Uses and limitations of randomization-based efficacy estimators

Statistical Methods in Medical Research

Volumn 14, Issue 4, 2005, Pages 327-347

  White, Ian R ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

HYDROXYMETHYLGLUTARYL COENZYME A REDUCTASE INHIBITOR; PLACEBO; RETINOL; SIMVASTATIN; ZIDOVUDINE;

CLINICAL RESEARCH; CLINICAL TRIAL; CONFIDENCE INTERVAL; CORRELATION FUNCTION; COST EFFECTIVENESS ANALYSIS; COVARIANCE; DATA ANALYSIS; DRUG RESEARCH; FOLLOW UP; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS; METHODOLOGY; NONLINEAR SYSTEM; OUTCOMES RESEARCH; PATIENT COMPLIANCE; PATIENT INFORMATION; PROBABILITY; REVIEW; RISK ASSESSMENT; RISK REDUCTION; SAMPLE SIZE; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICAL SIGNIFICANCE; SURVIVAL;

AGED; CHILD; CLINICAL PROTOCOLS; GUIDELINE ADHERENCE; HUMANS; MALE; MODELS, STATISTICAL; NONLINEAR DYNAMICS; RANDOMIZED CONTROLLED TRIALS; RESEARCH DESIGN;

EID: 24944468294     PISSN: 09622802     EISSN: None     Source Type: Journal    
DOI: 10.1191/0962280205sm406oa     Document Type: Review

References (64)

