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ERIC Number: EJ797556
Record Type: Journal
Publication Date: 2008
Pages: 28
Abstractor: As Provided
Reference Count: 15
ISSN: ISSN-1076-9986
Bias Mechanisms in Intention-to-Treat Analysis with Data Subject to Treatment Noncompliance and Missing Outcomes
Jo, Booil
Journal of Educational and Behavioral Statistics, v33 n2 p158-185 2008
An analytical approach was employed to compare sensitivity of causal effect estimates with different assumptions on treatment noncompliance and non-response behaviors. The core of this approach is to fully clarify bias mechanisms of considered models and to connect these models based on common parameters. Focusing on intention-to-treat analysis, systematic model comparisons are performed on the basis of explicit bias mechanisms and connectivity between models. The method is applied to the Johns Hopkins school intervention trial, where assessment of the intention-to-treat effect on school children's mental health is likely to be affected by assumptions about intervention noncompliance and nonresponse at follow-up assessments. The example calls attention to the importance of focusing on each case in investigating relative sensitivity of causal effect estimates with different identifying assumptions, instead of pursuing a general conclusion that applies to every occasion. (Contains 5 tables and 4 figures.)
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Evaluative
Education Level: Elementary Education; Grade 1
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A