userfriendlyscience (version 0.5-1)

associationMatrix Helper Functions: associationMatrix Helper Functions

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:And in addition, it often contains (among other things, sometimes):For computeEffectSize, this object always contains:And in addition, it often contains (among other things, sometimes):

See Also

meanDiff, associationMatrix

Examples

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