I am trying to create a 2x2xk contingency table.  The variables are GDP and
an income inequality statistic with year being the k levels.  I want to
eventually run a loglinear model with the data.  Currently the data is
organized by either year or country.  example

Country    Year   log(GDP)    sqrt(INEQ)
1              1980   24             5.3
1              1981   25             5.45
1              1982   24.5          5.4
1              1983   25            5.3
1              1984   25.5          5.5

or

Country    Year    log(GDP)   sqrt(INEQ)
1              1980   25             5.5
2              1980   22             6.5
3              1980   23.8          6.8
4              1980   26.7          5.2
5              1980   24             6
6              1980   26             5.5


I want to reorganize the data so it's like:

Year    GDP>median(for the ith year)     INEQ>sqrt(40)      count
1980    1
1                          3
1980    1
0                          6
1980    0
1                          8
1980    0
0                          9
1981    1
1                          2
1981    1
0                          7
1981    0
1                          7
1981    0
0                          9



So far, I've been using the "sort()" function to order the data.  Then,

f63<-sort(data1963$Gdp)
data1963$INEQ[data1963$Gdp>median(f63)]
data1963$INEQ[data1963$Gdp<median(f63)]

in order to separate the data.  But, there's missing data and the NA are
still being counted when I use the function "length()".  I'm not sure how to
get the data in the way I need it without simply doing it by hand.  I might
have to do that, but I would really rather not.


Any advice would be much appreciated,

Chris

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