associationMatrix Helper Functions

These objects contain a number of settings and functions for associationMatrix.

Keywords
utilities, bivar
Usage
computeStatistic_t(var1, var2, conf.level=.95, var.equal='test', ...)
computeStatistic_r(var1, var2, conf.level=.95, ...)
computeStatistic_f(var1, var2, conf.level=.95, ...)
computeStatistic_chisq(var1, var2, conf.level=.95, ...)

computeEffectSize_d(var1, var2, conf.level=.95, var.equal='test', ...) computeEffectSize_r(var1, var2, conf.level=.95, ...) computeEffectSize_etasq(var1, var2, conf.level=.95, ...) computeEffectSize_omegasq(var1, var2, conf.level=.95, ...) computeEffectSize_v(var1, var2, conf.level=.95, bootstrap=FALSE, samples=5000, ...)

Arguments
var1
One of the two variables for which to compute a statistic or effect size
var2
The other variable for which to compute the statistic or effect size
conf.level
The confidence for the confidence interval for the effect size
bootstrap
Whether to bootstrap to estimate the confidence interval for Cramer's V. If FALSE, the Fisher's Z conversion is used.
samples
If bootstrapping, the number of samples to generate (of course, more samples means more accuracy and longer processing time).
var.equal
Whether to test for equal variances ('test'), assume equality ('yes'), or assume unequality ('no'). See meanDiff for more information.
Any additonal arguments are sometimes used to specify exactly how statistics and effect sizes should be computed.
Value

associationMatrixStatDefaults and associationMatrixESDefaults contain the default functions from computeStatistic and computeEffectSize that are called (see the help file for associationMatrix for more details).

The other functions return an object with the relevant statistic or effect size, with a confidence interval for the effect size.

For computeStatistic, this object always contains:

statistic
The relevant statistic
statistic.type
The type of statistic
parameter
The degrees of freedom for this statistic
p.raw
The p-value of this statistic for NHST
And in addition, it often contains (among other things, sometimes):
object
The object from which the statistics are extracted

For computeEffectSize, this object always contains:

es
The point estimate for the effect size
esc.type
The type of effect size
ci
The confidence interval for the effect size
And in addition, it often contains (among other things, sometimes):
object
The object from which the effect size is extracted

See Also

meanDiff, associationMatrix

Aliases
  • computeStatistic_t
  • computeStatistic_r
  • computeStatistic_f
  • computeStatistic_chisq
  • computeEffectSize_d
  • computeEffectSize_r
  • computeEffectSize_etasq
  • computeEffectSize_v
  • associationMatrixESDefaults
  • associationMatrixStatDefaults
  • computeEffectSize_omegasq
Examples

computeStatistic_f(Orange$Tree, Orange$circumference)
computeEffectSize_etasq(Orange$Tree, Orange$circumference)

Documentation reproduced from package userfriendlyscience, version 0.6-1, License: GPL (>= 2)

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