library(pwrss)
power.t.test(ncp = 1.96, df = 99, alpha = 0.05,
alternative = "equivalent", plot = TRUE)
## power ncp.alt ncp.null.1 ncp.null.2 alpha df t.crit.1 t.crit.2
## 0.2371389 0 -1.96 1.96 0.05 99 -0.3155295 0.3155295
power.z.test(ncp = 1.96, alpha = 0.05,
alternative = "not equal", plot = TRUE)
## power ncp.alt ncp.null alpha z.crit.1 z.crit.2
## 0.5000586 1.96 0 0.05 -1.959964 1.959964
power.chisq.test(ncp = 15, df = 20,
alpha = 0.05, plot = TRUE)
## power ncp.alt ncp.null alpha df chisq.crit
## 0.6110368 15 0 0.05 20 31.41043
power.f.test(ncp = 3, df1 = 2, df2 = 98,
alpha = 0.05, plot = TRUE)
## power ncp.alt ncp.null alpha df1 df2 f.crit
## 0.3128778 3 0 0.05 2 98 3.089203
power.t.test(ncp = c(0.50, 1.00, 1.50, 2.00, 2.50), plot = FALSE,
df = 99, alpha = 0.05, alternative = "not equal")
## power ncp.alt ncp.null alpha df t.crit.1 t.crit.2
## 0.07852973 0.5 0 0.05 99 -1.984217 1.984217
## 0.16769955 1.0 0 0.05 99 -1.984217 1.984217
## 0.31785490 1.5 0 0.05 99 -1.984217 1.984217
## 0.50826481 2.0 0 0.05 99 -1.984217 1.984217
## 0.69698027 2.5 0 0.05 99 -1.984217 1.984217
<- pwrss.t.2means(mu1 = 0.20, margin = -0.05, paired = TRUE,
design1 power = 0.80, alpha = 0.05,
alternative = "non-inferior")
## Difference between Two means
## (Paired Samples t Test)
## H0: mu1 - mu2 <= margin
## HA: mu1 - mu2 > margin
## ------------------------------
## Statistical power = 0.8
## n = 101
## ------------------------------
## Alternative = "non-inferior"
## Degrees of freedom = 100
## Non-centrality parameter = 2.512
## Type I error rate = 0.05
## Type II error rate = 0.2
plot(design1)