Description Usage Arguments Details Value Author(s) References See Also Examples
Gives the generalized exp-log specification for various coefficients
1 |
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. |
data |
data set. Necessary for MEL estimation |
rep |
number of repetitions of the coefficient |
Currently the following coefficients are implemented:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | SpecifyCoefficient("Mean",arg = scores)
SpecifyCoefficient("Variance", arg = scores)
SpecifyCoefficient("StandardDeviation", arg = scores)
SpecifyCoefficient("GiniMeanDifference", arg = scores)
SpecifyCoefficient("Entropy", arg = k)
SpecifyCoefficient("DiversityIndex", arg = k)
SpecifyCoefficient("Covariance",arg = list(xscores,yscores))
SpecifyCoefficient("Correlation",arg = list(xscores,yscores))
SpecifyCoefficient("KendallTau",arg = list(r,c))
SpecifyCoefficient("GoodmanKruskalGammma",arg = list(r,c))
SpecifyCoefficient("CohenKappa",r)
SpecifyCoefficient("CronbachAlpha",arg = list(items,item.scores), data = X)
SpecifyCoefficient("Hij")
SpecifyCoefficient("DifferenceInProportions",arg = m)
SpecifyCoefficient("LogOddsRatio")
SpecifyCoefficient("LoglinearParameters",arg = dim)
SpecifyCoefficient("Probabilities",arg = dim)
SpecifyCoefficient("LogProbabilities",arg = dim)
SpecifyCoefficient("ConditionalProbabilities",arg = list(var,condvar,dim))
SpecifyCoefficient("AllMokkenHj", arg = list(items,item.scores), data = X)
SpecifyCoefficient("MokkenH", arg = list(items,item.scores), data = X)
SpecifyCoefficient("OrdinalLocation-A", arg = arg)
SpecifyCoefficient("OrdinalLocation-L", arg = arg)
SpecifyCoefficient("OrdinalDispersion-A", arg = arg)
SpecifyCoefficient("OrdinalDispersion-L", arg = arg)
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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; items
are the columns
in the data matrix that should be used for compuing the statistic; item.scores
is the number of item scores (e.g., 2 for dichotomous items,
or 5 for Likert items); X
is the NxJ data matrix. "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.
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"
W. P. Bergsma w.p.bergsma@lse.ac.uk
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.
ConstraintMatrix
, DesignMatrix
, MarginalMatrix
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | SpecifyCoefficient("Mean",arg = c(1,2,3))
SpecifyCoefficient("Variance",arg = c(1,2,3))
SpecifyCoefficient("StandardDeviation",arg = c(1,2,3))
SpecifyCoefficient("GiniMeanDifference",arg = c(1,2,3))
SpecifyCoefficient("Entropy",arg = 5)
SpecifyCoefficient("DiversityIndex",arg = 5)
SpecifyCoefficient("Covariance",arg = list(c(1,2,3),c(1,2,3)))
SpecifyCoefficient("Correlation",arg = list(c(1,2,3),c(1,2,3)))
SpecifyCoefficient("KendallTau",arg = list(3,4))
SpecifyCoefficient("GoodmanKruskalGammma",arg = list(3,4))
SpecifyCoefficient("CohenKappa",arg = 3)
SpecifyCoefficient("DifferenceInProportions",arg = 1)
SpecifyCoefficient("LogOddsRatio",arg = 1)
SpecifyCoefficient("LoglinearParameters",arg = c(3,3))
SpecifyCoefficient("Probabilities",arg = 8)
SpecifyCoefficient("LogProbabilities",arg = 8)
# conditional probabilities for 3x3 table, conditioning on first variable
SpecifyCoefficient("ConditionalProbabilities",arg = list(c(1,2),c(1),c(3,3)))
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