Barbara M. – 1988
Confirmatory Factor Analysis (CFA; LISREL) was used to: (1) validate the Self Description Questionnaire III (SDQ III) subscales measuring general, school, English, and mathematics self-concepts for a sample of 898 (285 low track and 613 high track) students in grades 11 and 12, and (2) test the equivalency of the factor structure across academic…
Descriptors: Factor Analysis, Grade 11, Grade 12, High School Students
Wober, J. M. – 1986
In July 1984, British Channel 4 began televising Case on Camera, a series based on genuine arbitration of civil cases carried out by a retired judge, recorded as it happened, and edited into half hour programs. Because of the Independent Broadcasting Authority's concern for the rights to privacy, a systematic study of public reaction to the series…
Descriptors: Arbitration, Audience Analysis, Broadcast Industry, Court Judges
Perkins, Kyle – 1987
In this paper four classes of procedures for measuring the instructional sensitivity of reading comprehension test items are reviewed. True experimental designs are not recommended because some of the most important reading comprehension variables do not lend themselves to experimental manipulation. "Ex post facto" factorial designs are…
Descriptors: Bayesian Statistics, Correlation, Elementary Secondary Education, Evaluation Methods
Marsh, Herbert W.; And Others – 1988
Data from the authors' previous research (1979, 1980, 1987), consisting of responses to five masculinity-femininity (M-F), two esteem, and two social desirability instruments, were reanalyzed. The subjects were 104 male and 133 female college students who completed the: Bem Sex Role Inventory, Personal Attributes Questionnaire, ANDRO instrument…
Descriptors: Androgyny, College Students, Construct Validity, Factor Analysis
Hedl, John J., Jr. – 1983
Previous factor studies of the Beck Depression Inventory (BDI) have not analyzed the item data as a function of sex, or reported more than one factor solution. To further study the factor structure of the BDI, items were factor analyzed and multiple solutions were examined for simple structure, parsimony, and psychological meaningfulness. A sample…
Descriptors: College Students, Depression (Psychology), Emotional Problems, Factor Analysis
Gariepy, Jean-Louis; Kindermann, Thomas – 1989
Addressing a common problem in the analysis of social networks, this study describes quantitative techniques for identifying social subgroups using individual perceptions of social affinities within natural groups. Compared are four analytic methods for abstracting composite representations of sub-structures. These methods, formally evaluated…
Descriptors: Elementary Education, Factor Analysis, Grade 7, Identification
Carr, Sonya C. – 1989
This paper briefly explains the possible two-mode techniques of factor analysis, and discusses, in more detail, one two-mode technique--the Q-technique. The Q-technique may be useful when the researcher is interested in obtaining information about "types" of individuals with regard to certain variables. A concrete heuristic example is used to…
Descriptors: Cluster Analysis, Data Interpretation, Emotional Disturbances, Factor Analysis
Knol, Dirk L.; Berger, Martijn P. F. – 1988
Many multidimensional item response theory (IRT) models have been proposed. A comparison is made between the so-called full information models and the models that use only pairwise information. Three multidimensional models described are: (1) the compensatory model of R. D. Bock and M. Aitken (1981) using the computer program TESTFACT; (2) a model…
Descriptors: Comparative Analysis, Computer Simulation, Computer Uses in Education, Factor Analysis
O'Neal, Marcia R.; And Others – 1988
The factorial validity of four of the nine Fennema-Sherman Mathematics Attitudes Scales (FSMASs) was examined for use in measuring fifth graders' interaction with a subject. The following four scales were assessed: (1) the Confidence in Learning Mathematics Scale; (2) the Attitude Toward Success in Mathematics Scale (ATSMS); (3) the Mathematics…
Descriptors: Elementary School Mathematics, Elementary School Students, Factor Analysis, Grade 5


