248057 A Cautionary Note on Standard Errors from Complex Survey Analysis: Classical Weighted Least Squares, Generalized Estimating Equation, or Information-Weighted Least-Squares Regression?

Tuesday, November 1, 2011: 1:35 PM

Motao Zhu, MD, MS, PhD , Dept. of Community Medicine and Injury Control Research Center, West Virginia University, Morgantown, WV
Haitao Chu, MD, PhD , Division of Biostatistics, University of Minnesota, Minneapolis, MN
Sander Greenland, Dr PH , Department of Epidemiology and Department of Statistics, University of California, Los Angeles, Los Angeles, CA
Objective: A common research interest is to identify whether there is an increasing or decreasing trend for various health-related conditions over time in national complex surveys. We examined whether standard errors from common regression approaches appear accurate for trend analysis of complex surveys.

Methods: We re-conducted a trend analysis of the national emergency department visit rate from 1997 through 2007 published recently in JAMA. We compared standard errors from classical weighted least squares (CWLS), generalized estimating equation (GEE), information-weighted least squares (IWLS) regression, and nonparametric bootstrapping.

Results: The standard errors of the slope estimates from CWLS regression (0.88 per 1000 person-years) and from GEE regression (0.87 per 1000 person-years) were less than half the standard error from IWLS regression (1.98 per 1000 person-years). Nonparametric bootstrapping replicated the IWLS result. The p-value for trend from CWLS was only 0.002 and the GEE p-value was 0.00002, both much smaller than the p-value of 0.09 from IWLS.

Conclusion: In ecologic time-trend analyses, standard errors from CWLS and GEE can be much too small. For these settings, IWLS provides more reliable inferential statistics.

Learning Areas:

Learning Objectives:
Compare the standard errors from classical weighted least squares, generalized estimating equation, and information-weighted least-squares regression for trend analysis of complex surveys

Keywords: Epidemiology, Emergency Department/Room

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I design and conduct the study.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.