perm.oneway.anova: Permutation One-Way ANOVA Test

In wPerm: Permutation Tests

Description

Performs a permutation (randomization) test for location, using trimmed data (trim = 0 gives untrimmed data) on several independent samples.

Usage

perm.oneway.anova(x, y, trim = 0, ford = NULL, R = 9999)

Arguments

x	a (non-empty) vector of observations of the (response) variable.
y	a vector of the corresponding populations (levels of the factor).
trim	the fraction (0 to 0.5) of observations to be trimmed from each sample; default is 0.
ford	an optional integer vector giving the change from alphabetical order of the populations to some other desired order.
R	number of replications (default = 9999).

Details

The null hypothesis is that the distributions of the variable are identical on all the populations. The alternative hypothesis is that the distributions of the variable have systematically larger values on some of the populations than on others.

Value

A list with class "perm.oneway.anova" containing the following components:

Perm.values	the values of the test statistic obtained from the permutations.
Header	the main title for the output.
Response	the name of the (response) variable.
Factor	the name of the factor.
Levels	the populations (levels of the factor).
n	the sample sizes.
Mean	the sample means.
SD	the sample standard deviations.
Statistic	the test statistic; here, always F.trim.
Observed	the observed value of the test statistic.
P.value	the P-value or a statement like P < 0.001.
p.value	the P-value.
Trim	the trim value.

Author(s)

Neil A. Weiss

Examples

# Last year's energy consumptions, to the nearest 10 million BTU, for
# independent random samples of households in the four U.S. regions.
data("energy")
str(energy)
attach(energy)

# Permutation one-way ANOVA to decide whether the energy distributions
# have systematically larger values in some U.S. regions than in others.
# Regions ordered to Northeast, Midwest, South, and West; 999 replications.
perm.oneway.anova(ENERGY, REGION, ford = c(2,1,3,4), R = 999)

detach(energy)  # clean up

Example output

'data.frame':	20 obs. of  2 variables:
 $ ENERGY: int  13 8 11 12 11 15 10 16 11 13 ...
 $ REGION: Factor w/ 4 levels "Midwest","Northeast",..: 2 2 2 2 2 1 1 1 1 1 ...


 RESULTS OF PERMUTATION 0% TRIMMED ONE-WAY ANOVA
 BASED ON 999 REPLICATIONS  

SUMMARY STATISTICS

    REGION n Mean       SD
 Northeast 5 11.0 1.870829
   Midwest 6 12.5 2.588436
     South 4  7.5 3.000000
      West 5  7.2 1.923538

HYPOTHESIS TEST

 Response Factor Trim Statistic Observed P.value
   ENERGY REGION    0    F.trim 6.324748   0.007

wPerm documentation built on May 2, 2019, 3:02 a.m.