associationMatrixHelperFunctions: associationMatrix Helper Functions

In userfriendlyscience: Quantitative Analysis Made Accessible

Description

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

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

Author(s)

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters <[e-mail]>

See Also

meanDiff, associationMatrix

Examples

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

userfriendlyscience documentation built on May 2, 2019, 1:09 p.m.