Description Usage Arguments Details Value Author(s) References Examples
Calculate sample size for two-way ANOVA models.
1 2 |
a |
Number of groups in Factor A |
b |
Number of groups in Factor B |
alpha |
Significant level (Type I error probability) |
beta |
Type II error probability (Power=1-beta) |
f.A |
Effect size of Factor A |
f.B |
Effect size of Factor B |
delta.A |
The smallest difference among a groups in Factor A |
delta.B |
The smallest difference among b groups in Factor B |
sigma.A |
Standard deviation, i.e. square root of variance in Factor A |
sigma.B |
Standard deviation, i.e. square root of variance in Factor B |
B |
Iteration times, default number is 100 |
Beta is the type II error probability which equals 1-power. For example, if the target power is 85% (=0.85), the corresponding beta equals 0.15. If effect size f is known, plug it in to the function; If delta and sigma are known instead of effect size, put NULL to f.
Object of class "power.htest", a list of the arguments (including the computed one) augmented with "method" and "note" elements.
Pengcheng Lu, Junhao Liu, and Devin Koestler.
Angela Dean & Daniel Voss (1999). Design and Analysis of Experiments. Springer.
1 2 3 4 5 6 7 | ## Example 1
ss.2way(a=3, b=3, alpha=0.05, beta=0.1, f.A=0.4, f.B=0.2, B=100)
ss.2way(a=3, b=3, alpha=0.05, beta=0.1, f.A=0.4, f.B=0.2,
delta.A=NULL, delta.B=NULL, sigma.A=NULL, sigma.B=NULL, B=100)
## 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)
|
Balanced two-way analysis of variance sample size adjustment
a = 3
b = 3
sig.level = 0.05
power = 0.9
n = 36
NOTE: n is number in each group, total sample = 324
Balanced two-way analysis of variance sample size adjustment
a = 3
b = 3
sig.level = 0.05
power = 0.9
n = 36
NOTE: n is number in each group, total sample = 324
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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