JDR JDR Most Read Articles
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Full Text (PDF)
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Chuang, S. K.
Right arrow Articles by Dodson, T. B.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Chuang, S. K.
Right arrow Articles by Dodson, T. B.

Journal of Dental Research, Vol 80, 2016-2020, Copyright © 2001 by International & American Associations for Dental Research Online Journals


ARTICLES

Kaplan-Meier analysis of dental implant survival: a strategy for estimating survival with clustered observations

S. K. Chuang, L. Tian, L. J. Wei and T. B. Dodson
Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Boston, MA 02115, USA. schuang@hsph.harvard.edu

The study's purposes were to estimate dental implant survival in a statistically valid manner and to compare three models for estimating survival. We estimated survival using three different statistical models: (1) randomly selecting one implant per patient; (2) utilizing all implants, assuming independence among implants from the same subject; and (3) utilizing all implants, assuming dependence among implants from the same subject. The cohort was composed of 660 patients who had 2286 implants placed. Due to the high success rates of implants, the five-year survival point and standard error estimates varied little among the three models. Patients at high risk for implant failure (smokers) manifested greater variation in the standard error estimates among the three models, 8.2%, 4.0%, and 5.6%, respectively. To obtain statistically valid survival confidence intervals when performing Kaplan-Meier survival analyses, we recommend adjusting for dependence when there are multiple observations within the same subject.


This article has been cited by other articles:


Home page
Stat Methods Med ResHome page
T. A Gerds and M. Vogeler
Endpoints and survival analysis for successful osseointegration of dental implants
Statistical Methods in Medical Research, December 1, 2005; 14(6): 579 - 590.
[Abstract] [PDF]


Home page
J. Dent. Res.Home page
S.K. Chuang, T. Cai, C.W. Douglass, L.J. Wei, and T.B. Dodson
Frailty Approach for the Analysis of Clustered Failure Time Observations in Dental Research
J. Dent. Res., January 1, 2005; 84(1): 54 - 58.
[Abstract] [Full Text] [PDF]


Home page
J. Dent. Res.Home page
A. Hannigan
Using Survival Methodologies in Demonstrating Caries Efficacy
J. Dent. Res., July 1, 2004; 83(suppl_1): C99 - C102.
[Abstract] [Full Text] [PDF]


Home page
J. Dent. Res.Home page
S.K. Chuang, L. Tian, L.J. Wei, and T.B. Dodson
Predicting Dental Implant Survival by Use of the Marginal Approach of the Semi-parametric Survival Methods for Clustered Observations
J. Dent. Res., December 1, 2002; 81(12): 851 - 855.
[Abstract] [Full Text] [PDF]


Home page
J. Dent. Res.Home page
S.K. Chuang, L.J. Wei, C.W. Douglass, and T.B. Dodson
Risk Factors for Dental Implant Failure: A Strategy for the Analysis of Clustered Failure-time Observations
J. Dent. Res., August 1, 2002; 81(8): 572 - 577.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
IADR Journals Advances in Dental Research ®
Journal of Dental Research ® Critical Reviews (1990-2004)
Copyright © 2001 Institutional Access Guidelines