ERIC Number: ED129871
Record Type: Non-Journal
Publication Date: 1976-Apr
Pages: 17
Abstractor: N/A
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: N/A
Estimating Bias in Test Items Utilizing Principal Components Analysis and the General Linear Solution.
Merz, William R.
A number of methods have been used to identify potentially biased items within a test. These methods examine one item at a time and do not deal with the complex interrelationships among items or among items and the potentially biasing elements. The use of multivariate procedures to assess whether or not items are biased and to obtain clues about the source of the bias are demonstrated here. A total of 1,294 six and seven year old children from five ethnic groups took the Goodenough-Harris Drawing Test. Principal components analysis and analysis of variance were performed on the results. Other analysis methods are suggested, and are presently being studied. (Author/BW)
Descriptors: American Indians, Analysis of Variance, Anglo Americans, Blacks, Elementary School Students, Ethnic Groups, Factor Analysis, Factor Structure, Item Analysis, Mexican Americans, Multiple Regression Analysis, Orthogonal Rotation, Projective Measures, Racial Discrimination, Statistical Analysis, Test Bias, Test Items
Publication Type: Reports - Research
Education Level: N/A
Audience: N/A
Language: N/A
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Goodenough Harris Drawing Test
Grant or Contract Numbers: N/A
Author Affiliations: N/A