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

Abstract Details

Activity Number: 684
Type: Contributed
Date/Time: Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #307590
Title: Principal Trend Ratio Regression: Comparing Nonlinear Longitudinal Trajectories Between Groups via a Ratio of Inter-Period Changes When a Linear Trend Fits Poorly
Author(s): Robert M Boudreau*+
Companies: University of Pittsburgh
Address: Dept of Epidemiology, Pittsburgh, PA, 15213,
Keywords: Growth Curves ; Random effects ; Longitudinal data analysis ; Exercise ; Observational cohort studies

Random slopes & intercepts mixed models with a linear trend are widely used for longitudinal data. Yet, in practice the growth curve often looks more curved than linear or has eras of timepoints with steeper or diminishing changes. Polynomial terms are difficult to interpret. With the goal of one parameter that compares groups, a new growth curve model identifies a "principal trend" with the group comparison as a multiplier of the changes by the referent. Covariates and random effects apply. Gait speed (GS) over 20m was measured in an elderly cohort (n=1462,age 69-80) at years 1,3,5,8. Men at baseline had 0.24 m/sec higher GS than women, but their GS declined 21% more (beta=1.207,p=0.002) than women over time. Regular exercisers had higher baseline GS. The confidence interval for the multiplier vs non-exercisers covers 1. Still slowing, they maintain a higher parallel GS trend over time.

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