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United States Department of Agriculture

Agricultural Research Service

Title: Regression Splines with Longitudinal Data

Authors
item Jo, Chan Hee - UAMS DEPT OF PEDIACTRICS
item Simpson, Pippa - ACHRI-DAC
item Gossett, Jeff - ACHRI-DAC
item Bogle, Margaret

Submitted to: Meeting Proceedings
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 20, 2006
Publication Date: April 17, 2007
Citation: Jo, C., Simpson, P.M., Gossett, J.M., Bogle, M.L. 2007. Regression splines with longitudinal data: SAS Survey Procedures and NHANES. SAS Global Forum 2007, April 16-19, 2007, Orlando, Florida. Paper 143-2007. Available: http://www2.sas.proceedings/forum2007/143-2007.pdf.

Technical Abstract: In many clinical trial studies, patients are observed and/or measured on multiple occasions. To account for the longitudinal nature of the data, a mixed model analysis implemented using SAS PROC MIXED is commonly used. It is typical to make comparisons between dose or treatment groups, possibly controlling for demographic variables. When the dose response curve is non-linear, it can be difficult to find an appropriate curve, and model misspecification is common. We will present an alternative to non-linear mixed models that avoids the problem of specifying a parametric model. We demonstrate the use of a semi-parametric regression in the mixed model framework. This use of PROC MIXED allows for nonlinear fitting with a covariance structure for the correlated observations. We illustrate its use from the longitudinal data with various time points.

Last Modified: 12/21/2014
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