On 2011-01-20 02:05, Taras Zakharko wrote:
Hello Den,
your problem is not as it may seem so Ivan's suggestion is only a partial
answer. I see that each patient can have
more then one diagnosis and I take that you want to isolate patients based on
particular conditions.
Thus, simply looking for "ah" or "idh" as Ivan suggests will yield patients
which can have either of those but not
necessarily patients that have both.
Instead, what one must do is apply the condition to the whole set of diagnosis
associated with each patient.
I think that its done best with the aggregate function. This function splits
the data according to some
factor (in our case it will be the patient id) and performs a routine on each
subset (in our case it will be
a condition test):
ids<- aggregate(diagnosis ~ id, df, function(x) "ah" %in% x&& "ihd" %in% x)
ids<- aggregate(diagnosis ~ id, df, function(x) "ah" %in% x&& !"ihd" %in% x)
ids<- aggregate(diagnosis ~ id, df, function(x) ! "ah" %in% x&& "ihd" %in% x)
Now, ids will contain a data frame like:
id diagnosis
1 TRUE
2 FALSE
3 FALSE
...
which shows which patients have the set of diagnoses you asked for. You can
then apply these
patients to the original data by something like:
subset(df, id %in% subset(ids, diagnosis == TRUE)$id)
this will extract only patients from the 'ids' data frame for which the
diagnosis applies and then extract the associated
diagnosis sets from the original 'df' data frame.
Hope it helps,
Taras
Here's a tidy version using the plyr package:
require(plyr)
df1 <- ddply(df, .(id), summarize,
has.both = ("ah" %in% diagnosis) & ("ihd" %in% diagnosis),
has.only.ah = ("ah" %in% diagnosis) & !("ihd" %in% diagnosis),
has.only.ihd = !("ah" %in% diagnosis) & ("ihd" %in% diagnosis)
)
Further processing on the columns of df1 is straightforward.
Peter Ehlers
On Jan 20, 2011, at 9:53 , Den wrote:
Dear R people
Could you please help.
Basically, there are two variables in my data set. Each patient ('id')
may have one or more diseases ('diagnosis'). It looks like
id diagnosis
1 ah
2 ah
2 ihd
2 im
3 ah
3 stroke
4 ah
4 ihd
4 angina
5 ihd
..............
Q: How to make three data sets:
1. Patients with ah and ihd
2. Patients with ah but no ihd
3. Patients with ihd but no ah?
If you have any ideas could just guide what should I look for. Is a
subset or aggregate, or loops, or something else??? I am a bit lost. (F1
F1 F1 !!!:)
Thank you
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