# R/ssizePCC.R In stamats/MKmisc: Miscellaneous Functions from M. Kohl

#### Documented in ssize.pcc

```## gamma: tolerance between PCC(infty) and PCC(n)
## stdFC: standardized fold-change
## prev: pervalence
## nrFeatures: total number of features
## sigFeatures: number of significant features
## verbose: print
ssize.pcc <- function(gamma, stdFC, prev = 0.5, nrFeatures, sigFeatures = 20, verbose = FALSE){
pcc.n.a <- function(alpha, n, d.s, nrFeatures, m){
pow <- pt(d.s*sqrt(n)+qt(alpha/2, df = n-2), df = n-2)
T1 <- d.s*m*pow
T2 <- sqrt(m*pow + alpha*(nrFeatures-m))
pnorm(T1/T2)
}
d.s <- stdFC/2
n <- 2
M <- sigFeatures
repeat{
n <- n + 1
m <- seq_len(M)
alpha <- numeric(M)
for(mi in m){
alpha[mi] <- optimize(f = pcc.n.a, interval = c(0, 1), maximum = TRUE,
n = n, d.s = d.s, nrFeatures = nrFeatures, m = mi,
tol = 1e-10)\$maximum
}
pow <- pt(d.s*sqrt(n)+qt(alpha/2, df = n-2), df = n-2)
T1 <- d.s*m*pow
T2 <- sqrt(m*pow + alpha*(nrFeatures-m))
crit <- max(pnorm(d.s*sqrt(m)) - pnorm(T1/T2))
if(verbose){
cat("========================================\n")
cat("Current sample size:\t", n, "\n")
cat("Upper bound Un:\t", crit, "\n")
}
if(crit < gamma) break
}
n1 <- 0.5*n/min(prev, 1-prev)
ns <- ceiling(c(prev*n1, (1-prev)*n1))
NOTE <- "n1 is number of cases, n2 is number of controls"
METHOD <- "Sample Size Planning for Developing Classifiers Using High Dimensional Data"

res <- structure(list(gamma = gamma, prev = prev,
nrFeatures = nrFeatures,
n1 = ns[1], n2 = ns[2],
note = NOTE, method = METHOD),
class = "power.htest")
res
}
```
stamats/MKmisc documentation built on Dec. 14, 2018, 6:54 a.m.