SpecifyCoefficient {cmm}R Documentation

SpecifyCoefficient

Description

Gives the generalized exp-log specification for various coefficients

Usage

SpecifyCoefficient(name, arg, rep=1)

Arguments

name character: name of desired coefficient
arg an argument specific to the coefficient, e.g., a vector of scores or number of rows and colums.
rep number of repetitions of the coefficient

Details

Currently the following coefficients are implemented:

 SpecifyCoefficient("Mean",scores)
 SpecifyCoefficient("Variance",scores)
 SpecifyCoefficient("StandardDeviation",scores)
 SpecifyCoefficient("GiniMeanDifference",scores)
 SpecifyCoefficient("Entropy",k)
 SpecifyCoefficient("DiversityIndex",k)
 SpecifyCoefficient("Covariance",list(xscores,yscores))
 SpecifyCoefficient("Correlation",list(xscores,yscores))
 SpecifyCoefficient("KendallTau",list(r,c))
 SpecifyCoefficient("GoodmanKruskalGammma",list(r,c))
 SpecifyCoefficient("CohenKappa",r)
 SpecifyCoefficient("DifferenceInProportions",m)
 SpecifyCoefficient("LogOddsRatio",)
 SpecifyCoefficient("LoglinearParameters",dim)
 SpecifyCoefficient("Probabilities",dim)
 SpecifyCoefficient("LogProbabilities",dim)
 SpecifyCoefficient("ConditionalProbabilities",list(var,condvar,dim))

Here, scores is a score vector, e.g., c(1,2,3,4,5); k is the number of cells in a table; r is the number of rows and columns of a square table; dim is the dimension of the table. "LoglinearParameters" gives the highest order loglinear parameters (loglinear parameters can also be obtained as output of SampleStatistics, ModelStatistics or MarginalModelFit by setting ShowParameters=TRUE and the coefficients equal to log probabilities.

Value

output is of the form list(matlist,funlist) where matlist is a list of matrices and funlist is a list of function names, which can currently be "log", "exp", "identity", "xlogx" (i.e., f(x) = x log(x)), "xbarx" (i.e., f(x)=x(1-x)), "sqrt"

Author(s)

W. P. Bergsma w.p.bergsma@lse.ac.uk

References

Bergsma, W. P. (1997). Marginal models for categorical data. Tilburg, The Netherlands: Tilburg University Press. http://stats.lse.ac.uk/bergsma/pdf/bergsma_phdthesis.pdf

Bergsma, W. P., Croon, M. A., & Hagenaars, J. A. P. (2009). Marginal models for dependent, clustered, and longitudunal categorical data. Berlin: Springer.

See Also

ConstraintMatrix, DesignMatrix, MarginalMatrix

Examples

   SpecifyCoefficient("Mean",c(1,2,3))
   SpecifyCoefficient("Variance",c(1,2,3))
   SpecifyCoefficient("StandardDeviation",c(1,2,3))
   SpecifyCoefficient("GiniMeanDifference",c(1,2,3))
   SpecifyCoefficient("Entropy",5)
   SpecifyCoefficient("DiversityIndex",5)
   SpecifyCoefficient("Covariance",list(c(1,2,3),c(1,2,3)))
   SpecifyCoefficient("Correlation",list(c(1,2,3),c(1,2,3)))
   SpecifyCoefficient("KendallTau",list(3,4))
   SpecifyCoefficient("GoodmanKruskalGammma",list(3,4))
   SpecifyCoefficient("CohenKappa",3)
   SpecifyCoefficient("DifferenceInProportions",1)
   SpecifyCoefficient("LogOddsRatio",1)
   SpecifyCoefficient("LoglinearParameters",c(3,3))
   SpecifyCoefficient("Probabilities",8)
   SpecifyCoefficient("LogProbabilities",8)
   # conditional probabilities for 3x3 table, conditioning on first variable
   SpecifyCoefficient("ConditionalProbabilities",list(c(1,2),c(1),c(3,3)))

[Package cmm version 0.1 Index]