Description Details Author(s) References Examples
User friendly functions for power and sample size analysis at one-way and two-way ANOVA settings take either effect size or delta and sigma as arguments. They are designed for both one-way and two-way ANOVA settings. In addition, a function for plotting power curves is available for power comparison, which can be easily visualized by statisticians and clinical researchers.
Package: | SPA |
Type: | Package |
Version: | 1.0 |
Date: | 2017-05-01 |
License: | GPL-2 |
There are major five functions in the package. The pwr.1way and pwr.2way functions provide the power analysis for one-way and two-way ANOVA models. The ss.1way and ss.2way functions provide the sample size calculation for one-way and two-way ANOVA models. The pwr.plot function illustrates drawing power curves for different parameter settings.
Pengcheng Lu, Junhao Liu, and Devin Koestler.
Maintainer:Pengcheng Lu <plu2@kumc.edu>
[1] Angela Dean & Daniel Voss (1999). Design and Analysis of Experiments. Springer.
1 2 3 4 5 6 7 8 9 10 11 | ## Example 1
pwr.2way(a=3, b=3, alpha=0.05, size.A=4, size.B=5, f.A=0.8, f.B=0.4)
pwr.2way(a=3, b=3, alpha=0.05, size.A=4, size.B=5, delta.A=4, delta.B=2, sigma.A=2, sigma.B=2)
## Example 2
ss.2way(a=3, b=3, alpha=0.05, beta=0.1, delta.A=1, delta.B=2, sigma.A=2, sigma.B=2, B=100)
## Example 3
n <- seq(2, 30, by=4)
f <- seq(0.1, 1.0, length.out=10)
pwr.plot(n=n, k=5, f=f, alpha=0.05)
|
Balanced two-way analysis of variance power calculation
a = 3
b = 3
n.A = 4
n.B = 5
sig.level = 0.05
power.A = 0.9883206
power.B = 0.6333554
power = 0.6333554
NOTE: power is the minimum power among two factors
Balanced two-way analysis of variance power calculation
a = 3
b = 3
n.A = 4
n.B = 5
sig.level = 0.05
power.A = 0.9908543
power.B = 0.6523857
power = 0.6523857
NOTE: power is the minimum power among two factors
Balanced two-way analysis of variance sample size adjustment
a = 3
b = 3
sig.level = 0.05
power = 0.9
n = 35
NOTE: n is number in each group, total sample = 315
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