[R] R - Populate Another Variable Based on Multiple Conditions | For a Large Dataset

Kevin Wamae KWamae at kemri-wellcome.org
Sun Jul 3 22:47:17 CEST 2016


Hi Bert, my first task is to make a Kaplan Meier Plot to evaluate the risk of developing disease in the treated vs the non-treated individuals. I therefore figured it might be easier to compute dates first as any further analysis will be based on time, in this case days. I keep getting recommendations on how to tweak my analysis and keeps coming down to dates between the start of drug administration and the end of it.

Can you suggest an “easier” way to go about this.. 

Regards
-------------------------------------------------------------------------------
Kevin Wame 
 

On 7/3/16, 11:28 PM, "Bert Gunter" <bgunter.4567 at gmail.com> wrote:

I haven't followed this thread closely, but if it's not too late, I
might suggest that you stop worrying about how you want your data
frame to look and start worrying about you want to display/analyze
your data. As Jeff suggested, you and your supervisor are probably
being driven by paradigms from Excel, SPSS, or whatever that are
simply unnecessary for R. My guess would be that if you explained the
sort of analyses/plots you wish to do, you will find it can be done
fairly directly from your existing data. At the very least it would
give Jeff and other helpeRs a better idea of what you might need
rather than what you and your supervisor think you need.


