gmvalid-package {gmvalid}R Documentation

Validation of graphical models

Description

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 CoCo package and to quantify associations or interactions.

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

Details

Package: gmvalid
Type: Package
Version: 1.2
Date: 2008-12-18
License: GPL (>=2)

  • This package requires the packages grid, epitools, gtools and CoCo.
  • 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 reboot the computer.
  • Model formulae have to be specified according to CoCo model formulae.

    Note

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

    Author(s)

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

    References

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

    > CSI
    Foraita R (2008) A conditional synergy index to assess biological interaction. http://nbn-resolving.de/urn:nbn:de:gbv:46-diss000111139

    See Also

    CoCo

    Examples

        ### 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)
    
        ### 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)
    
    

    [Package gmvalid version 1.2 Index]