Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Thompson casts doubt on the rehabilitative intentions of prison labor

Inglehart says European social democracy is a victim of its own success

Bound, Khanna, and Morales find multiple effects of H1-B visas on US tech industry

More News

Highlights

Heather Ann Thompson wins Bancroft Prize for History for 'Blood in the Water'

Michigan ranks in USN&WR top-10 grad schools for sociology, public health, labor economics, social policy, social psychology

Paula Lantz to speak at Women in Health Leadership Summit, March 24, 2:30-5:30 Michigan League

New site highlights research, data, and publications of Relationship Dynamics and Social Life study

More Highlights

Next Brown Bag

Mon, March 20, 2017, noon:
Dean Yang, Taken by Storm

Bias Due to Left Truncation and Left Censoring in Longitudinal Studies of Developmental and Disease Processes

Publication Abstract

Cain, K., Sioban D. Harlow, R. J. A. Little, B. Nan, M. Yosef, J. Taffe, and Michael R. Elliott. 2011. "Bias Due to Left Truncation and Left Censoring in Longitudinal Studies of Developmental and Disease Processes." American Journal of Epidemiology, 173(9): 1078-1084.

In longitudinal studies of developmental and disease processes, participants are followed prospectively with intermediate milestones identified as they occur. Frequently, studies enroll participants over a range of ages including ages at which some participants' milestones have already passed. Ages at milestones that occur prior to study entry are left censored if individuals are enrolled in the study or left truncated if they are not. The authors examined the bias incurred by ignoring these issues when estimating the distribution of age at milestones or the time between 2 milestones. Methods that account for left truncation and censoring are considered. Data on the menopausal transition are used to illustrate the problem. Simulations show that bias can be substantial and that standard errors can be severely underestimated in naive analyses that ignore left truncation. Bias can be reduced when analyses account for left truncation, although the results are unstable when the fraction truncated is high. Simulations suggest that a better solution, when possible, is to modify the study design so that information on current status (i.e., whether or not a milestone has passed) is collected on all potential participants, analyzing those who are past the milestone at the time of recruitment as left censored rather than excluding such individuals from the analysis.

DOI:10.1093/aje/kwq481 (Full Text)

PMCID: PMC3121224. (Pub Med Central)

Country of focus: United States of America.

Browse | Search : All Pubs | Next