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##' Diffusion Tensor Imaging: more fractional anisotropy profiles and outcomes
##'
##' A diffusion tensor imaging dataset used in Swihart et al. (2012). Mean
##' diffusivity profiles for the corpus callosum (cca) and parallel diffusivity
##' for the right corticospinal tract (rcst). Accompanying the profiles are the
##' subject ID numbers, visit number, and Paced Auditory Serial Addition Test
##' (pasat) score. We thank Dr. Daniel Reich for making this dataset available.
##'
##' If you use this data as an example in written work, please include the
##' following acknowledgment: ``The MRI/DTI data were collected at Johns
##' Hopkins University and the Kennedy-Krieger Institute"
##'
##' Note: DTI2 uses mean diffusivity of the the corpus callosum rather than
##' fractional anisotropy (FA), and parallel diffusivity of the rcst rather
##' than FA. Please see the documentation for DTI for more about the DTI
##' dataset.
##'
##'
##' @name DTI2
##' @docType data
##' @format A data frame made up of \describe{
##' \item{cca}{a 340 x 93
##' matrix of fractional anisotropy profiles from the corpus callosum;}
##' \item{rcst}{a 340 x 55 matrix of fractional anisotropy
##' profiles from the right corticospinal tract;}
##' \item{id}{numeric vector of subject ID numbers;}
##' \item{visit}{numeric vector of the
##' subject-specific visit numbers;}
##' \item{pasat}{numeric vector
##' containing the PASAT score at each visit.}
##' }
##' @references Goldsmith, J., Bobb, J., Crainiceanu, C., Caffo, B., and Reich,
##' D. (2011). Penalized functional regression. \emph{Journal of Computational
##' and Graphical Statistics}, 20(4), 830--851.
##'
##' Goldsmith, J., Crainiceanu, C., Caffo, B., and Reich, D. (2012).
##' Longitudinal penalized functional regression for cognitive outcomes on
##' neuronal tract measurements. \emph{Journal of the Royal Statistical
##' Society: Series C}, 61(3), 453--469.
##'
##' Swihart, B. J., Goldsmith, J., and Crainiceanu, C. M. (2014). Restricted
##' Likelihood Ratio Tests for Functional Effects in the Functional Linear Model.
##' \emph{Technometrics}, 56, 483--493.
##'
##' @keywords datasets
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