Item analysis with alpha standard error and principal axis
factoring for continuous variable scales (with plots).

Relabel Loadings from MCMC Output for Confirmatory Factor
Analysis
c(person("S. McKay", "Curtis", role=c("aut", "cre"), email="s.mckay.curtis@gmail.com"),
person("Elena A.", "Erosheva", role=c("aut")))
In confirmatory factor analysis (CFA), structural constraints
typically ensure that the model is identified up to all possible reflections,
i.e., column sign changes of the matrix of loadings. Such reflection invariance
is problematic for Bayesian CFA when the reflection modes are not well separated
in the posterior distribution. Imposing rotational constraints -- fixing
some loadings to be zero or positive in order to pick a factor solution that
corresponds to one reflection mode -- may not provide a satisfactory solution
for Bayesian CFA. The function 'relabel' uses the relabeling algorithm of
Erosheva and Curtis to correct for sign invariance in MCMC draws from CFA
models. The MCMC draws should come from Bayesian CFA models that are fit without
rotational constraints.
S. McKay Curtis [aut, cre],
Elena A. Erosheva [aut]

Relative importance of regressors in linear models
relaimpo provides several metrics for assessing relative importance in linear models. These can be printed, plotted and bootstrapped. The recommended metric is lmg, which provides a decomposition of the model explained variance into non-negative contributions. There is a version of this package available that additionally provides a new and also recommended metric called pmvd. If you are a non-US user, you can download this extended version from Ulrike Groempings web site.

relaimpo provides several metrics for assessing relative importance in linear models. These can be printed, plotted and bootstrapped. The recommended metrics are lmg or pmvd, which provide a decomposition of the model explained variance into non-negative contributions. This version of relaimpo is licensed outside the US only. If you are a US-user, you can download a global version (without pmvd) from CRAN.