[R] Operating on count lists of non-equal lengths

[Kari Manninen]

This is my first post to R-help and I look forward receiving some  
advice for a novice like me...

I’ve got a simple repeated (4 periods so far) 10-question survey data  
that is very easy to work on Excel. However, I’d like to move the  
compilation to R but I’m having some trouble operating on count list  
data in a neat way.

The data C
> str(C)
'data.frame':	551 obs. of  13 variables:
  $ TIME   : int  1 1 1 1 1 1 1 1 1 1 ...
  $ Sector : Factor w/ 6 levels "D","F","G","H",..: 1 1 1 1 1 1 1 1 1 1 ...
  $ COMP   : Factor w/ 196 levels " (_____ __ _____) ",..: 73 133 128  
109 153 147 56 26 142 34 ...
  $ Q1     : int  0 0 1 1 0 -1 -1 1 1 -1 ...
  $ Q2     : int  0 0 0 -1 0 -1 0 0 1 -1 ...
  $ Q3     : int  0 0 0 1 0 -1 -1 1 1 -1 ...
  $ Q4     : int  -1 0 0 0 0 -1 0 -1 0 -1 ...
  $ Q5     : int  0 0 0 -1 0 -1 0 -1 0 0 ...
  $ Q6     : int  0 0 0 1 0 -1 0 -1 0 0 ...
  $ Q7     : int  0 1 1 0 0 0 1 0 1 1 ...
  $ Q8     : int  0 0 0 0 0 -1 0 0 1 0 ...
  $ Q9     : int  0 1 0 0 0 -1 0 -1 1 -1 ...
  $ Q10    : int  0 0 0 0 -1 -1 0 -1 0 0 ...

> summary(C)
       TIME       Sector  COMP        Q1               Q2
  Min.   :1.000   D:130   A:  4   Min.   :-1.000   Min.   :-1.0000
  1st Qu.:2.000   F:126   B:  4   1st Qu.: 0.000   1st Qu.: 0.0000
  Median :3.000   G:158   C:  4   Median : 1.000   Median : 0.0000
  Mean   :2.684   H: 26   D:  4   Mean   : 0.446   Mean   : 0.2178
  3rd Qu.:4.000   I: 20   E:  4   3rd Qu.: 1.000   3rd Qu.: 1.0000
  Max.   :4.000   J: 91   F:  4   Max.   : 1.000   Max.   : 1.0000
                    (Other):527   NA's   :60.000   NA's   :69.0000



The aim is to produce balance scores between positive and negative  
answers’ shares in the data. First counts of -1, 0 and 1 (negative,  
neutral, positive) and missing NA (it would be som much simple without  
the missing values) for each question Q1-Q10 for each period (TIME) in  
6 Sectors:

b<-apply(C[,4:13], 2, function (x) tapply(x,C[,1:2], count))

I know that b is a list of data.frames dim(4x6) for each question,  
where each ‘cell’ is a count list.

For example, for Question 1, Time period 2, Sector 1:
> str(b$Q1[2,1])
List of 1
  $ :’data.frame’:  4 obs. of 2 variables:
    ..$ x    : int [1:4]  -1 0 1  NA
    ..$ freq : int [1:4]  3  9 12 2

Now I would like to group questions (C[, 4:6],   C[, 7],  C[8:9],   
C[10:11]  and  C[, 12:13])  and sum counts (-1, 0, 1) for these groups  
and present them in percentage terms. I don’t know how to this  
efficiently for the whole data. I would not like to go through each  
cell separately


Then I’d give each group a balance score based on something like:

Score = 100 + 100*[ pos% - neg%] for each group by TIME, Sector, while  
excluding the missing observations.

### This is not working
Score <-  100 + 100*[sum(count( =="1")/sum(count(list( "-1", "0","1")   
- sum(count( =="-1")/sum(count(list( "-1", "0","1")]  for each 5  
groups defined above and by TIME, Sector

I would greatly appreciate your help on this.

Regards,
- Kari Manninen