Description Usage Arguments Details Value See Also Examples
This function produces graphs between the sample size, power and the detectable standardized effect size of two-level fractional factorial design.
1 2 3 | plots.2levFr(nfactor, nfraction, interaction = FALSE, delta_type = 1,
delta = c(1, 0, 1), deltao = NULL, alpha = 0.05, beta = 0.2, type = 1,
maxsize = 1000)
|
nfactor |
the number of factor. |
nfraction |
the number of fraction. For example, when a model is 2^(k-p), k is the number of factor and p is the number of fraction. It is called a 1/2^p fraction of the 2^k design. |
interaction |
specifies whether two-way interaction effects are included in a model with the main effects. When |
delta_type |
specifies the type of standardized effect size: 1 for standard deviation type and 2 for range type. |
delta |
vector of effect sizes: |
deltao |
the minimal detectable standardized effect size for power vs the sample size plot when |
alpha |
Type I error. |
beta |
Type II error. |
type |
graph type: 1 for Power vs Delta plot, 2 for Delta vs Sample size plot, and 3 for Power vs Sample size plot. |
maxsize |
tolerance for sample size. |
This function produces graph between the sample size, power 1-beta
and the detectable standardized effect size delta
of two-level fractional factorial design.
According to type
, it displays plot of Power vs Delta, Delta vs Sample size, or Power vs Sample size.
plot of Power vs Delta, Delta vs Sample size, or Power vs Sample size according to type
.
plots.Full
, plots.Split
, plots.Block
.
1 2 3 4 5 6 7 8 | # plot of Power vs Delta for two-level fractional factorial design
# without the interaction effects
plots.2levFr(nfactor=3, nfraction=1, interaction=FALSE,
delta_type=1, delta=c(1, 0, 1), alpha=0.05, beta=0.2, type=1)
# plot of Power vs Sample size for two-level fractional factorial design
# with the interaction effects
plots.2levFr(nfactor=5, nfraction=1, interaction=TRUE,
delta_type=1, delta=c(1, 1, 1), deltao=1, alpha=0.05, beta=0.2, type=3)
|
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