plots.2levFr {BDEsize} R Documentation

## Diagnosis Graphs for Sample Size of Two-level Fractional Factorial Design

### Description

This function produces graphs between the sample size, power and the detectable standardized effect size of two-level fractional factorial design.

### Usage

```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)
```

### Arguments

 `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 `interaction = TRUE`, two-way interaction effects are include in a model. `delta_type` specifies the type of standardized effect size: 1 for standard deviation type and 2 for range type. `delta` vector of effect sizes: `delta` for main effects, `delta` for two-way interaction effects, and `delta` for standard deviation of noise. When `interaction=FALSE`, `delta` is 0. `deltao` the minimal detectable standardized effect size for power vs the sample size plot when `type = 3`. `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.

### Details

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.

### Value

plot of Power vs Delta, Delta vs Sample size, or Power vs Sample size according to `type`.

`plots.Full`, `plots.Split`, `plots.Block`.

### Examples

```# 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)
```

[Package BDEsize version 1.6 Index]