This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 156
Type: Topic Contributed
Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
Sponsor: Health Policy Statistics Section
Abstract - #307312
Title: Using Multiple Control Groups as Evidence About Unobserved Biases in an Observational Study of Mental Health Care Parity
Author(s): Frank Yoon*+ and Haiden A. Huskamp and Alisa B. Busch and Sharon-Lise T. Normand
Companies: Harvard Medical School and Harvard Medical School and Harvard Medical School and Harvard Medical School and Harvard School of Public Health
Address: Dept of Health Care Policy, Boston, MA, 02115,
Keywords: Equivalence test ; Matching ; Mental health parity ; Observational study ; testing in order
Abstract:

In an observational study of policy interventions matching can control for biases on measured pre-intervention covariates, but there is invariably concern that some important covariates were not measured. We present an example from an observational study of parity for mental health benefits and its effect on spending in major health care plans, that uses two control groups to provide some evidence about unmeasured biases. We illustrate a procedure for decomposing complex hypotheses into simpler hypotheses that are tested in order of priority. The procedure first tests the difference between the intervention and first control group; then tests with the second control group; then turns to a statement concerning the degree of equivalence of the two control groups. Because the process terminates with the first insignificant test, it controls the probability of any false rejection.


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