A weighted logistic regression model for estimation of recurrence of adenomas

Statistics in Medicine

Volumn 26, Issue 7, 2007, Pages 1567-1578

  Hsu, Chiu Hsieh ^a   Green, Sylvan B ^a   He, Yulei ^b  

^a UNIVERSITY OF ARIZONA   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

Author keywords

Colon Cancer; Current status data; Logistic regression; Non parametric maximum likelihood estimator; Weight function

Indexed keywords

PLACEBO; URSODEOXYCHOLIC ACID;

ARTICLE; CANCER STATISTICS; CLINICAL TRIAL; COLONOSCOPY; COLORECTAL ADENOMA; DATA ANALYSIS; DISEASE FREE SURVIVAL; FOLLOW UP; HUMAN; INTERMETHOD COMPARISON; KAPLAN MEIER METHOD; LOGISTIC REGRESSION ANALYSIS; MAXIMUM LIKELIHOOD METHOD; NONPARAMETRIC TEST; RECURRENCE RISK; RECURRENT CANCER; RISK ASSESSMENT; SIMULATION;

ADENOMA; CHOLAGOGUES AND CHOLERETICS; COLONIC POLYPS; COLONOSCOPY; COLORECTAL NEOPLASMS; COMPUTER SIMULATION; HUMANS; KAPLAN-MEIERS ESTIMATE; LOGISTIC MODELS; NEOPLASM RECURRENCE, LOCAL; RANDOMIZED CONTROLLED TRIALS; TREATMENT REFUSAL; URSODEOXYCHOLIC ACID;

EID: 33947122129     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.2648     Document Type: Article

References (13)

1. Einspahr JG, Alberts DS, Gapstur SM, Bostick RM et al. Surrogate endpoint biomarkers as measures of colon cancer risk and their use in cancer chemoprevention trials. Cancer Epidemiology, Biomarkers, and Prevention 1997; 6:37-48.
2. Peto R. Experimental survival curves for interval-censored data. Applied Statistics 1973; 22:86-91.
3. Turnbull BW. The empirical distribution function with arbitrarily grouped, censored and truncated data. Journal of the Royal Statistical Society, Series B 1976; 38:290-295.
4. Rcker G, Messerer D. Remission duration: an example of interval-censored observations. Statistics in Medicine 1988; 7:1139-1145.
5. Law CG, Brookmeyer R. Effects of mid-point imputation on the analysis of doubly censored data. Statistics in Medicine 1992; 11:1569-1578.
6. Odell PM, Anderson KM, DAgostino RB. Maximum likelihood estimation for interval-censored data using a Weibull-based accelerated failure time model. Biometrics 1992; 48:951-959.
7. Dorey FJ, Little RJA, Schenker N. Multiple imputation for threshold-crossing data with interval censoring. Statistics in Medicine 1993; 12:1589-1603.
8. Hsu C-H. Joint modeling of recurrence and progression of adenomas: a latent variable approach. Statistical Modelling 2005; 5:201-215.
9. Cheung YK, Chappell R. Sequential designs for phase I clinical trials with late-onset toxicities. Biometrics 2000; 56:1177-1182.
10. Efron B. The two sample problem with censored data. In Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, vol. 4. Prentice-Hall: New York, 1967; 831-853.
11. Gill RD. Censoring and Stochastic Integral, vol. 124. Mathematical Centre Tracts. Mathematisch Centrum: Amsterdam, 1980.
12. Klein JP. Small sample moments of some estimators of the variance of the Kaplan-Meier and Nelson-Aalen estimators. Scandinavian Journal of Statistics 1991; 18:333-340.
13. Alberts DS, Martnez ME, Hess LM et al. Phase III trial of ursodeoxycholic acid to prevent colorectal adenoma recurrence. Journal of the National Cancer Institute 2005; 97:846-853.