R: Power Simulation for One-Factorial All-Pairs and Many-To-One...

powerMCTests {PMCMRplus} | R Documentation

## Power Simulation for One-Factorial All-Pairs and Many-To-One Comparison Tests

### Description

Performs power simulation for one-factorial all-pairs and Many-To-One comparison tests.

### Usage

    powerMCTests(
      mu,
      n = 10,
      errfn = c("Normal", "Lognormal", "Exponential", "Chisquare", "TDist", "Cauchy",
        "Weibull"),
      parms = list(mean = 0, sd = 1),
      test = c("kwManyOneConoverTest", "kwManyOneDunnTest", "kwManyOneNdwTest",
        "vanWaerdenManyOneTest", "normalScoresManyOneTest", "dunnettTest",
        "tamhaneDunnettTest", "ManyOneUTest", "kwAllPairsNemenyiTest", "kwAllPairsDunnTest",
        "kwAllPairsConoverTest", "normalScoresAllPairsTest", "vanWaerdenAllPairsTest",
        "dscfAllPairsTest", "gamesHowellTest", "lsdTest", "scheffeTest", "tamhaneT2Test",
        "tukeyTest", "dunnettT3Test", "pairwise.t.test", "pairwise.wilcox.test",
        "adManyOneTest", "adAllPairsTest", "bwsManyOneTest",      "bwsAllPairsTest",
        "welchManyOneTTest"),
      alternative = c("two.sided", "greater", "less"),
      p.adjust.method = c("single-step", p.adjust.methods),
      alpha = 0.05,
      FWER = TRUE,
      replicates = 1000
    )

### Arguments

`mu` | numeric vector of group means.
`n` | number of replicates per group. If `n` is a scalar, then a balanced design is assumed. Otherwise, `n` must be a vector of same length as `mu`.
`errfn` | the error function. Defaults to `"Normal"`.
`parms` | a list that denotes the arguments for the error function. Defaults to `list(mean=0, sd=1)`.
`test` | the multiple comparison test for which the power analysis is to be performed. Defaults to `"kwManyOneConoverTest"`.
`alternative` | the alternative hypothesis. Defaults to `"two.sided"`, ignored if the selected error function does not use this argument.
`p.adjust.method` | method for adjusting p values (see `p.adjust`).
`alpha` | the nominal level of Type I Error.
`FWER` | logical, indicates whether the family-wise error should be computed. Defaults to `TRUE`.
`replicates` | the number of Monte Carlo replicates or runs. Defaults to `1000`.

### Details

The linear model of a one-way ANOVA can be written as:

X_{ij} = μ_i + ε_{ij}

For each Monte Carlo run, the function simulates ε_{ij} based on the given error function and the corresponding parameters. Then the specified all-pairs or many-to-one comparison test is performed. Finally, several effect sizes (Cohen's f ans R-squared), error rates (per comparison error rate, false discovery rate and familywise error rate) and test powers (any-pair power, average per-pair power and all-pairs power) are calculated.

### Value

An object with class `powerPMCMR`.

### Examples

    ## Not run:
    mu <- c(0, 0, 1, 2)
    n <- c(5, 4, 5, 5)
    set.seed(100)
    powerMCTests(mu, n, errfn="Normal",
     parms=list(mean=0, sd=1),
     test="dunnettTest", replicates=1E4)

    powerMCTests(mu, n, errfn="Normal",
     parms=list(mean=0, sd=1),
     test="kwManyOneDunnTest", p.adjust.method = "bonferroni",
     replicates=1E4)

    ## End(Not run)

[Package PMCMRplus version 1.7.1 Index]