ctsem

Package: ctsem
Type: Package
Title: Continuous Time Structural Equation Modelling
Version: 1.1.6
Date: 2016-6-12
Authors@R: c(person("Manuel", "Voelkle", role = c("aut","cph"), comment =
"Original development of continuous time model specification within OpenMx,
advisor for further development"),person("Han", "Oud", role =
c("aut","cph"), comment = "Original development of continuous time model
specification within OpenMx"),person("Charles", "Driver", role =
c("aut","cre","cph"), comment = "Further development of continuous time
model specification within OpenMx, package development, documentation and
maintenance",email="driver@mpib-berlin.mpg.de"))
Description: An easily accessible continuous (and discrete) time dynamic
modelling package for panel and time series data, reliant upon the OpenMx.
package (http://openmx.psyc.virginia.edu/) for computation. Most dynamic
modelling approaches to longitudinal data rely on the assumption that time
intervals between observations are consistent. When this assumption is
adhered to, the data gathering process is necessarily limited to a specific
schedule, and when broken, the resulting parameter estimates may be biased
and reduced in power. Continuous time models are conceptually similar to
vector autoregressive models (thus also the latent change models popularised
in a structural equation modelling context), however by explicitly including
the length of time between observations, continuous time models are freed
from the assumption that measurement intervals are consistent. This allows:
data to be gathered irregularly; the elimination of noise and bias due to
varying measurement intervals; parsimonious structures for complex dynamics.
The application of such a model in this SEM framework allows full-information
maximum-likelihood estimates for both N = 1 and N > 1 cases, multiple measured
indicators per latent process, and the flexibility to incorporate additional
elements, including individual heterogeneity in the latent process and
manifest intercepts, and time dependent and independent exogenous covariates.
Furthermore, due to the SEM implementation we are able to estimate a random
effects model where the impact of time dependent and time independent predictors
can be assessed simultaneously, but without the classic problems of random
effects models assuming no covariance between unit level effects and predictors.
License: GPL-3
Depends: R (>= 3.0.0), OpenMx (>= 2.3.0)
URL: http://ctsem.r-forge.r-project.org/
Imports: MASS, Matrix, stats, utils, graphics, methods, grDevices
LazyData: Yes
Suggests: knitr, testthat, PSM, cts, yuima
VignetteBuilder: knitr
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-06-14 19:51:13 UTC; driver
Author: Manuel Voelkle [aut, cph] (Original development of continuous time
model specification within OpenMx, advisor for further development),
Han Oud [aut, cph] (Original development of continuous time model
specification within OpenMx),
Charles Driver [aut, cre, cph] (Further development of continuous time
model specification within OpenMx, package development,
documentation and maintenance)
Maintainer: Charles Driver <driver@mpib-berlin.mpg.de>
Repository: CRAN
Date/Publication: 2016-06-15 18:15:34

Install log

* installing to library '/home/ddbj/local/lib64/R/library'
* installing *source* package 'ctsem' ...
** package 'ctsem' successfully unpacked and MD5 sums checked
** R
** data
*** moving datasets to lazyload DB
** inst
** preparing package for lazy loading
** help
*** installing help indices
  converting help for package 'ctsem'
    finding HTML links ... done
    AnomAuth                                html  
    Oscillating                             html  
    ctCI                                    html  
    ctCompareExpected                       html  
    ctDeintervalise                         html  
    ctExample1                              html  
    ctExample1TIpred                        html  
    ctExample2                              html  
    ctExample2level                         html  
    ctExample3                              html  
    ctExample4                              html  
    ctFit                                   html  
    ctGenerate                              html  
    ctIndplot                               html  
    ctIntervalise                           html  
    ctLongToWide                            html  
    ctModel                                 html  
    ctMultigroupFit                         html  
    ctPSMfit                                html  
    ctPlot                                  html  
    ctRefineTo                              html  
    ctWideNames                             html  
    ctWideToLong                            html  
    ctsem                                   html  
    datastructure                           html  
    longexample                             html  
    plot.ctsemFit                           html  
    plot.ctsemMultigroupFit                 html  
    summary.ctsemFit                        html  
    summary.ctsemMultigroupFit              html  
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (ctsem)
Making 'packages.html' ... done