gmvalid-package           package:gmvalid           R Documentation

_V_a_l_i_d_a_t_i_o_n _o_f _g_r_a_p_h_i_c_a_l _m_o_d_e_l_s

_D_e_s_c_r_i_p_t_i_o_n:

     This package provides functions among others that can be used to
     analyse graphical models. This includes e.g. the possibility to
     simulate data sets given a dependence model, to analyze discrete
     graphical models utilizing the MIM program or the CoCo package and
     to quantify associations or interactions.

     Furthermore, a selected graphical model can be validated using the
     bootstrap and the best prediction model can be evaluated for a
     dichotomous outcome variable and several discrete influences using
     cross validation.

_D_e_t_a_i_l_s:


       Package:  gmvalid
       Type:     Package
       Version:  1.0
       Date:     2007-11-07
       License:  GPL (version 2 or later)

     *  This package requires the packages mimR and CoCo as well as the
        software MIM that can be downloaded at <URL:
        http://www.hypergraph.dk>.

     *  The mimR package itself requires the package Rgraphviz that is
        found in the Bioconductor repository.

     *  Further the packages grid, epitools and gtools are required.

     *  Before using any functions that use MIM make sure that the
        program is runnning.

     *  The package mimR will only work properly if your Windows
        temporary directory has a path where every folder has a name
        containing only 8 letters or less.

     *  For mimR requirements we refer to the package's help page
        'mimR'.

     *  If CoCo calculations fail, please type "endCoCo()" to remove
        temporary files. 

     *  CoCo crashes occasionally. If you have recurring problems with
        a specific data set, we suggest to use the MIM-option.
        Otherwise reboot the Computer.

     *  Model formulas have to be specified according to MIM model
        formulas or respectively CoCo model formulas.

_N_o_t_e:

     This work has been supported by the German Research Foundation
      (DFG: <URL: http://www.dfg.de>) under grant scheme PI 345/2-1.

_A_u_t_h_o_r(_s):

     Ronja Foraita, Fabian Sobotka 
      Bremen Institute for Prevention Research and Social Medicine 
      (BIPS)  <URL: http://www.bips.uni-bremen.de>

_R_e_f_e_r_e_n_c_e_s:

     > MIM (<URL: http://www.hypergraph.dk/>) 
      Edwards D (2002)  _An Introduction to Graphical Modelling._
     Springer

     > mimR (<URL: http://genetics.agrsci.dk/~sorenh/mimR/index.html>)
      Hjsgaard S (2004)  _The mimR package for graphical modelling in
     R._ Journal of Statistical Software, 11(6).

     > CoCo (<URL: http://www.badsberg.eu>)
      Badsberg JH (2001)  _A guide to CoCo._ Journal of Statistical
     Software, 6(4).

     > CSI 
      Foraita R (2007)  _A conditional synergy index to assess
     biological interaction._ Working Paper. Please send an e-mail to
     foraita@bips.uni-bremen.de.

_S_e_e _A_l_s_o:

     'mimR',  'CoCo'

_E_x_a_m_p_l_e_s:

         ### Generates a data frame given a dependence model
         gm.a <- gm.modelsim(1000,"ABC,CDE")
         
         ### Modelselection with graphical output
         gm.analysis(gm.a)   
         
         ### Model validation using the bootstrap 
         gm.boot.coco(100,gm.a,recursive=TRUE,follow=TRUE)

         ### Model prediction using cross validation
         gm.cv(3,data=gm.a,strategy="f",options="b")
         
         ### Testing interaction on the penetrance scale
         ### using the conditional synergy index (CSI)
         gm.csi(1,2,3,data=gm.a)

         ### Testing interaction on a additivity scale
         ### using the synergy index (S)
         gm.si(1,2,3,data=gm.a)   

         ### Gamma Coefficient B indpendent D given C
         gm.gamma(2,4,data=gm.a,conditions=3)

