Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome

International Journal of Epidemiology

Volumn 43, Issue 3, 2014, Pages 922-929

  Burgess, Stephen ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

Allele score; Binary outcome; Mendelian randomization; Power; Sample size

Indexed keywords

ALLELE; EPIDEMIOLOGY; GENETIC ANALYSIS; GENETIC VARIATION; RISK FACTOR; SAMPLING;

ALLELE; ARTICLE; CASE CONTROL STUDY; CONTROLLED STUDY; CORRELATION ANALYSIS; GENETIC VARIABILITY; INSTRUMENTAL VARIABLE ANALYSIS; MENDELIAN RANDOMIZATION ANALYSIS; POWER ANALYSIS; PRIORITY JOURNAL; RISK FACTOR; SAMPLE SIZE; SIMULATION; SINGLE INSTRUMENTAL VARIABLE; HUMAN; MONTE CARLO METHOD; PROCEDURES; RANDOMIZATION;

HUMANS; MENDELIAN RANDOMIZATION ANALYSIS; MONTE CARLO METHOD; RANDOM ALLOCATION; RISK FACTORS; SAMPLE SIZE;

EID: 84902684375     PISSN: 03005771     EISSN: 14643685     Source Type: Journal    
DOI: 10.1093/ije/dyu005     Document Type: Article

References (33)

1. Davey Smith G, Ebrahim S. Data dredging, bias, or confounding. BMJ 2002;325:1437.
2. Davey Smith G, Ebrahim S. 'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol 2003;32:1-22.
3. Lawlor D, Harbord R, Sterne J, Timpson N, Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med 2008;27: 1133-63.
4. Nitsch D, Molokhia M, Smeeth L, DeStavola B, Whittaker J, Leon D. Limits to causal inference based on Mendelian randomization: a comparison with randomized controlled trials. Am J Epidemiol 2006;163:397-403.
5. Greenland S. An introduction to instrumental variables for epidemiologists. Int J Epidemiol 2000;29:722-29.
6. Martens E, Pestman W, de Boer A, Belitser S, Klungel O. Instrumental variables: application and limitations. Epidemiology 2006;17:260-67.
7. Didelez V, Sheehan N. Mendelian randomization as an instrumental variable approach to causal inference. Stat Methods Med Res 2007;16(4):309-30.
8. Schatzkin A, Abnet C, Cross A. Mendelian randomization: how it can-and cannot-help confirm causal relations between nutrition and cancer. Cancer Prev Res 2009;2:104-13.
9. Freeman G, Cowling B, Schooling M. Power and sample size calculations for Mendelian randomization studies. Int J Epidemiol 2013;doi:10.1093/ije/dyt110.
10. Burgess S, Thompson S. Use of allele scores as instrumental variables for Mendelian randomization. Int J Epidemiol 2013;42: 1134-44.
11. Pierce B, Ahsan H, VanderWeele T. Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol 2011;40: 740-52.
12. Didelez V, Meng S, Sheehan N. Assumptions of IV methods for observational epidemiology. Stat Sci 2010;25:22-40.
13. Palmer T, Lawlor D, Harbord R et al. Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res 2011;21:223-42.
14. Cai B, Small D, Ten Have T. Two-stage instrumental variable methods for estimating the causal odds ratio: Analysis of bias. Stat Med 2011;30:1809-24.
15. Burgess S; CHD CRP Genetics Collaboration. Identifying the odds ratio estimated by a two-stage instrumental variable analysis with a logistic regression model. Stat Med 2013;32: 4726-47.
16. Burgess S, Thompson S. Improvement of bias and coverage in instrumental variable analysis with weak instruments for continuous and binary outcomes. Stat Med 15 2012;31:1582-600.
17. Nelson C, Startz R. The distribution of the instrumental variables estimator and its t-ratio when the instrument is a poor one. J Business 1990;63:125-40.
18. Wooldridge J. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press, 2002.
19. Shakhbazov K. mRnd: Power Calculations for Mendelian Randomization. http://glimmer.rstudio.com/kn3in/mRnd (27 January 2014, date last accessed).
20. Thomas D, Conti D. Commentary: the concept of 'Mendelian Randomization'. Int J Epidemiol 2004;33:21-25.
21. R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing, 2011.
22. Burgess S. Online Sample Size and Power Calculator for Mendelian Randomization With a Binary Outcome. http:// spark.rstudio.com/sb452/power/ (27 January 2014, date last accessed).
23. Buonaccorsi J. Fieller's theorem. In: Armitage P, Colton T (eds). Encyclopedia of Biostatistics.Hoboken NJ: Wiley, 2005.
24. Burgess S, Thompson S; CRP CHD Genetics Collaboration. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol 2011;40:755-64.
25. Burgess S, Seaman S, Lawlor D, Casas J, Thompson S. Missing data methods in Mendelian randomization studies with multiple instruments. Am J Epidemiol 2011;174:1069-76.
26. Burgess S, Thompson S. Bias in causal estimates from Mendelian randomization studies with weak instruments. Stat Med 2011;30:1312-23.
27. Palmer T, Thompson J, Tobin M, Sheehan N, Burton P. Adjusting for bias and unmeasured confounding in Mendelian randomization studies with binary responses. Int J Epidemiol 2008;37:1161-68.
28. Palmer T, Sterne J, Harbord R et al. Instrumental variable estimation of causal risk ratios and causal odds ratios in Mendelian randomization analyses. Am J Epidemiol 2011;173: 1392-403.
29. Greenland S, Robins J, Pearl J. Confounding and collapsibility in causal inference. Stat Sci 1999;14:29-46.
30. Harbord R, Didelez V, Palmer T, Meng S, Sterne J, Sheehan N. Severity of bias of a simple estimator of the causal odds ratio in Mendelian randomization studies. Stat Med 2013;32: 1246-58.
31. Vansteelandt S, Bowden J, Babanezhad M, Goetghebeur E. On instrumental variables estimation of causal odds ratios. Stat Sci 2011;26:403-22.
32. Burgess S, Butterworth A, Malarstig A, Thompson S. Use of Mendelian randomisation to assess potential benefit of clinical intervention. BMJ 2012;345:e7325.
33. Pierce B, Burgess S. Efficient design for Mendelian randomization studies: subsample and two-sample instrumental variable estimators. Am J Epidemiol 2013;178:1177-84.