Analysis of multivariate failure times in the presence of selection bias with application to breast cancer

2014 ◽  
Vol 64 (3) ◽  
pp. 525-541 ◽  
Author(s):  
Martin Leclerc ◽  
Antonis C. Antoniou ◽  
Jacques Simard ◽  
Lajmi Lakhal-Chaieb ◽  
◽  
...  
Keyword(s):  
Breast Cancer ◽  
Selection Bias ◽  
Failure Times ◽  
Multivariate Failure Times

scholarly journals Investigating Respondents and Nonrespondents of a Postal Breast Cancer Questionnaire Survey Regarding Differences in Age, Medical Conditions, and Therapy

Breast Care ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. 139-143 ◽  
Author(s):  
Anna L. Frobeen ◽  
Christoph Kowalski ◽  
Verena Weiß ◽  
Holger Pfaff
Keyword(s):  
Breast Cancer ◽  
Selection Bias ◽  
Questionnaire Survey ◽  
Cancer Control ◽  
Hospital Staff ◽  
Postal Questionnaire ◽  
Cross Sectional ◽  
Old Patients ◽  
Patient Reported ◽  
Reported Data

Background: Collecting patient-reported data via postal questionnaires is a common and frequently used technique. Selection bias may occur through lost data from nonrespondents. This study investigated differences in characteristics between respondents and nonrespondents of a postal breast cancer survey. Patients and Methods: The investigation was based on a cross-sectional postal questionnaire survey for the mandatory annual routine (re-)certification of accredited breast centers in North Rhine-Westphalia in 2010. Out of 4,444 patients meeting the inclusion criteria who gave their consent to participate, 3,856 respondents sent back a questionnaire and 588 nonrespondents did not. Using logistic regression, differences between respondents and nonrespondents regarding information gathered through hospital staff concerning age, affected breast, UICC (Union for International Cancer Control) staging and grading, ASA (American Society of Anesthesiologists) classification, neoadjuvant chemotherapy, and type of surgery were assessed. Results: Very young and very old patients sent back their questionnaire significantly less frequently, as did patients who showed a later cancer stage and poorer general health and those who underwent mastectomy. Conclusion: Differences exist between respondents and nonrespondents with regard to age, disease, and therapy characteristics that need to be considered for the interpretation and generalizability of survey results due to selection bias.

Some Issues Related to Estimation of Component Life Time Distributions in a Coherent System

1997 ◽  
Vol 47 (1-2) ◽  
pp. 91-106
Author(s):  
Anup Dewanji
Keyword(s):  
Nonparametric Estimation ◽  
Continuous Monitoring ◽  
Life Time ◽  
Monitoring Data ◽  
Dependence Structure ◽  
Coherent System ◽  
Coherent Systems ◽  
Failure Times ◽  
Multivariate Failure Times ◽  
Autopsy Data

Recently, some interest has been focussed on the estimation of component life time distributions in coherent systems. For simplicity, most of the work assume independence between different component life times. Also, some specific dependence structure has been dealt with in some limited cases. In this work, we introduce a unified way of modelling the component life time distributions in a coherent system through the framework of multivariate failure times, which includes some arbitrary nature of dependence. Under independence, both parametric and nonparametric estimation of component life time distributions are discussed with continuous monitoring data and autopsy data as well. A specific dependence structure is also considered for this purpose.

scholarly journals Breast cancer management and outcome according to surgeon's affiliation: a population-based comparison adjusted for patient's selection bias

2013 ◽  
Vol 24 (1) ◽  
pp. 116-125 ◽  
Author(s):  
F. Taban ◽  
E. Rapiti ◽  
G. Fioretta ◽  
Y. Wespi ◽  
D. Weintraub ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Selection Bias ◽  
Population Based ◽  
Cancer Management ◽  
Breast Cancer Management

The impact of a psychosocial support program on survival with breast cancer: The importance of selection bias in program evaluation

1984 ◽  
Vol 37 (4) ◽  
pp. 273-282 ◽  
Author(s):  
Hal Morgenstern ◽  
George A. Gellert ◽  
Stephen D. Walter ◽  
Adrian M. Ostfeld ◽  
Bernard S. Siegel
Keyword(s):  
Breast Cancer ◽  
Program Evaluation ◽  
Selection Bias ◽  
Psychosocial Support ◽  
Support Program ◽  
The Impact
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