SensitivityCaseControl (version 2.2)

SensitivityCaseControl-package: Sensitivity Analysis for Case-Control Studies

Description

This package performs sensitivity analysis for matched case-control studies in which some cases meet a narrow definition of being a case compared to other cases which only meet a broad definition. The package also implements an adaptive sensitivity analysis for matched pair cohort studies.

Details

Package:	CaseSensitivity
Type:	Package
Version:	1.0
Date:	2012-10-19
License:	R 2.11.1
LazyLoad:	yes

The functions sens.analysis.mh and sens.analysis.aberrant.rank provide sensitivity analyses based on the Mantel-Haenszel test statistic and aberrant rank test statistic. The function adaptive.case.test provides adaptive inferences that reject if either the Mantel-Haenszel statistic for the narrow cases is greater than a critical value or the Mantel-Haenszel statistic for all cases is greater than a critical value. The sensitivity analyses are described in Small, Cheng, Halloran and Rosenbaum (2012, "Case Definition and Sensitivity Analysis", working paper). The function adaptive.noether.brown provides a sensitivity analysis for a matched cohort study based on an adaptive test. The other functions in the package are internal functions.

References

Small, D.S., Cheng, J., Halloran, M.E. and Rosenbaum, P.R. (2013). "Case Definition and Design Sensitivity." Journal of the American Statistical Association, 108, 1457-1468.

Rosenbaum, P.R. (2012). "An Exact Adaptive Test with Superior Design Sensitivity in an Observational Study of Treatments for Ovarian Cancer." Annals of Applied Statistics, 6, 83-105.

Examples

# NOT RUN {
# Adaptive test for a case-control study based on Table 4 in Small, Cheng, 
# Halloran and Rosenbaum (2013)
no.exposed.in.matched.set=c(rep(0,229),rep(1,23),rep(1,51),rep(2,9),rep(0,373),rep(1,46),rep(1,50),
rep(2,13));
narrowcase=c(rep(1,312),rep(0,482));
case.exposed=c(rep(0,229),rep(0,23),rep(1,51),rep(1,9),rep(0,373),rep(0,46),rep(1,50),rep(1,13));
size.matched.set=rep(2,length(case.exposed))
# Test using the statistics T1 and T1+T2 where T1 is Mantel-Haenszel for narrow cases and T2 is 
# Mantel Haenszel for marginal cases
adaptive.case.test(no.exposed.in.matched.set,narrowcase,case.exposed,size.matched.set,Gamma=1.37,
alpha=.05,narrowmultiplier=1)
# Test using the statistics T1 and 2*T1+T2
adaptive.case.test(no.exposed.in.matched.set,narrowcase,case.exposed,size.matched.set,Gamma=1.37,
alpha=.05,narrowmultiplier=2)

# Sensitivity analysis using only the narrow cases and the Mantel-Haenszel statistic
# Data from narrow cases in Table 1 of Small, Cheng and Halloran, Rosenbaum
cases.exposed=c(rep(0,174+60+14+4+0),rep(1,34+19+6+1+0));
referents.exposed=c(rep(0,174),rep(1,60),rep(2,14),rep(3,4),rep(0,34),rep(1,19),rep(2,6),rep(3,1));
no.referents=rep(4,312);
# Sensitivity analysis for Mantel-Haenszel statistic at Gamma=1.2
sens.analysis.mh(cases.exposed,referents.exposed,no.referents,Gamma=1.2);

# Adaptive test using Noether's and Brown's statstics for a matched cohort study
# Data on volume of hippocampus in 15 sets of twins in which one twin is affected by schizophrenia 
# and one twin is not (data from R.L. Suddath et al., "Anatomical Abnormalities in the Brains of 
# Monozygotic Twins Discordant for Schizophrenia," New England Journal of Medicine 322, 1990
# pp. 789-93.  Data taken from the Statistical Sleuth, F.L. Ramsey and D.W. Schafer
unaffected=c(1.94,1.44,1.56,1.58,2.06,1.66,1.75,1.77,1.78,1.92,1.25,1.93,2.04,1.62,2.08)
affected=c(1.27,16.3,1.47,1.39,1.93,1.26,1.71,1.67,1.28,1.85,1.02,1.34,2.02,1.59,1.97)
difference=unaffected-affected
adaptive.noether.brown(difference,Gamma=1.1)
# The null hypothesis of no treatment is rejected for Gamma=1.13 but not for Gamma=1.14
# }