Discrete Proportional Hazards Models for Mismeasured Outcomes

Biometrics

Volumn 59, Issue 4, 2003, Pages 947-954

  Meier, Amalia S ^a   Richardson, Barbra A ^b   Hughes, James P ^b  

^a Fred Hutchinson Cancer Research Center   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Measurement error; Proportional hazards; Sensitivity; Specificity; Survival

Indexed keywords

HAZARDS; REGRESSION ANALYSIS;

BIAS ESTIMATION; BIASED ESTIMATION; COVARIATES; HAZARD RATIO; OUTCOME MEASURES; PROPORTIONAL HAZARD MODELS; PROPORTIONAL HAZARDS; SENSITIVITY; SPECIFICITY; SURVIVAL;

BIOMETRICS;

MODEL;

ANALYTICAL ERROR; ARTICLE; GONORRHEA; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; MEASUREMENT; NONBIOLOGICAL MODEL; RISK FACTOR; SEXUALLY TRANSMITTED DISEASE; STATISTICAL MODEL; SURVIVAL;

HUMAN IMMUNODEFICIENCY VIRUS;

EID: 0346733299     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2003.00109.x     Document Type: Article

References (14)

1. Balasubramanian, R. and Lagakos, S. W. (2001). Estimation of the timing of perinatal transmission of HIV. Biometrics 57, 1048-1058.
2. Balasubramanian, R. and Lagakos, S. W. (2003). Estimation of a failure time distribution based on imperfect diagnostic tests. Biometrika 90, 71-182.
3. Buimer, M., van Doornum, G. J., Ching, S., Peerbooms, P. G., Plier, P. K., Ram, D., and Lee, H. H. (1996). Detection of Chlamydia trachomatis and Neisseria gonorrhoeae by ligase chain reaction-based assays with clinical specimens from various sites: Implications for diagnostic testing and screening. Journal of Clinical Microbiology 34, 2395-2400.
4. Carroll, K. C., Aldeen, W. E., Morrison, M., Anderson, R., Lee, D., and Mottice, S. (1998). Evaluation of the Abbott lcx ligase chain reaction assay for detection of Chlamydia trachomatis and Neisseria gonorrhoeae in urine and genital swab specimens from a sexually transmitted disease clinic population. Journal of Clinical Microbiology 36, 1630-1633.
5. Cox, D. R. (1972). Regression models and life-tables. JRSS, Series B 34, 187-220.
6. Fleming, T. R. and Harrington, D. P. (1991). Counting Processes and Survival Analysis. New York: Wiley.
7. Fuller, W. A. (1987). Measurement Error Models. New York: Wiley.
8. Gelfand, A. E. and Wang, F. (2000). Modelling the cumulative risk for a false-positive under repeated screening events. Statistics in Medicine 19, 1865-1879.
9. Kalbfleisch, J. D. and Prentice, R. L. (1980). The Statistical Analysis of Failure Time Data. New York: Wiley.
10. Little, R. J. A. and Rubin, D. B. (1987). Statistical Analysis with Missing Data. New York: Wiley.
11. Magder, L. and Hughes, J. P. (1997). Logistic regression when the outcome is measured with uncertainty. American Journal of Epidemiology 146, 195-203.
12. Martin, H. L., Jr., Nyange, P. M., Richardson, B. A., Lavreys, L., Mandaliya, K., Jackson, D. J., Ndiriya-Achola, J. O. and Kreiss, J. (1998). Hormonal contraception, sexually transmitted diseases, and risk of heterosexual transmissions of human immunodeficiency virus type 1. Journal of Infectious Diseases 178, 1053-1059.
13. Richardson, B. A. and Hughes, J. P. (2000). Product limit estimation for infectious disease data when the diagnostic test for the outcome is measured with uncertainty. Biostatistics 1, 341-354.
14. Snapinn, S. M. (1998). Survival analysis with uncertain endpoints. Biometrics 54, 209-218.