# R/pairt.R In pwr2ppl: Power Analyses for Common Designs (Power to the People)

#### Documented in pairt

```#'Compute power for a Paired t-test
#'Takes means, sd, and sample sizes. Alpha is .05 by default, alternative values may be entered by user.
#'correlation (r) defaults to .50.
#'@param m1 Mean for Pre Test
#'@param m2 Mean for Post Test
#'@param s Standard deviation
#'@param r Correlation pre-post measures (default is .50)
#'@param n Sample size
#'@param alpha Type I error (default is .05)
#'@examples
#'pairt(m1=25,m2=20, s = 5, n = 25, r = .5)
#'@return Power for the Paired t-test
#'@export

pairt<-function(m1=NULL,m2=NULL, s=NULL, n=NULL, r = NULL, alpha=.05)
{
cov<-s^2
corr<-r*cov
data <- MASS::mvrnorm(n, mu = c(m1,m2), Sigma = matrix(c(cov,corr,corr,cov), ncol = 2),
empirical = TRUE)
data<-as.data.frame(data)
t<-stats::t.test(data\$V1,data\$V2, paired=TRUE)
lambda<-abs(t\$statistic)^2
minusalpha<-1-alpha
Ft<-stats::qf(minusalpha, 1, n-1)
Power<-round(1-stats::pf(Ft, 1,n-1,lambda),4)
message("Power for n = ", n, " is ", Power)
result <- data.frame(matrix(ncol = 2))
colnames(result) <- c("n", "Power")
result[, 1]<-n
result[, 2]<-Power
output<-na.omit(result)
rownames(output)<- c()
invisible(output)
}
```

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pwr2ppl documentation built on Sept. 6, 2022, 5:06 p.m.