1. Schwartz D, Lellouch J. Explanatory and pragmatic attitudes in therapeutic trials. Journal of Chronic Diseases 1967; 20: 637-48.
2. Hughes DA, Bagust A, Haycox A, Walley T. Accounting for noncompliance in pharmacoeconomic evaluations. Pharmacoeconomics 2001; 19: 1185-97.
3. White IR, Babiker AG, Walker SJ, Darbyshire JH. Randomisation-based methods for correcting for treatment changes: examples from the Concorde trial. Statistics in Medicine 1999; 18: 2617-34.
4. White IR, Carpenter J, Pocock SJ, Henderson RA. Adjusting treatment comparisons to account for non-randomised interventions: an example from an angina trial. Statistics in Medicine 2003; 22: 781-93.
5. Pocock SJ. Clinical trials: a practical approach. Chichester: Wiley, 1983.
6. Hollis S, Campbell F. What is meant by intention to treat analysis? Survey of published randomised controlled trials. British Medical Journal 1999; 319: 670-74.
7. Baker SG. Analysis of survival data from a randomized trial with all-or-none compliance: Estimating the cost-effectiveness of a cancer screening program. Journal of the American Statistical Association 1998; 93: 929-34.
8. Sommer A, Zeger SL. On estimating efficacy from clinical trials. Statistics in Medicine 1991; 10: 45-52.
9. Cuzick J, Edwards R, Segnan N. Adjusting for non-compliance and contamination in randomized controlled trials. Statistics in Medicine 1997; 16: 1017-29.
10. Imbens GW, Rubin DB. Bayesian inference for causal effects in randomized experiments with noncompliance. Annals of Statistics 1997; 25: 305-27.
11. Frangakis CE, Rubin DB. Addressing complications of intention-to-treat analysis in the combined presence of all-or-none treatment-noncompliance and subsequent missing outcomes. Biometrika 1999; 86: 365-79.
12. Hirano K, Imbens GW, Rubin DB, Zhou XH. Assessing the effect of an influenza vaccine in an encouragement design. Biostatistics 2000; 1(1): 69-88.
13. Jo B. Model misspecification sensitivity analysis in estimating causal effects of interventions with non-compliance. Statistics in Medicine 2002; 21: 3161-81.
14. Loeys T, Goetghebeur E. A causal proportional hazards estimator for the effect of treatment actually received in a randomized trial with all-or-nothing compliance. Biometrics 2003; 59: 100-105.
15. International conference on harmonisation. Statistical principles for clinical trials. Statistics in Medicine 1999; 18: 1905-42.
16. Horne AD, Lachenbruch PA, Goldenthal KL. Intent-to-treat analysis and preventive vaccine efficacy. Vaccine 2000; 19: 319-26.
17. White IR, Walker S, Babiker AG, Darbyshire JH. Impact of treatment changes on the interpretation of the Concorde trial. AIDS 1997; 11: 999-1006.
18. Burns T, White I, Byford S, Fiander M, Creed F, Fahy T. Exposure to case management: Relationships to patient characteristics and outcome: A UK700 study. British Journal of Psychiatry 2002; 181: 236-41.
19. Little RJA, Rubin DB. Statistical analysis with missing data. Hoboken, NJ: Wiley, 1987; 2nd edition.
20. Robins JM, Finkelstein DM. Correcting for noncompliance and dependent censoring in an AIDS clinical trial with inverse probability of censoring weighted (IPCW) log-rank tests. Biometrics 2000; 56: 779-88.
21. Newcombe RG. Explanatory and pragmatic estimates of the treatment effect when deviations from allocated treatment occur. Statistics in Medicine 1988; 7: 1179-86.
22. Frangakis CE, Rubin DB. Principal stratification in causal inference. Biometrics 2002; 58: 21-29.
23. Greenland S. An introduction to instrumental variables for epidemiologists. International Journal of Epidemiology 2000; 29: 722-29.
24. Rubin DB., More powerful randomization-based p-values in double-blind trials with non-compliance. Statistics in Medicine 1998; 17: 371-85.
25. Angrist JD, Imbens GW, Rubin DB. Identification of causal effects using instrumental variables. Journal of the American Statistical Association 1996; 91: 444-55.
26. Bowden RJ, Turkington DA. Instrumental variables. Cambridge: Cambridge University Press, 1984.
27. Branson M, Whitehead J. A score test for binary data with patient non-compliance. Statistics in Medicine 2003; 22: 3115-32.
28. Heart Protection Study Collaborative Group. MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20536 high-risk individuals: a randomised placebo-controlled trial. Lancet 2002; 360: 7-22.
29. Coronary Drug Project Research Group T. Influence of adherence to treatment and response of cholesterol on mortality in the Coronary Drug Project. New England Journal of Medicine 1980; 303: 1038-41.
30. Kim LG, White IR. Compliance-adjusted treatment effects in survival data. STATA Journal 2004; 4: 257-64.
31. Abadie A. Semiparametric instrumental variable estimation of treatment response models. Journal of Econometrics 2002; 113: 231-63.
32. Imbens GW, Rubin DB. Estimating outcome distributions for compliers in instrumental variables models. Review of Economic Studies 1997; 64: 555-74.
33. Senn SJ. Covariate imbalance and random allocation in clinical trials. Statistics in Medicine 1989; 8: 467-75.
