[R] unequal number of observations for longitudinal data

[Chuck Cleland]

gallon li wrote:
> i have a large longitudinal data set. The number of observations for each
> subject is not the same across the sample. The largest number of a subject
> is 5 and the smallest number is 1.
> 
> now i want to make each subject to have the same number of observations by
> filling zero, e.g., my original sample is
> 
> id x
> 001 10
> 001 30
> 001 20
> 002 10
> 002 20
> 002 40
> 002 80
> 002 70
> 003 20
> 003 40
> 004 ......
> 
> now i wish to make the data like
> 
>  id x
> 001 10
> 001 30
> 001 20
> 001 0
> 001 0
> 002 10
> 002 20
> 002 40
> 002 80
> 002 70
> 003 20
> 003 40
> 003 0
> 003 0
> 003 0
> 004 ......
> 
> so that each id has exactly 5 observations. is there a function which can
> allow me do this quickly?

  Filling in with zeros seems like a bad idea, but here is an approach
to filling in with NAs.  I will leave replacing the NAs with zeros to you.

df.long <- data.frame(id = c(1,1,1,2,2,2,2,2,3,3), x = runif(10),
                      time = c(1,2,5,1,2,3,4,5,2,4))

df.long
   id          x time
1   1 0.72888215    1
2   1 0.60893548    2
3   1 0.41347690    5
4   2 0.79388248    1
5   2 0.05810054    2
6   2 0.02451654    3
7   2 0.85464775    4
8   2 0.15970365    5
9   3 0.22856183    2
10  3 0.38291471    4

df.wide <- reshape(df, idvar = "id", v.names = "x", direction="wide")

df.wide
  id       x.1       x.2       x.5       x.3       x.4
1  1 0.6375135 0.1651258 0.3210223        NA        NA
4  2 0.9878134 0.8909020 0.9853269 0.7747615 0.3834130
9  3        NA 0.3586109        NA        NA 0.8310539

df.long2 <- reshape(df.wide, direction="long")

df.long2
    id time         x
1.1  1    1 0.6375135
2.1  2    1 0.9878134
3.1  3    1        NA
1.2  1    2 0.1651258
2.2  2    2 0.8909020
3.2  3    2 0.3586109
1.5  1    5 0.3210223
2.5  2    5 0.9853269
3.5  3    5        NA
1.3  1    3        NA
2.3  2    3 0.7747615
3.3  3    3        NA
1.4  1    4        NA
2.4  2    4 0.3834130
3.4  3    4 0.8310539

  This assumes that your data in the "long" format has a time variable.
 See the help page for reshape() for more details.

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-- 
Chuck Cleland, Ph.D.
NDRI, Inc.
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