### Department of Biostatistics Seminar/Workshop Series

# Evaluating Subunit Diagnostic Tests by Weighted GEE

## Carol Lin, MPH, PhD

### Quantitative Sciences and Data Management Branch NCHHSTP

### Wednesday, June 11, 1:30-2:30pm, MRBIII Conference Room 1220

### Intended Audience: Persons interested in applied statistics, statistical theory, epidemiology, health services research, clinical trials methodology, statistical computing, statistical graphics, R users or potential users

Sensitivity and specificity are common measures used to evaluate
the performance of a diagnostic test. A diagnostic test is often
administrated at a subunit level, e.g. at the level of vessel, ear
or eye of a patient so that the treatment can be targeted at the
specific subunit. Therefore, it is essential to evaluate the
diagnostic test at the subunit level. Often patients with more
negative subunit test results are less likely to receive the gold
standard tests than patients with more positive subunit test
results. To account for this type of missing data and correlation
between subunit test results, we proposed a weighted generalized
estimating equations (WGEE) approach to evaluate subunit
sensitivities and specificities. A simulation study was conducted
to evaluate the performance of the WGEE estimators and the
weighted least squares (WLS) estimators (Barnhart and Kosinski,
2003) under a missing at random assumption. The results suggested
that WGEE estimator is consistent under various scenarios of
percentage of missing data and sample size, while the WLS approach
could yield biased estimators due to a misspecified missing data
mechanism. We illustrate the methodology with a cardiology
example.