Nothing
#' The dominanceanalysis package allows to perform the dominance analysis for multiple regression models, such as OLS (univariate and multivariate), GLM and HLM.
#' The dominance analysis on this package is performed by \code{\link{dominanceAnalysis}}
#' function. To perform bootstrap procedures you should use \code{\link{bootDominanceAnalysis}}
#' function. For both, standard \code{print} and \code{summary} functions are provided.
#'
#' @section Main Features:
#' \itemize{
#' \item Provides complete, conditional and general dominance analysis for lm (univariate and multivariate), lmer and glm (family=binomial) models.
#' \item Covariance / correlation matrixes could be used as input for OLS dominance analysis, using \code{\link{lmWithCov}} and \code{\link{mlmWithCov}} methods, respectively.
#' \item Multiple criteria can be used as fit indices, which is useful especially for HLM.
#' }
#'
#' @section About Dominance Analysis:
#' Dominance analysis is a method developed to evaluate the importance of each predictor
#' in the selected regression model: "one predictor is 'more important than another'
#' if it contributes more to the prediction of the criterion than does its competitor
#' at a given level of analysis." (Azen & Budescu, 2003, p.133).
#'
#' The original method was developed for OLS regression (Budescu, 1993).
#' Later, several definitions of dominance and bootstrap procedures
#' were provided by Azen & Budescu (2003), as well as adaptations
#' to Generalized Linear Models (Azen & Traxel, 2009)
#' and Hierarchical Linear Models (Luo & Azen, 2013).
#'
#' @name dominanceanalysis-package
#' @aliases dominanceanalysis
#' @docType package
#' @title Dominance analysis for general, generalized and mixed linear models
#' @author Claudio Bustos \email{clbustos@gmail.com}, Filipa Coutinho Soares (documentation)
#' @seealso \code{\link{dominanceAnalysis}} , \code{\link{bootDominanceAnalysis}}
#' @references
#' \itemize{
#' \item Budescu, D. V. (1993). Dominance analysis: A new approach to the problem of relative importance of predictors in multiple regression. Psychological Bulletin, 114(3), 542-551. doi:10.1037/0033-2909.114.3.542
#' \item Azen, R., & Budescu, D. V. (2003). The dominance analysis approach for comparing predictors in multiple regression. Psychological Methods, 8(2), 129-148. doi:10.1037/1082-989X.8.2.129
#' \item Azen, R., & Budescu, D. V. (2006). Comparing Predictors in Multivariate Regression Models: An Extension of Dominance Analysis. Journal of Educational and Behavioral Statistics, 31(2), 157-180. doi:10.3102/10769986031002157
#' \item Azen, R., & Traxel, N. (2009). Using Dominance Analysis to Determine Predictor Importance in Logistic Regression. Journal of Educational and Behavioral Statistics, 34(3), 319-347. doi:10.3102/1076998609332754
#' \item Luo, W., & Azen, R. (2013). Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis. Journal of Educational and Behavioral Statistics, 38(1), 3-31. doi:10.3102/1076998612458319
#' }
#' @examples
#' # Basic dominance analysis
#'
#' data(longley)
#' lm.1<-lm(Employed~.,longley)
#' da<-dominanceAnalysis(lm.1)
#' print(da)
#' summary(da)
#' plot(da,which.graph='complete')
#' plot(da,which.graph='conditional')
#' plot(da,which.graph='general')
#'
#' # Dominance analysis for HLM
#'
#' library(lme4)
#' x1<-rnorm(1000)
#' x2<-rnorm(1000)
#' g<-gl(10,100)
#' g.x<-rnorm(10)[g]
#' y<-2*x1+x2+g.x+rnorm(1000,sd=0.5)
#' lmm1<-lmer(y~x1+x2+(1|g))
#' lmm0<-lmer(y~(1|g))
#' da.lmm<-dominanceAnalysis(lmm1, null.model=lmm0)
#' print(da.lmm)
#' summary(da.lmm)
#'
#'
#' # GLM analysis
#'
#' x1<-rnorm(1000)
#' x2<-rnorm(1000)
#' x3<-rnorm(1000)
#' y<-runif(1000)<(1/(1+exp(-(2*x1+x2+1.5*x3))))
#' glm.1<-glm(y~x1+x2+x3,family="binomial")
#' da.glm<-dominanceAnalysis(glm.1)
#' print(da.glm)
#' summary(da.glm)
#'
#' # Bootstrap procedure
#'
#' \donttest{
#' da.boot<-bootDominanceAnalysis(lm.1,R=1000)
#' summary(da.boot)
#'
#' da.glm.boot<-bootDominanceAnalysis(glm.1,R=200)
#' summary(da.glm.boot)
#' }
NULL
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.