Estimation techniques for the reliability estimate: Maximized
Lambda4
This code provides 4 different estimates of maximized
lambda4 (A split half reliability estimate)

Currently the code features 2 new ways to calculate
reliability.  Both are based on a combination of Cronbach's
alpha and Maximal-type reliability coefficients but use
different maximization procedures.

Currently the package includes 4 functions.  Three of
which are different methods of calculating Guttman's lambda4
coefficient.  One allows the user to select the item splits.
The remaining two are new methods to calculate reliability.
Both are based on a combination of Cronbach's alpha and
Maximal-type reliability coefficients but use different
maximization procedures.

Estimation techniques for the reliability estimate: Maximized
Lambda4.
Currently the package includes 5 functions.  Three of
which are different methods of calculating Guttman's lambda4
coefficient.  One allows the user to select the item splits.
The remaining two are new methods to calculate reliability.
Both are based on a combination of Cronbach's alpha and
Maximal-type reliability coefficients but use different
maximization procedures.  Lastly, lambda3 (Cronbach's alpha) is
included for convenience.

Collection of Internal Consistency Reliability Coefficients.
Currently the package includes 14 methods for calculating internal
consistency reliability but is still growing.  The package allows users
access to whichever reliability estimator is deemed most appropriate for
their situation.
'angoff.R' 'bin.combs.R' 'cov.lambda4.R' 'impute.cov.R'
'kristof.R' 'lambda1.R' 'lambda2.R' 'lambda3.R' 'lambda5.R'
'lambda6.R' 'omega.tot.R' 'print.Lambda4.pkg.R'
'quant.lambda4.R' 'raju.R' 'user.lambda4.R' 'guttman.R'

Estimation, plotting, testing of Lambert W random
variables

Lambert W parameter estimation, plots, simulation (Skew
Analysis)
Lambert W random variables (RV) offer a new way of dealing
with slightly skewed data. It is based on an input/ouput
framework - for details see References. This package contains
the most important functions to perform an adequate analysis.
Lambert W data can be simulated, parameters estimated and
results can be plotted in a proper way.