R/samplesize_RSABE_NTID.R

Defines functions sampleN.NTIDFDA

Documented in sampleN.NTIDFDA

#---------------------------------------------------------------------------
# Sample size for partial and full replicate design and scaled ABE 
# via simulated (empirical) power
# 
# Author: dlabes
#---------------------------------------------------------------------------

sampleN.NTIDFDA <- function(alpha=0.05, targetpower=0.8, theta0, theta1, theta2, 
                            CV, design=c("2x2x4", "2x2x3"),
                            nsims=1E5, nstart, imax=100,
                            print=TRUE, details=TRUE, setseed=TRUE)
{
  if (missing(theta1) & missing(theta2)) theta1 <- 0.8
  if (missing(theta1)) theta1=1/theta2
  if (missing(theta2)) theta2=1/theta1
  
  if (missing(theta0)) theta0 <- 0.975      # tighter content requirement
  if ( (theta0<=theta1) | (theta0>=theta2) ) {
    stop("True ratio ",theta0," not between margins ",theta1," / ",theta2,"!", 
         call.=FALSE)
  }
  if (missing(CV)) stop("CV(s) must be given!", call.=FALSE)
  
  regulator <- "FDA"
  r_const   <- -log(0.9)/0.1  # =log(1.111111)/0.1
  # no widening/shrinking after CVcap
  # scap = 0.2117905, CVcap=0.2142 if theta2=1.25
  CVcap     <- se2CV(log(theta2)/r_const)               

  CVwT <- CV[1]
  if (length(CV)>1) CVwR <- CV[2] else CVwR <- CVwT
  if (length(CV)>2) warning("Only first 2 entries from CV vector used.")
  s2wT <- CV2mse(CVwT)
  s2wR <- CV2mse(CVwR)
  
  design <- match.arg(design)
  # we are treating only balanced designs
  # thus we use here bk - the design constant for ntotal
  # expressions for the df's
  if (design=="2x2x4") {
    seqs  <- 2
    bk    <- 1.0    # needed for n0
    dfe   <- parse(text="n-2", srcfile=NULL)
    dfRRe <- parse(text="n-2", srcfile=NULL)
    dfTTe <- parse(text="n-2", srcfile=NULL)
    # expectation of mse of the ANOVA of intra-subject contrasts T-R
    Emse  <- (s2wT + s2wR)/2
    desi  <- "2x2x4 (TRTR|RTRT)"
  }
  if (design=="2x2x3") {
    seqs  <- 2
    bk    <- 1.5    # needed for n0
    dfe   <- parse(text="n-2", srcfile=NULL)
    dfRRe <- parse(text="n/2-1", srcfile=NULL)  # balanced only
    dfTTe <- parse(text="n/2-1", srcfile=NULL)  # balanced only
    # expectation of mse of the ANOVA of intra-subject contrasts T-R
    Emse  <- 1.5*(s2wT + s2wR)/2                # balanced only
    desi  <- "2x2x3 (TRT|RTR)"
  }
  
  mlog <- log(theta0)
  ltheta1 <- -r_const*sqrt(s2wR)
  ltheta2 <- -ltheta1

  # 'design' constant for nstart
  # this is purely empirical to accelarate n0!
  if(design=="2x2x4") bkk <- 1.55 else bkk <- 1.65
  
  # CVcap=0.2142 if theta2=1.25
  if (CVwR > CVcap) { # outside the acceptance range shrinking
    ltheta1 <- log(theta1)
    ltheta2 <- log(theta2)
    bkk     <- bk
  }
  
  if (print){
    cat("\n+++++++++++ FDA method for NTIDs ++++++++++++\n")
    cat("           Sample size estimation\n")
    cat("---------------------------------------------\n")
    cat("Study design: ",desi,"\n")
    cat("log-transformed data (multiplicative model)\n")
    cat(nsims,"studies for each step simulated.\n\n")
    cat("alpha  = ",alpha,", target power = ", targetpower,"\n", sep="")
    cat("CVw(T) = ",CVwT,", CVw(R) = ",CVwR,"\n", sep="")
    cat("True ratio     =",theta0,"\n")
    cat("ABE limits     =", theta1, "...", theta2,"\n")
    if (details) {
      cat("Implied scABEL =", formatC(exp(ltheta1), format="f", digits=4), 
          "...", formatC(exp(ltheta2), format="f", digits=4),"\n")
    }
    cat("Regulatory settings:",regulator,"\n")
    if (details) { 
      cat("- Regulatory const. =",r_const,"\n")
      # CVcap?
      cat("- 'CVcap'           =", formatC(CVcap, format="f", digits=4),"\n")
    }     
  }
  # attention! it may be happen that mlog is outside ltheta1, ltheta2!
  # for example mlog=log(0.95), s2wR=CV2mse(0.04)
  # gave mlog=-0.05129329 , ltheta1=-0.04212736
  if (mlog<ltheta1 | mlog>ltheta2) {
    stop("theta0 outside implied scABE limits! No sample size estimable.", call. = FALSE)
  }  
  # -----------------------------------------------------------------
  # nstart? from sampleN0 with shrunken/widened limits
  # does'nt fit always really good 
  if (missing(nstart)){
    n <- .sampleN0(alpha=alpha, targetpower, ltheta1, ltheta2, diffm=mlog, 
                   se=sqrt(Emse), steps=seqs, bk=bkk, diffmthreshold=0.01)
    #cat("n0=",n,"\n")
  } else n <- seqs*round(nstart/seqs)
  nmin <- 6
  if(n<nmin) n <- nmin
  # we are simulating for balanced designs
  C3 <- 1/n
  # sd of the sample mean T-R (point estimator)
  sdm  <- sqrt(Emse*C3)
  df   <- eval(dfe)
  dfRR <- eval(dfRRe)
  dfTT <- eval(dfTTe)
  
