StateExpand: StateExpand
In PeFox/DySeq: Functions for Dyadic Sequence Analyses

Description Usage Arguments Details Value References Examples

Transforms dyadic binary data into state-expand-sequences (combines two corresponding sequences into one for every row of a dataframe)

1	StateExpand(x, pos1, pos2, replace.na = FALSE)

`x`	Dataframe or matix containing the sequences that should be combined
`pos1`	a vector that indicates all columns of the first sequence
`pos2`	a vector that indicates all columns of the second sequence
`replace.na`	a numeric that is used for replacement. If FALSE: no replacement will take place! 0 is handled as zero in this case not als FALSE!

Takes a dataframe or matrix with dyadic binary data in wide data format, that is:

one observation unit (for example one couple) is represented by one row
every observation unit has two sequences with the same length
entrys must be corresponding to each other (for example they represent same time intervalls)
every sequence contains only zeros and/or ones (for example behavior is shown or not)

and transforms it into state-expand-sequences:

one sequence per observation unit that contains the same information as before
every entry represents the combination of the corresponding previous entrys
0 represents two former zeros,
1 represents a one in the first sequence and a zeros in the second
2 represents a zero in the first sequence and a one in the second
3 represents a one in both former sequeces

why/how to use:

Most packages are only suited for univariat sequence analysis.
This function transforms dyadic dequences into univariate sequences.
state-expand-sequences are needed for some of the other functions of this package.

returns a matrix with the combined sequences.

Bakeman, R., & Gottman, J. M. (1997) <DOI: 10.1017/cbo9780511527685 >
Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006) <DOI: 10.1177/1098214007300894>

 # Example 1
 data(CouplesCope) # Load sample data
 CouplesCope[1:5,] # inspect first five cases

 my.expand<-StateExpand(CouplesCope, 2:49, 50:97)
 my.expand[1:5,] # inspect first five cases of the combined sequences



 # Example 2: with NA replacement
 data(CouplesCope)
 
 # copy part of the example data
 # excluding code and EDCm for simplification
 na.CouplesCope<-CouplesCope[,2:97] 
 
   
 # fill it with 10% NA's as an example:
 na.CouplesCope[matrix(sample(c(TRUE, rep(FALSE,9)),64*96, TRUE), 64, 96)]<-NA 
 na.CouplesCope[1:5,] # inspect the first 5 cases
 
 # demonstrate na.replace: combine states and fill NA's with zeros!
 my.expand<-StateExpand(na.CouplesCope, 1:48, 49:96, replace.na=0) 
 my.expand[1:5,] # inspect the first 5 cases



## Not run: 
 # Example 3: Use StateExpand for further analyis 
 #            or plotting using the Package TraMineR
              
 # install.packages("TraMineR") # install "TraMineR" for graphical analysis
 library(TraMineR) #load TraMineR

 my.expand<-StateExpand(CouplesCope, 2:49, 50:97) # create combined sequences

 # create labels for plot
 couple.labels <-c("no reaction", "stress only", "coping only", "both reactions")  
 
 # create a sequence object (the way TraMineR represents sequences)
 couple.seq <- seqdef(my.expand, labels = couple.labels) 
 seqdplot(couple.seq)

 detach(TraMineR) # unloading TraMineR

## End(Not run)