34. Neuhaus JM, Jewell NP. A geometric approach to assess bias due to omitted covariates in generalized linear models. Biometrika 1993; 80: 807-15.
35. Robinson LD, Jewell NP. Some surprising results about covariate adjustment in logistic regression models. International Statistical Review 1991; 58: 227-40.
36. Neuhaus JM. Estimation efficiency with omitted covariates in generalized linear models. Journal of the American Statistical Association 1998; 93: 1124-29.
37. Jo, B. Statistical power in randomized intervention studies with noncompliance. Psychological Methods 2002; 7: 178-93.
38. Goetghebeur E, Lapp K. The effect of treatment compliance in a placebo-controlled trial: Regression with unpaired data. Applied Statistics 1997; 46: 351-64.
39. Fischer-Lapp K, Goetghebeur E. Practical properties of some structural mean analyses of the effect of compliance in randomized trials. Controlled Clinical Trials 1999; 20: 531-46.
40. Robins JM. Correcting for non-compliance in randomized trials using structural nested mean models. Communications in Statistics - Theory and Methods 1994; 23: 2379-2412.
41. Robins JM. Analytic methods for estimating HIV-treatment and cofactor effects. In Ostrow DG, Kessler RC, ed., Methodological issues in AIDS behavioural research. New York: Plenum Press, 1993.
42. Mark SD, Robins JM. A method for the analysis of randomised trials with compliance information: an application to the multiple risk factor intervention trial. Controlled Clinical Trials 1993; 14: 79-97.
43. Mark SD, Robins JM. Estimating the causal effect of smoking cessation in the presence of confounding factors using a rank preserving structural failure time model. Statistics in Medicine 1993; 12: 1605-28.
44. Robins JM, Tsiatis AA. Correcting for non-compliance in randomized trials using rank preserving structural failure time models. Communications in Statistics - Theory and Methods 1991; 20(8): 2609-31.
45. Robins JM, Greenland S. Adjusting for differential rates of prophylaxis therapy for PCP in high-dose versus low-dose AZT treatment arms in an AIDS randomized trial. Journal of the American Statistical Association 1994; 89: 737-49.
46. Robins JM. Correction for non-compliance in equivalence trials. Statistics in Medicine 1998; 17: 269-302.
47. White IR, Goetghebeur EJT. Clinical trials comparing two treatment policies: which aspects of the treatment policies make a difference? Statistics in Medicine 1998; 17: 319-339.
48. Joffe MM, Brensinger C. Weighting in instrumental variables and G-estimation. Statistics in Medicine 2003; 22: 1285-1303.
49. Lagakos SW, Lim LLY, Robins JM. Adjusting for early treatment termination in comparative clinical trials. Statistics in Medicine 1990; 9: 1417-24.
50. The Multicentre Aneurysm Screening Study Group. The multicentre aneurysm screening study (MASS) into the effect of abdominal aortic aneurysm screening on mortality in men: a randomised controlled trial. Lancet 2002; 360: 1531-39.
51. Trial of Alternative Regimens in Glue Ear Treatment. Surgery for persistent otitis media with effusion: generalizability of results from the UK trial (TARGET). Clinical Otolaryngology 2001; 26: 417-24.
52. Stata Statistical Software: Release 7.0. College Station, TX: Stata Corporation, 2001.
53. Korhonen P, Palmgren J. Effect modification in a randomized trial under non-ignorable non-compliance: an application to the alpha-tocopherol beta-carotene study. Applied Statistics 2002; 51: 115-133.
54. Thompson SG. Why sources of heterogeneity in meta-analysis should be investigated. British Medical Journal 1994; 309: 1351-55.
55. Glasziou PP, Sanders SL. Investigating causes of heterogeneity in systematic reviews. Statistics in Medicine 2002; 21: 1503-11.
56. Glasziou PP, Meta-analysis adjusting for compliance - the example of screening for breast-cancer. Journal of Clinical Epidemiology 1992; 45: 1251-56.
57. Glasziou PP, Woodward AJ, Mahon CM. Mammographic screening trials for women aged under 50 - a quality assessment and meta-analysis. Medical Journal of Australia 1995; 162: 625-29.
58. Towler B, Irwig L, Glasziou P, Kewenter J, Weller D, Silagy C. A systematic review of the effects of screening for colorectal cancer using the faecal occult blood test, hemoccult. British Medical Journal 1998; 317: 559-65.
59. Thompson SG, Sharp S. Explaining heterogeneity in meta-analysis: A comparison of methods. Statistics in Medicine 1999; 18: 2693-708.
60. Lewis JA, Machin D. Intention to treat - who should use ITT. British Journal of Cancer 1993; 68: 647-50.
61. Jones B, Jarvis P, Lewis J, Ebbutt A. Trials to assess equivalence: the importance of rigorous methods. British Medical Journal 1996; 313: 36-39.
62. Willan AR, Lin DY. Incremental net benefit in randomized clinical trials. Statistics in Medicine 2001; 20: 1563-74.
63. O'Hagan A, Stevens JW, Montmartin J. Bayesian cost-effectiveness analysis from clinical trial data. Statistics in Medicine 2001; 20: 733-53.
64. Hughes DA, Bagust A, Haycox A, Walley T. The impact of non-compliance on the cost-effectiveness of pharmaceuticals: a review of the literature. Health Economics 2001; 10: 601-605.