  if(setseed) set.seed(123456)
  p <- .power.NTID(mlog, sdm, C3, Emse, df, s2wR, dfRR, s2wT, dfTT, nsims, 
                   r_const, ln_lBEL=log(theta1),ln_uBEL=log(theta2), alpha)
  pwr <- as.numeric(p["BE"]);
  
  if (details) {
    cat("\nSample size search\n")
    cat(" n     power\n")
    # do not print first too high
    # this is for cases with only one step-down and than step up
    if (pwr<=targetpower) cat( n," ", formatC(pwr, digits=6, format="f"),"\n")
  }
  iter <- 0
  nmin <- 6 
  # iter>100 is emergency brake
  # --- loop until power <= target power, step-down
  down <- FALSE; up <- FALSE
  while (pwr>targetpower) {
    if (n<=nmin) { 
      if (details & iter==0) cat( n," ", formatC(pwr, digits=6, format="f"),"\n")
      break
    }
    down <- TRUE
    n  <- n-seqs     # step down if start power is to high
    iter <- iter + 1
    C3 <- 1/n
    # sd of the sample mean T-R (point estimator)
    sdm  <- sqrt(Emse*C3)
    df   <- eval(dfe)
    dfRR <- eval(dfRRe)
    dfTT <- eval(dfTTe)
    
    if(setseed) set.seed(123456)
    p <- .power.NTID(mlog, sdm, C3, Emse, df, s2wR, dfRR, s2wT, dfTT, nsims, 
                     r_const, ln_lBEL=log(theta1),ln_uBEL=log(theta2), alpha)
    pwr <- as.numeric(p["BE"]);
    
    # do not print first step down
    if (details) cat( n," ", formatC(pwr, digits=6, format="f"),"\n")
    if (iter>imax) break  
    # loop results in n with power too low
    # must step one up again. is done in the next loop
  }
  while (pwr<targetpower) {
    up   <- TRUE ; down <- FALSE
    n    <- n+seqs  # step up
    iter <- iter+1
    C3 <- 1/n
    sdm  <- sqrt(Emse*C3)
    df   <- eval(dfe)
    dfRR <- eval(dfRRe)
    dfTT <- eval(dfTTe)
    
    if(setseed) set.seed(123456)
    p <- .power.NTID(mlog, sdm, C3, Emse, df, s2wR, dfRR, s2wT, dfTT, nsims, 
                     r_const, ln_lBEL=log(theta1),ln_uBEL=log(theta2), alpha)
    pwr <- as.numeric(p["BE"]);
    
    if (details) cat( n," ", formatC(pwr, digits=6, format="f"),"\n")
    if (iter>imax) break 
  }
  nlast <- n
  if (up & pwr<targetpower) {
    n <- NA
    if (details) cat("Sample size search failed!\n")
  }
  if (down & pwr>targetpower & n != nmin) {
    n <- NA
    if (details) cat("Sample size search failed!\n")
  }
  
  if (print && !details) {
    cat("\nSample size\n")
    cat(" n     power\n")
    cat( n," ", formatC(pwr, digits=6, format="f"),"\n")
    if (is.na(n)) cat("Sample size search failed!\n")
  }
  if (print) cat("\n")
  
  #return results as data.frame
  res <- data.frame(design=design, alpha=alpha, CVwT=CVwT, CVwR=CVwR,
                    theta0=theta0, theta1=theta1, theta2=theta2, n=n, power=pwr, 
                    targetpower=targetpower,nlast=nlast)
  names(res) <-c("Design","alpha","CVwT","CVwR","theta0","theta1","theta2",
                 "Sample size", "Achieved power", "Target power","nlast")
  
  if (print | details) return(invisible(res)) else return(res)
  
} # end function

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PowerTOST documentation built on Jan. 18, 2021, 5:07 p.m.