Identifier

etd-02242008-205541

Degree

Master of Arts (MA)

Department

Psychology

Document Type

Thesis

Abstract

Visual analysis is the “Gold Standard” for single-subject data because of two assumptions: a low Type I error rate and consistency across raters. However, research has shown it less reliable and accurate than desired. Autocorrelation, variability, trend, lack of obvious mean shift, and differences in the physical presentation of graphs contribute to inconsistencies and higher error rates. Statistical analysis has been advocated as a judgmental aid to visual analysis, but an appropriate statistic has not been found. In the present study, the accuracy of Hierarchical Linear Modeling was compared to raters’ visual analysis of previously published data using Receiver Operating Characteristic curves. The statistic was established as a potentially useful judgmental aid; however, definite conclusions were hindered by low power.

Date

2008

Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Frank M. Gresham

Included in

Psychology Commons

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