# Example using the function scores():

source("http://www2.jura.uni-hamburg.de/instkrim/kriminologie/Mitarbeiter/Enzmann/Software/scores.r")

items = data.frame(v1 = c( 1, 1, 1, 1, 1, 1,NA),
                   v2 = c( 2, 2, 2,NA, 2,NA,NA),
                   v3 = c( 3, 3, 3, 3,NA,NA,NA),
                   v4 = c( 4, 4,NA, 4,NA,NA,NA),
                   v5 = c( 5,NA,NA,NA,NA,NA,NA))

# Create test = mean scores of v1,v3,v4, and v5:
# Because fcn='mean' is default you need not specify fcn='mean'. Because 1 is
# default of minvalid you will obtain valid scores for all cases with at least
# 1 valid value:
attach(items)
cbind(items,test=scores(v1,v3,v4,v5))
detach(items)

# Same as above but specifying the data frame:
cbind(items,test=scores(items[,-2]))

# Same as above but specify minvalid(3) so that scores are valid only if least
# three values of the four variables are valid (or equivalently: at most 4-3=1
# value may be missing):
cbind(items,test=scores(items[,-2],minvalid=3))

# Same as above but requesting minima instead of mean scores:
cbind(items,test=scores(items[,-2],minvalid=3,fcn='min'))

# Same as above but requesting maxima instead of minima:
cbind(items,test=scores(items[,-2],minvalid=3,fcn='max'))

# Same as above but requesting sum scores instead of maxima:
cbind(items,test=scores(items[,-2],minvalid=3,fcn='sum'))

# Same as above but requesting standard deviations instead of sum scores:
cbind(items,test=scores(items[,-2],minvalid=3,fcn='sd'))

# Same as above but requesting mean scores centered at the overall mean:
cbind(items,test=scores(items[,-2],minvalid=3,score='c'))

# Same as above but requesting mean scores transformed to z-scores:
cbind(items,test=scores(items[,-2],minvalid=3,score='z'))

# Same as above but requesting mean scores transformed to POMP scores assuming
# Likert scale items with anchors ranging from 1 (minimum possible value) to 5
# (maximum possible value):
cbind(items,test=scores(items[,-2],minvalid=3,score='p',minval=1,maxval=5))