psych (version 1.3.10.12)

psych.misc: Miscellaneous helper functions for the psych package

Description

This is a set of minor, if not trivial, helper functions. lowerCor finds the correlation of x variables and then prints them using lowerMat which is a trivial, but useful, function to round off and print the lower triangle of a matrix. reflect reflects the output of a factor analysis or principal components analysis so that one or more factors is reflected. (Requested by Alexander Weiss.) progressBar prints out ... as a calling routine (e.g., tetrachoric) works through a tedious calculation. shannon finds the Shannon index (H) of diversity or of information. test.all tests all the examples in a package.

Usage

psych.misc()
lowerCor(x,digits=2,use="pairwise",method="pearson")
lowerMat(R, digits = 2)
reflect(f,flip=NULL)
progressBar(value,max,label=NULL) 
shannon(x,correct=FALSE,base=2)
test.all(p)

Arguments

R
A rectangular matrix or data frame (probably a correlation matrix)
x
A data matrix or data frame
digits
round to digits
use
Should pairwise deletion be done, or one of the other options to cor
method
"pearson", "kendall", "spearman"
value
the current value of some looping variable
max
The maximum value the loop will achieve
label
what function is looping
f
The object returned from either a factor analysis (fa) or a principal components analysis (principal)
flip
The factor or components to be reversed keyed (by factor number)
correct
Correct for the maximum possible information in this item
base
What is the base for the log function (default=2, e implies base = exp(1) )
p
The name of a package to be activated and then have all the examples tested.

Value

  • The lower triangle of a matrix, rounded to digits with titles abbreviated to digits + 3 (lowerMat) or a series of dots (progressBar).

    lowerCor prints the lower diagonal correlation matrix but returns (invisibly) the full correlation matrix found with the use and method parameters. The default values are for pairwise deletion of variables, and to print to 2 decimal places.

    shannon finds Shannon's H index of information. Used for estimating the complexity or diversity of the distribution of responses in a vector or matrix. $$H = -\sum{p_i log(p_i) }$$

    link{test.all} allows one to test all the examples in specified package. This allows us to make sure that those examples work when other packages are also loaded.

See Also

corr.test to find correlations, count the pairwise occurrences, and to give significance tests for each correlation. r.test for a number of tests of correlations, including tests of the difference between correlations. lowerUpper will display the differences between two matrices.

Examples

Run this code
lowerMat(Thurstone)
lowerCor(bfi[1:10])
f3 <- fa(Thurstone,3)
f3r <- reflect(f3,2)  #reflect the second factor
#find the complexity of the response patterns of the iqitems.
round(shannon(iqitems),2) 
#test.all('BinNor')  #Does the BinNor package work when we are using other packages

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