Cheers,
Bert


Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Sun, Jul 3, 2016 at 1:08 PM, Kevin Wamae <KWamae at kemri-wellcome.org> wrote:
> Hi Jeff, It works on well on a dataset with 100000 rows and I figure it will work well with the “real” dataset. You’ve been of great help and I am starting to make headway.
>
> It creates a new dataframe (result), as shown below that doesn’t quite have the result as I would want it.
>
> ID      admin_period    start   end     ddays
> J1/3    1       5/11/07 8/13/07 94
> J1/3    2       8/13/07 11/12/07        91
> J1/3    3       11/12/07        2/4/08             84
> J1/3    4       2/4/08              5/5/08                  91
> J1/3    5       5/5/08               5/4/09            364
> J1/3    6       5/4/09               5/17/10    378
> J1/3    7       5/17/10 5/16/11 364
> J10/1   1       5/11/07 8/13/07 94
> J10/1   2       8/13/07 11/12/07        91
> J10/1   3       11/12/07        2/4/08              84
> J10/1   4       2/4/08                5/5/08    91
> J10/1   5       5/5/08                5/8/09    368
> J10/1   6       5/8/09               5/17/10    374
> J10/1   7       5/17/10 5/16/11 364
> J102/1  1       5/15/07 8/15/07 92
> J102/1  2       8/15/07 11/13/07        90
> J102/1  3       11/13/07        2/5/08             84
> J102/1  4       2/5/08                5/6/08    91
> J102/1  5       5/6/08                5/5/09    364
> J102/1  6       5/5/09                5/19/10   379
>
> My supervisor doesn’t want me to create a new dataset, she’s afraid I might lose some data…I cannot fight that.
>
> Like you mentioned earlier, I might be mixing up things which I think is what you alluded to earlier.
>
> After consultation with my supervisor, this is what we’ve agreed. For every individual, given the start and end date, create a new column (say, diff_days) and for every row that falls within the range of start and end_date, get the difference between the date in that row and start date and add it to the diff_days column. Below is an example of the result. As it can be seen 5/11/2007 is the start while 2/4/2008 is the end. The diff_days has been populated excluding the end date and that is because that is the start of the study in 2008 that will continue into 2009 and thus from 2/4/2008, I should compute diff_days till 2009 and so no (I hope this makes sense).
>
> ID      date    drug_admin      year    month   diff_days
> R1/3    5/11/2007       Y       2007    5       0
> R1/3    5/16/2007               2007    5       6
> R1/3    5/22/2007               2007    5       11
> R1/3    5/28/2007               2007    5       17
> R1/3    1/14/2008               2008    1       248
> R1/3    1/21/2008               2008    1       255
> R1/3    1/28/2008               2008    1       263
> R1/3    2/4/2008        Y       2008    2
>
>
> Regards
> -------------------------------------------------------------------------------
> Kevin Wame
>
>
> On 7/3/16, 10:09 PM, "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us> wrote:
>
> Typo on the second line
>
> result <- (   result0
>           %>% select( -admin_period1 )
>           %>% inner_join( result0 %>% select( ID, admin_period1, end=start )
>                        , by = c( ID="ID", admin_period ="admin_period1" )
>                         )
>           %>% mutate( ddays = end - start )
>           )
> --
> Sent from my phone. Please excuse my brevity.
>
> On July 3, 2016 11:55:14 AM PDT, Kevin Wamae <KWamae at kemri-wellcome.org> wrote:
>>Hi Jeff, “likes its Excel”, I don’t follow. Pardon me for any mix up.
>>
>>Thanks for the code.  After running it, this is the error I get.
>>
>>Error: cannot join on columns 'admin_period' x 'admin_period1': index
>>out of bounds
>>
>>Regards
>>-------------------------------------------------------------------------------
>>Kevin Wame | Ph.D. Student (IDeAL)
>>KEMRI-Wellcome Trust Collaborative Research Programme
>>Centre for Geographic Medicine Research
>>P.O. Box 230-80108, Kilifi, Kenya
>>
>>
>>On 7/3/16, 9:34 PM, "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us> wrote:
>>
>>I still get the impression from your mixing of information types that
>>you are thinking like this is Excel.
>>
>>Perhaps something like
>>
>>drug_study$admin_period  <- ave( "Y" == drug_study$drug_admin,
>>drug_study$ID, FUN=cumsum )
>>library(dplyr)
>>result0 <- (   drug_study
>>          %>% filter( 0 != admin_period )
>>          %>% group_by( ID, admin_period )
>>          %>% summarise( start = min( date ) )
>>          %>% mutate( admin_period1 = admin_period -1 )
>>          )
>>result <- (   result0
>>          %>% select( -admin_period )
>>     %>% inner_join( result0 %>% select( ID, admin_period1, end=start )
>>                     , by = c( ID="ID", admin_period ="admin_period1" )
>>                        )
>>          %>% mutate( ddays = end - start )
>>          )
>>--
>>Sent from my phone. Please excuse my brevity.
>>
>>On July 3, 2016 10:24:51 AM PDT, Kevin Wamae
>><KWamae at kemri-wellcome.org> wrote:
>>>HI Jeff, it’s been an uphill task working with the dataset and I am
>>not
>>>the first to complain. Nonetheless, data-cleaning is ongoing and since
>>>I cannot wait for that to get done, I decided to make the most of what
>>>the dataset looks like at this time. It appears the process may take a
>>>while.
>>>
>>>Thanks for the script. From the output, I noticed that “result”
>>>contains the first and last date for each of the individuals and not
>>>taking into account the variable “drug-admin”.
>>>
>>>ID        start               end
>>>J1/3      1/5/09      12/25/10
>>>R1/3      1/4/07      12/15/08
>>>R10/1     1/4/07      3/5/12
>>>
>>>My aim is to pick the date, for example in 2007, where drug-admin ==
>>>“Y” as my start and the date in the subsequent year (2008 in this
>>case)
>>>where drug-admin == “Y” as my end. Then, I should populate the
>>variable
>>>“study_id” with “start” up to the entry just above the one whose date
>>>matches “end”, as the output below shows (I hope its structure is
>>>maintained as I have copied it from R-Studio). The goal for now is to
>>>then get difference in days between “date” and “study_id” and still
>>get
>>>to keep that column for “study_id” as I might use it later.
>>>
>>>From the output, it can be seen that for this individual, the dates
>>run
>>>from 2007 to 2008. However, for some individuals, the dates run from
>>>2008-2009, 2009-2010 and so on. Therefore, I need to make the script
>>>deal with all the years as the dates range from 2001-2016
>>>
>>>ID    date    drug_admin      year    month   study_id
>>>R1/3  5/11/07 Y       2007    5       5/11/07
>>>R1/3  5/16/07         2007    5       5/11/07
>>>R1/3  5/22/07         2007    5       5/11/07
>>>R1/3  5/28/07         2007    5       5/11/07
>>>R1/3  6/5/07                  2007    6       5/11/07
>>>R1/3  6/11/07         2007    6       5/11/07
>>>R1/3  6/18/07         2007    6       5/11/07
>>>R1/3  6/25/07         2007    6       5/11/07
>>>R1/3  7/2/07                  2007    7       5/11/07
>>>R1/3  7/16/07         2007    7       5/11/07
>>>R1/3  7/29/07         2007    7       5/11/07
>>>R1/3  8/2/07                  2007    8       5/11/07
>>>R1/3  8/7/07                  2007    8       5/11/07
>>>R1/3  8/13/07         2007    8       5/11/07
>>>R1/3  9/18/07         2007    9       5/11/07
>>>R1/3  9/24/07         2007    9       5/11/07
>>>R1/3  10/6/07         2007    10      5/11/07
>>>R1/3  10/8/07         2007    10      5/11/07
>>>R1/3  10/15/07                2007    10      5/11/07
>>>R1/3  10/22/07                2007    10      5/11/07
>>>R1/3  10/29/07                2007    10      5/11/07
>>>R1/3  11/8/07         2007    11      5/11/07
>>>R1/3  11/12/07                2007    11      5/11/07
>>>R1/3  11/19/07                2007    11      5/11/07
>>>R1/3  11/29/07                2007    11      5/11/07
>>>R1/3  12/6/07         2007    12      5/11/07
>>>R1/3  12/10/07                2007    12      5/11/07
>>>R1/3  12/21/07                2007    12      5/11/07
>>>R1/3  1/7/08                  2008    1       5/11/07
>>>R1/3  1/14/08         2008    1       5/11/07
>>>R1/3  1/21/08         2008    1       5/11/07
>>>R1/3  1/28/08         2008    1       5/11/07
>>>R1/3  2/4/08          Y       2008    2
>>>
>>>
>>>Regards
>>>-------------------------------------------------------------------------------
>>>Kevin Wame
>>>
>>>###############################################################
>>>
>>>###############################################################
>>>
>>>
>>>
>>>On 7/3/16, 7:05 PM, "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us> wrote:
>>>
>>>result <- setNames( data.frame( aggregate( date~ID, data=drug_study,
>>>FUN=min ),  aggregate( date~ID, data=drug_study, FUN=max )[2] ), c(
>>>"ID", "start", "end" ) )
>>>
>>>
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