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Marsh, Herbert W.; And Others – 1989
The purpose of the present investigation is to examine the influence of sample size (N) and model complexity on a set of 23 goodness-of-fit (GOF) indices, including those typically used in confirmatory factor analysis. The focus was on two potential problems in assessing GOF: (1) some fit indices are substantially influenced by N so that tests of…
Descriptors: Computer Simulation, Difficulty Level, Factor Analysis, Goodness of Fit
Muraki, Eiji – 1991
Multiple group factor analysis is described and illustrated through a simulation involving 5,000 examinees. The estimation process of the group factors were implemented using the TESTFACT program of Wilson and others (1987). Group factor analysis is described as a special case of confirmatory factor analysis. Group factors can be computed based on…
Descriptors: Data Analysis, Difficulty Level, Equations (Mathematics), Estimation (Mathematics)
Reckase, Mark D.; And Others – 1985
Factor analysis is the traditional method for studying the dimensionality of test data. However, under common conditions, the factor analysis of tetrachoric correlations does not recover the underlying structure of dichotomous data. The purpose of this paper is to demonstrate that the factor analyses of tetrachoric correlations is unlikely to…
Descriptors: Correlation, Difficulty Level, Factor Analysis, Item Analysis
Reckase, Mark D. – 1981
One of the major assumptions of latent trait theory is that the items in a test measure a single dimension. This report describes an investigation of procedures for forming a set of items that meet this assumption. Factor analysis, nonmetric multidimensional scaling, cluster analysis and latent trait analysis were applied to simulated and real…
Descriptors: Cluster Analysis, Difficulty Level, Factor Analysis, Guessing (Tests)
Jones, Patricia B.; And Others – 1987
In order to determine the effectiveness of multidimensional scaling (MDS) in recovering the dimensionality of a set of dichotomously-scored items, data were simulated in one, two, and three dimensions for a variety of correlations with the underlying latent trait. Similarity matrices were constructed from these data using three margin-sensitive…
Descriptors: Cluster Analysis, Correlation, Difficulty Level, Error of Measurement
Ackerman, Phillip L.; And Others – 1982
Statistical methods employed to test individual differences in dual-task performance and the existence of a general time-sharing ability are reviewed and critiqued. Specifically, both the types of data being collected and the types of data analysis procedures have been inadequate to the critical evaluation of a hypothetical…
Descriptors: Attention Control, Cognitive Processes, Difficulty Level, Factor Analysis
Muraki, Eiji – 1984
The TESTFACT computer program and full-information factor analysis of test items were used in a computer simulation conducted to correct for the guessing effect. Full-information factor analysis also corrects for omitted items. The present version of TESTFACT handles up to five factors and 150 items. A preliminary smoothing of the tetrachoric…
Descriptors: Comparative Analysis, Computer Simulation, Computer Software, Correlation
O'Hara, Takeshi; And Others – 1978
Path analysis was used to reanalyze Kropp and Stoker's data from tests designed to evaluate Bloom's taxonomy of educational objectives in the cognitive domain. Scores for 1,128 students in grades nine through twelve were analyzed separately by grade level for four content areas on six taxonomic levels. A measure of general ability was also…
Descriptors: Age Differences, Classification, Cognitive Ability, Cognitive Objectives
Bejar, Issac I. – 1976
The concept of testing for partial knowledge is considered with the concept of tailored testing. Following the special usage of latent trait theory, the word valdity is used to mean the correlation of a test with the construct the test measures. The concept of a method factor in the test is also considered as a part of the validity. The possible…
Descriptors: Achievement Tests, Adaptive Testing, Computer Assisted Testing, Confidence Testing
Tucker, Ledyard R.; And Others – 1986
A Monte Carlo study of five indices of dimensionality of binary items used a computer model that allowed sampling of both items and people. Five parameters were systematically varied in a factorial design: (1) number of common factors from one to five; (2) number of items, including 20, 30, 40, and 60; (3) sample sizes of 125 and 500; (4) nearly…
Descriptors: Correlation, Difficulty Level, Educational Research, Expectancy Tables
Benson, Jeri; Wilson, Michael – 1979
Three methods of item selection were used to select sets of 38 items from a 50-item verbal analogies test and the resulting item sets were compared for internal consistency, standard errors of measurement, item difficulty, biserial item-test correlations, and relative efficiency. Three groups of 1,500 cases each were used for item selection. First…
Descriptors: Comparative Analysis, Difficulty Level, Efficiency, Error of Measurement
Merz, William R.; Grossen, Neal E. – 1978
Six approaches to assessing test item bias were examined: transformed item difficulty, point biserial correlations, chi-square, factor analysis, one parameter item characteristic curve, and three parameter item characteristic curve. Data sets for analysis were generated by a Monte Carlo technique based on the three parameter model; thus, four…
Descriptors: Difficulty Level, Evaluation Methods, Factor Analysis, Item Analysis
Rudner, Lawrence M.; Convey, John J. – 1978
Transformed item difficulties, chi-square, item characteristic curve (icc) theory and factor score techniques were evaluated as approaches for the identification of biased test items. The study was implemented to determine whether the approaches would provide identical classifications of items as to degree of aberrance for culturally different…
Descriptors: Comparative Analysis, Culture Fair Tests, Difficulty Level, Evaluation Criteria