[R] R - Populate Another Variable Based on Multiple Conditions | For a Large Dataset
Kevin Wamae
KWamae at kemri-wellcome.org
Mon Jul 4 08:48:07 CEST 2016
Hi Jeff, thanks and I will explore your suggestions too..
Regards
-------------------------------------------------------------------------------
Kevin Wame
On 7/4/16, 12:43 AM, "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us> wrote:
There are a great many hits when I search on the keywords "kaplan meier plot R"... so my first reaction is that you should be referring to some of the existing packages for doing this type of analysis. I do not do this type of analysis normally, so am probably not your best helper... perhaps someone else will chime in if you show that you have read some existing KM examples.
My second reaction is that if you want to avoid losing records you should also avoid adding records. Your example extends from the first matching date to and including the next matching date, which conflicts with analysis of successive treatment periods. You may have a good reason for doing this, but in my experience this is usually a mistake.
Finally, I think you should more closely study the use of the ave function that I already used if you want to work with the data in its original form. It should not be too difficult to generate your diff_days column using ave if you have the admin_period column that I showed you how to make.
--
Sent from my phone. Please excuse my brevity.
On July 3, 2016 1:47:17 PM PDT, Kevin Wamae <KWamae at kemri-wellcome.org> wrote:
>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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>>
>>
>>
>>
>>
>______________________________________________________________________
>>
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