oneway: oneway

In rosetta: Parallel Use of Statistical Packages in Teaching

oneway

Description

The oneway function wraps a number of analysis of variance functions into one convenient interface that is similar to the oneway anova command in SPSS.

Usage

oneway(
  y,
  x,
  posthoc = NULL,
  means = FALSE,
  fullDescribe = FALSE,
  levene = FALSE,
  plot = FALSE,
  digits = 2,
  omegasq = TRUE,
  etasq = TRUE,
  corrections = FALSE,
  pvalueDigits = 3,
  t = FALSE,
  conf.level = 0.95,
  posthocLetters = FALSE,
  posthocLetterAlpha = 0.05,
  overrideVarNames = NULL,
  silent = FALSE
)

## S3 method for class 'oneway'
print(
  x,
  digits = x$input$digits,
  pvalueDigits = x$input$pvalueDigits,
  na.print = "",
  ...
)

## S3 method for class 'oneway'
pander(
  x,
  digits = x$input$digits,
  pvalueDigits = x$input$pvalueDigits,
  headerStyle = "**",
  na.print = "",
  ...
)

Arguments

y	y has to be a numeric vector.
x	x has to be vector that either is a factor or can be converted into one.
posthoc	Which post-hoc tests to conduct. Valid values are any correction methods in p.adjust.methods (at the time of writing of this document, "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none"), as well as "tukey" and "games-howell".
means	Whether to show the means for the y variable in each of the groups determined by the x variable.
fullDescribe	If TRUE, not only the means are shown, but all statistics acquired through the 'describe' function in the 'psych' package are shown.
levene	Whether to show Levene's test for equality of variances (using car's leveneTest function but specifying mean as function to compute the center of each group).
plot	Whether to show a plot of the means of the y variable in each of the groups determined by the x variable.
digits	The number of digits to show in the output.
omegasq	Whether to show the omega squared effect size.
etasq	Whether to show the eta squared effect size (this is biased and generally advised against; omega squared is less biased).
corrections	Whether to show the corrections for unequal variances (Welch and Brown-Forsythe).
pvalueDigits	The number of digits to show for p-values; smaller p-values will be shown as <.001 or <.0001 etc.
t	Whether to transpose the dataframes with the means (if requested) and the anova results. This can be useful for blind people.
conf.level	Confidence level to use when computing the confidence interval for eta^2. Note that the function we use doubles the 'unconfidence' level to maintain consistency with the NHST value (see http://yatani.jp/HCIstats/ANOVA#RCodeOneWay, http://daniellakens.blogspot.nl/2014/06/calculating-confidence-intervals-for.html or Steiger, J. H. (2004). Beyond the F test: Effect size confidence intervals and tests of close fit in the analysis of variance and contrast analysis. Psychological methods, 9(2), 164-82. doi:10.1037/1082-989X.9.2.164
posthocLetters	Whether to also compute and show the letters signifying differences between groups when conducting post hoc tests. This requires package multcompView to be installed.
posthocLetterAlpha	The alpha to use when determining whether groups have different means when using posthocLetters.
overrideVarNames	Can be used to override the variable names (most useful in functions).
silent	Whether to show warnings and other diagnostic information or remain silent.
na.print	How to print missing values.
...	Any additional arguments are passed to the print or pander function.
headerStyle	The header pre- and suffix to use when pandering the result (useful when working with Markdown).

Value

A list of three elements:

input	List with input arguments
intermediate	List of intermediate objects, such as the aov and Anova (from the car package) objects.
output	List with etasq, the effect size, and dat, a dataframe with the Oneway Anova results.

Note

By my knowledge the Brown-Forsythe correction was not yet available in R. I took this from the original paper (directed there by Field, 2014). Note that this is the corrected F value, not the Brown-Forsythe test for normality!

Author(s)

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters [e-mail]

References

Brown, M., & Forsythe, A. (1974). The small sample behavior of some statistics which test the equality of several means. Technometrics, 16(1), 129-132. https://doi.org/10.2307/1267501

Field, A. (2014) Discovering statistics using SPSS (4th ed.). London: Sage.

Steiger, J. H. (2004). Beyond the F test: Effect size confidence intervals and tests of close fit in the analysis of variance and contrast analysis. Psychological methods, 9(2), 164-82. doi:10.1037/1082-989X.9.2.164

Examples

### Do a oneway Anova
oneway(y=ChickWeight$weight, x=ChickWeight$Diet);

### Also order means and transpose the results
oneway(y=ChickWeight$weight, x=ChickWeight$Diet, means=TRUE, t=TRUE);

rosetta documentation built on March 7, 2023, 7:40 p.m.