Multiple imputation analysis of case-cohort studies

Statistics in Medicine

Volumn 30, Issue 13, 2011, Pages 1595-1607

  Marti, Helena ^a   Chavance, Michel ^a  

^a CENTRE FOR RESEARCH IN EPIDEMIOLOGY AND POPULATION HEALTH   (France)

Author keywords

Case cohort design; Multiple imputation

Indexed keywords

FIBRINOGEN;

ACCURACY; ARTICLE; CALCULATION; CALIBRATION; CANCER STAGING; CARDIOVASCULAR RISK; CASE COHORT ANALYSIS; COHORT ANALYSIS; DISEASE COURSE; EVENT FREE SURVIVAL; HEART INFARCTION; HISTOLOGY; HUMAN; INTERMETHOD COMPARISON; METHODOLOGY; NEPHROBLASTOMA; PROBABILITY; SIMULATION; SMOKING; STATISTICAL ANALYSIS; TUMOR VOLUME; VALIDITY;

CASE-CONTROL STUDIES; COHORT STUDIES; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; FIBRINOGEN; HISTOCYTOCHEMISTRY; HUMANS; MALE; MODELS, STATISTICAL; MYOCARDIAL ISCHEMIA; WILMS TUMOR;

EID: 79956110012     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.4130     Document Type: Article

References (18)

1. Langholz B, Thomas DC. Nested case-control and case-cohort methods of sampling from a cohort: a critical comparison. American Journal of Epidemiology 1990; 131:169-176.
2. Prentice RL. A case-cohort design for epidemiologic cohort studies and disease prevention trials. Biometrika 1986; 73:1-11.
3. Breslow NE, Lumley T, Ballantyne CM, Chambless LE, Kulich M. Using the whole cohort in the analysis of case-cohort data. American Journal of Epidemiology 2009; 169:1398-1405. DOI: 10.1093/aje/kwp055.
4. Paik MC, Tsai WY. On using the Cox proportional hazards model with missing covariates. Biometrika 1997; 84:579-593. DOI: 10.1093/biomet/84.3.579.
5. Self SG, Prentice RL. Asymptotic distribution theory and efficiency results for case-cohort studies. The Annals of Statistics 1988; 16:64-81. DOI: 10.1214/aos/1176350691.
6. Borgan O, Langholz B, Samuelsen SO, Goldstein L, Pogoda J. Exposure stratified case-cohort designs. Lifetime Data Analysis 2000; 6:39-58. DOI: 10.1023/A:1009661900674.
7. Barlow WE. Analysis of case-cohort designs. Journal of Clinical Epidemiology 1999; 52:1165-1172. DOI: 10.1016/S0895-4356(99)00102-X.
8. Langholz B, Jiao J. Computational methods for case-cohort studies. Computational Statistics and Data Analysis 2007; 51:3737-3748.
9. Kulich K, Lin DY. Improving de efficiency of relative-risk estimation in case-cohort studies. Journal of the American Statistical Association 2004; 99:832-844. DOI: 10.1198/016214504000000584.
10. Qi L, Wang CY, Prentice RL. Weighted estimators for proportional hazards regression with missing covariates. Journal of the American Statistical Association 2005; 100:1250-1263. DOI: 10.1198/016214505000000295.
11. Little RJA, Rubin DB. Statistical Analysis with Missing Data. Wiley: New York, 1987.
12. Rubin DB, Schenker N. Multiple imputation for interval estimation from simple random samples with ignorable nonresponse. Journal of the American Statistical Association 1986; 81:366-374.
13. Rubin DB. Multiple Imputation for Nonresponse in Surveys. Wiley: New York, 1987.
14. Yarnell JWG. The PRIME study: classical risk factors do not explain the severalfold differences in risk of coronary heart disease between France and Northern Ireland. The Quarterly Journal of Medicine 1998; 91:667-676.
15. Scarabin PY, Jiao J. Plasma fibrinogen explains much of the difference in risk of coronary heart disease between France and Northern Ireland. The PRIME study. Atherosclerosis 2003; 166:103-109.
16. d'Angio GJ, Breslow N, Beckwith JB, Evans A, Baum H, deLorimier A, Fernbach D, Hrabovsky E, Jones B, Kelalis P, Othersen HB, Tefft M, Thomas PRM. Treatment of Wilms' tumor. Results of the Third National Wilms' Tumor Study. Cancer 1989; 64:349-360.
17. Cox DR, Hinkley DV. Theoretical Statistics. Chapman and Hall: London, 1974.
18. Yucel RM. Multiple imputation inference for multivariate multilevel continuous data with ignorable non-response. Philosophical Transactions of the Royal Society A 2008; 366:2389-2403. DOI: 10.1098/rsta.2008.0038.