added new proportions power analysis; re-ran docs

NAMESPACE

 # Generated by roxygen2: do not edit by hand
 
-export(estimateEffectSizes)
+export(estimateMeanEffectSizes)
+export(estimateProportionEffectSizes)
 import(data.table)
 import(pwr)
 import(reshape2)

R/power.R

 #--- Sample power related functions ---#
 
-#' Estimate detectable effect sizes using statistical power analysis
+#' Estimate detectable mean effect sizes using statistical power analysis
 #'
-#' \code{estimateEffectSizes} calculates required sample sizes for a given set of p values and samples.
+#' \code{estimateMeanEffectSizes} calculates required sample sizes for a given set of p values and samples. Assumes a 1-sided test.
 #'
 #' Returns a data.table of effect sizes for a given sample size. Calculates these for p = 0.01, 0.05, 0.1 & 0.2. Pick out the ones you want.
 #'
@@ -15,9 +15,10 @@
 #' @export
 #' @import data.table
 #' @import reshape2
+#' @import pwr
 #' @family Power functions
 
-estimateEffectSizes <- function(mean,sd,samples,power){
+estimateMeanEffectSizes <- function(mean,sd,samples,power){
   # obtain effect sizes using supplied mean & sd
   sigs <- c(0.01,0.05,0.1,0.2) # force these, can always remove later
   nSigs <- length(sigs)
@@ -29,12 +30,13 @@ estimateEffectSizes <- function(mean,sd,samples,power){
   # loop over significance values
   for (p in 1:nSigs){
     for (s in 1:nSamps){ # loop over the sample sizes
-      result <- power.t.test( # pwr.t.test?
+      result <- power.t.test(
         n = samples[s],
-        delta = NULL,
+        delta = NULL, # what we want to calculate
         sd = sd,
         sig.level = sigs[p],
         power = power,
+        type = c("two.sample"),
         alternative = c("one.sided")
       )
       resultsArray[s,p] <- result$delta/mean # report effect size against sample size
@@ -57,11 +59,11 @@ estimateEffectSizes <- function(mean,sd,samples,power){
   return(longDT) # returned the tidied & long form dt
 }
 
-#' Estimate proportion margins of error using statistical power analysis
+#' Estimate detectable proportion differences for given sample sizes using statistical power analysis
 #'
-#' \code{estimateProportions} calculates required sample sizes for a given set of p values and samples.
+#' \code{estimateProportionEffectSizes} calculates required sample sizes for a given set of p values and samples.
 #'
-#' Returns a data.table of effect sizes for a given sample size. Calculates these for p = 0.01, 0.05, 0.1 & 0.2. Pick out the ones you want.
+#' Returns a data.table of effect sizes (%) for a given sample size. Calculates these for p = 0.01, 0.05, 0.1 & 0.2. Pick out the ones you want.
 #'
 #' @param mean the estimated mean value to use
 #' @param sd the estimated stadnard deviation to use
@@ -75,7 +77,7 @@ estimateEffectSizes <- function(mean,sd,samples,power){
 #' @import pwr
 #' @family Power functions
 
-estimateEffectSizes <- function(mean,sd,samples,power){
+estimateProportionEffectSizes <- function(samples,power){
   # obtain effect sizes using supplied mean & sd
   sigs <- c(0.01,0.05,0.1,0.2) # force these, can always remove later
   nSigs <- length(sigs)
@@ -88,15 +90,13 @@ estimateEffectSizes <- function(mean,sd,samples,power){
   for (p in 1:nSigs){
     for (s in 1:nSamps){ # loop over the sample sizes
       # pwr.t.test?
-      result <- power.t.test(
+      result <- pwr::pwr.2p.test(
         n = samples[s],
-        delta = NULL,
-        sd = sd,
+        h = NULL,
         sig.level = sigs[p],
-        power = power,
-        alternative = c("one.sided")
+        power = power
       )
-      resultsArray[s,p] <- result$delta/mean # report effect size against sample size
+      resultsArray[s,p] <- result$h # report effect size against sample size
     }
   }
   dt <- data.table::as.data.table(resultsArray) # convert to dt for tidying

man/estimateEffectSizes.Rd → man/estimateMeanEffectSizes.Rd

 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/power.R
-\name{estimateEffectSizes}
-\alias{estimateEffectSizes}
-\title{Estimate detectable effect sizes using statistical power analysis}
+\name{estimateMeanEffectSizes}
+\alias{estimateMeanEffectSizes}
+\title{Estimate detectable mean effect sizes using statistical power analysis}
 \usage{
-estimateEffectSizes(mean, sd, samples, power)
-
-estimateEffectSizes(mean, sd, samples, power)
+estimateMeanEffectSizes(mean, sd, samples, power)
 }
 \arguments{
 \item{mean}{the estimated mean value to use}
@@ -15,29 +13,18 @@ estimateEffectSizes(mean, sd, samples, power)
 
 \item{samples}{a list of sample sizes to iterate over}
 
-\item{power}{power value to use}
-
-\item{mean}{the estimated mean value to use}
-
-\item{sd}{the estimated stadnard deviation to use}
-
-\item{samples}{a list of sample sizes to iterate over}
-
 \item{power}{power value to use}
 }
 \description{
-\code{estimateEffectSizes} calculates required sample sizes for a given set of p values and samples.
-
-\code{estimateProportions} calculates required sample sizes for a given set of p values and samples.
+\code{estimateMeanEffectSizes} calculates required sample sizes for a given set of p values and samples. Assumes a 1-sided test.
 }
 \details{
-Returns a data.table of effect sizes for a given sample size. Calculates these for p = 0.01, 0.05, 0.1 & 0.2. Pick out the ones you want.
-
 Returns a data.table of effect sizes for a given sample size. Calculates these for p = 0.01, 0.05, 0.1 & 0.2. Pick out the ones you want.
 }
+\seealso{
+Other Power functions: \code{\link{estimateProportionEffectSizes}}
+}
 \author{
-Ben Anderson, \email{b.anderson@soton.ac.uk}
-
 Ben Anderson, \email{b.anderson@soton.ac.uk}
 }
 \concept{Power functions}

man/estimateProportionEffectSizes.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/power.R
+\name{estimateProportionEffectSizes}
+\alias{estimateProportionEffectSizes}
+\title{Estimate detectable proportion differences for given sample sizes using statistical power analysis}
+\usage{
+estimateProportionEffectSizes(samples, power)
+}
+\arguments{
+\item{samples}{a list of sample sizes to iterate over}
+
+\item{power}{power value to use}
+
+\item{mean}{the estimated mean value to use}
+
+\item{sd}{the estimated stadnard deviation to use}
+}
+\description{
+\code{estimateProportionEffectSizes} calculates required sample sizes for a given set of p values and samples.
+}
+\details{
+Returns a data.table of effect sizes (%) for a given sample size. Calculates these for p = 0.01, 0.05, 0.1 & 0.2. Pick out the ones you want.
+}
+\seealso{
+Other Power functions: \code{\link{estimateMeanEffectSizes}}
+}
+\author{
+Ben Anderson, \email{b.anderson@soton.ac.uk}
+}
+\concept{Power functions}