TraMineR (version 1.6-2)

seqdiff: Decompose the difference between groups of sequences

Description

Decompose the difference between groups of sequences

Usage

seqdiff(seqdata, group, cmprange = c(0, 1),
        seqdist_arg=list(method="LCS",norm=TRUE))

Arguments

seqdata

a state sequence object created with the seqdef function.

group

The group variable

cmprange

The range used to compare subsequences

seqdist_arg

argument passed directly to seqdist as a list

Value

• A seqdiff object, with the following items:
• stat
  A data.frame with three statistics (PseudoF, PseudoR2 and PseudoT) for each timestamp of the sequence, see dissassoc
• variance
  A data.frame with, at each time stamp, the discrepancy within each group defined by the group variable and for the whole population.

encoding

latin1

Details

Analyses at each timestamp the sequence discrepancy within a sliding time window (of range defined by cmprange) that is explained by the group variable. The method computes a distance matrix, using seqdist at each timestamp and then derives the explained discrepancy with dissassoc. There are print and plot methods for the result returned.

References

Studer, M., G. Ritschard, A. Gabadinho, and N. S. M�ller (2009) Discrepancy analysis of complex objects using dissimilarities. In H. Briand, F. Guillet, G. Ritschard, and D. A. Zighed (Eds.), Advances in Knowledge Discovery and Management, Studies in Computational Intelligence. Berlin: Springer. Studer, M., G. Ritschard, A. Gabadinho and N. S. M�ller (2009) Analyse de dissimilarit�s par arbre d'induction. In EGC 2009, Revue des Nouvelles Technologies de l'Information, Vol. E-15, pp. 7-18.

See Also

dissassoc to analyse the association with the whole sequence

Examples

## Defining a state sequence object
data(mvad)
mvad.seq <- seqdef(mvad[, 17:86])

## Building dissimilarities
mvad.diff <- seqdiff(mvad.seq, group=mvad$gcse5eq)
print(mvad.diff)
plot(mvad.diff)
plot(mvad.diff, stat="Variance")