Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/RPCLR-functions.R
Simulate a dataset from a 1:1 matched case control study
1 | GenerateData(numstrat, NumType.BM, NumType.NS, mu.diff, rho)
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numstrat |
number of matched pairs |
NumType.BM |
number of features with non-zero difference in means between cases and controls (i.e. biomarkers) |
NumType.NS |
number of features with identical means between cases and controls (i.e. noise) |
mu.diff |
Difference in means between cases and controls for biomarkers |
rho |
correlation between matched pairs for biomarkers only |
Biomarkers and noise features are simulated as independent random variables following a Gaussian distribution with unit variance.
Data |
a numeric data matrix of n (number of subjects) rows and p (number of features) columns |
Out |
a response vector of length n of binary indicators of case/control status |
Strat |
a vector of length n of matched pair (stratum) indicators |
Raji Balasubramanian
Balasubramanian, R., Houseman, E. A., Coull, B. A., Lev, M. H., Schwamm, L. H., Betensky, R. A. (2012). Variable importance in matched case-control studies in settings of high dimensional data, Submitted to Biostatistics.
GetVarImp
1 2 3 4 5 | ## Simulate Data
MyDat <- GenerateData(50, 3, 7, 0.5, 0.4)
Dat <- MyDat$Data
Out <- MyDat$Out
Strat <- MyDat$Strat
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Loading required package: MASS
Loading required package: survival
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