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Peer reviewedDutka, Solomon; Frankel, Lester R. – American Behavioral Scientist, 1993
Describes three classes of measurement techniques: (1) interviewing methods; (2) record retrieval procedures; and (3) observation methods. Discusses primary reasons for measurement error. Concludes that, although measurement error can be defined and controlled for, there are other design factors that also must be considered. (CFR)
Descriptors: Data Analysis, Data Interpretation, Higher Education, Needs Assessment
Peer reviewedGilbert, Neil – Society, 1994
Deliberations about social policy often center on estimates of harm or benefit generated by different interest groups. Problems in what is measured and how it is measured are illustrated by a discussion of research into sexual abuse and rape. Advocacy research is an unreliable foundation for social policy formation. (SLD)
Descriptors: Advocacy, Child Abuse, Computation, Data Collection
Peer reviewedHosseini, Jamshid C.; Armacost, Robert L. – American Behavioral Scientist, 1993
Maintains that the need for gathering sensitive information frequently arises in planning and implementing organizational surveys. Describes methods of designing the instrument format and the mode of data collection. Provides a description and process summary of the Randomized Response Technique (RRT). (CFR)
Descriptors: Data Analysis, Data Interpretation, Higher Education, Needs Assessment
Stapleton, David C., Ed.; Burkhauser, Richard V., Ed. – 2003
This book includes revised presentations from an October 2001 meeting of the National Institute for Disability and Rehabilitation Research and the Cornell Rehabilitation Research and Training Center that considered the validity of current data for measuring trends in the employment rate of people with disabilities and investigated the causes and…
Descriptors: Assistive Technology, Attitudes toward Disabilities, Chronic Illness, Data Interpretation


