Replication of observations in the data can be specified with R (or the specified character).
Replication character = R or one of A-Z # $ % &
Upper and lower case characters are the same. Other characters may be available. If you need to use one, please try it. More than one character is also allowed: Replication character = R#
There is no character between this and the number of replications (integer R6 or decimal R3.5).
Example 1: player 1 won 3 times against player 2, and lost 4 times:
Replication character = R ; this is the default value
R3 1 2 1 ; R3 "replicate this observation 3 times"
R4 1 2 0
Example 2: Roger won 3 times against Alfred, and lost 4 times:
Facets = 2 ; 2 facets in the data
Entered = 1, 1 ; both facets in the data are facet 1 in the labels
Models = ?,-?,D ; any element in facet 1 - any facet in element 1 -> dichotomous observation
Labels=
1, players
1 = Roger
2 = Alfred
...
*
Delements = LN ; element identifiers in the data are labels
Replication = # ; the replication character is # and we use R for the first letter of some element labels in the data.
Data=
#3 Roger Alfred 1
#4 Roger Alfred 0
Example 3: For one element, the data looks like 2.7, 5.6, 8.9, ranging from 0 to 10. but other items are integers.
In Facets, every advancing score must mean one higher level of the latent variable. In your data, 0,1,2,3,4,5,6,7,8,9,10 are 11 levels of performance. What does 2.7 mean? From the viewpoint of Facets it means:
an observation of 2 weighted 0.3 (= 0.6) + an observation of 3 weighted 0.7 (= 2.1 so that 0.6+2.1=2.7)
so, if the original Facets observation was:
facet1, facet2, facet3, 2.7
then the Facets data is:
Data=
R0.3, facet1, facet2, facet3, 2
R0.7, facet1, facet2, facet3, 3
