Some pointers (not tested, may contain blunders...)
(a) you likely need some sort of split-operate-unsplit construct, by country.
E.g.,
myfun <- function(d) {....operate on data frame with only one country....}
ll <- split(data, data$country)
ll.new <- lapply(ll, myfun)
data.new <- unsplit(ll.new, data$country)
(There might be a tidyverse idiom for this too)
(b) your X1_pre5count looks like it is the same as cumsum(1-X1)*X1 (within
country)
(c) if you count in the opposite direction, tt <- rev(cumsum(rev(1-X1))) you
get number of years until agreement. Then X1_pre4 should be as.integer(tt <=4
& tt > 0)
-pd
> On 27 Jul 2019, at 09:13 , Faradj Koliev <[email protected]> wrote:
>
> Re-post, now in *plain text*.
>
>
>
> Dear R-users,
>
> I’ve a rather complicated task to do and need all the help I can get.
>
> I have data indicating whether a country has signed an agreement or not
> (1=yes and 0=otherwise). I want to simply create variable that would capture
> the years before the agreement is signed. The aim is to see whether pre or
> post agreement period has any impact on my dependent variables.
>
> More preciesly, I want to create the following variables:
> (i) a variable that is =1 in the 4 years pre/before the agreement, 0
> otherwise;
> (ii) a variable that is =1 5 years pre the agreement and
> (iii) a variable that would count the 4 and 5 years pre the agreement
> (1,2,3,4..).
>
> Please see the sample data below. I have manually added the variables I would
> like to generate in R, labelled as “X1_pre4” ( 4 years before the agreement
> X1), “X2_pre4”, “X1_pret5” ( 5 years before the agreement X5), and
> “X1pre5_count” (which basically count the years, 1,2,3, etc). The X1 and X2
> is the agreement that countries have either signed (1) or not (0). Note
> though that I want the variable to capture all the years up to 4 and 5. If
> it’s only 2 years, it should still be ==1 (please see the example below).
>
> To illustrate the logic: the country A has signed the agreement X1 in 1972 in
> the sample data, then, the (i) and (ii) variables as above should be =1 for
> the years 1970, 1971, and =0 from 1972 until the end of the study period.
>
> The country A has signed the agreement X2 in 1975, then, the (i) variable
> should be =1 from 1971 to 1974 (post 4 years) and (ii) should be =1 for the
> 1970-1974 period (post 5 years before the agreement is signed).
>
> Later, I would also like to create post_4 and post_5 variables, but I think
> I’ll be able to figure it out once I know how to generate the pre/before
> variables.
>
> All suggestions are much appreciated!
>
>
>
> data<-structure(list(country = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
> 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("A", "B", "C"), class = "factor"),
> year = c(1970L, 1971L, 1972L, 1973L, 1974L, 1975L, 1976L,
> 1977L, 1978L, 1979L, 1980L, 1981L, 1982L, 1983L, 1984L, 1985L,
> 1986L, 1987L, 1988L, 1970L, 1971L, 1972L, 1973L, 1974L, 1975L,
> 1976L, 1977L, 1978L, 1979L, 1980L, 1981L, 1982L, 1983L, 1984L,
> 1985L, 1986L, 1987L, 1988L, 1970L, 1971L, 1972L, 1973L, 1974L,
> 1975L, 1976L, 1977L, 1978L, 1979L, 1980L, 1981L, 1982L, 1983L,
> 1984L, 1985L, 1986L, 1987L, 1988L, 1989L, 1990L, 1991L),
> X1 = c(0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L), X2 = c(0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L), X1_pre4 = c(1L, 1L, 0L, 0L, 0L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> 0L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L,
> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), X2_pre4 = c(0L, 1L, 1L,
> 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
> 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), X1_pre5 = c(1L,
> 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L),
> X1_pre5_count = c(1L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 3L,
> 4L, 5L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 3L, 4L, 5L, 0L, 0L, 0L,
> 0L, 0L, 0L, 0L, 0L)), class = "data.frame", row.names = c(NA,
> -60L))
>
>> On 26 Jul 2019, at 21:58, Bert Gunter <[email protected]> wrote:
>>
>> Because you posted in HTML, your example got mangled and resulted in an
>> error. Re-post in *plain text* please (making sure that you cut and paste
>> correctly)
>>
>> 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 Fri, Jul 26, 2019 at 12:25 PM Faradj Koliev <[email protected]> wrote:
>> Dear R-users,
>>
>> I’ve a rather complicated task to do and need all the help I can get.
>>
>> I have data indicating whether a country has signed an agreement or not
>> (1=yes and 0=otherwise). I want to simply create variable that would capture
>> the years before the agreement is signed. The aim is to see whether pre or
>> post agreement period has any impact on my dependent variables.
>>
>> More preciesly, I want to create the following variables:
>> (i) a variable that is =1 in the 4 years pre/before the agreement, 0
>> otherwise;
>> (ii) a variable that is =1 5 years pre the agreement and
>> (iii) a variable that would count the 4 and 5 years pre the agreement
>> (1,2,3,4..).
>>
>> Please see the sample data below. I have manually added the variables I
>> would like to generate in R, labelled as “X1_pre4” ( 4 years before the
>> agreement X1), “X2_pre4”, “X1_pret5” ( 5 years before the agreement X5), and
>> “X1pre5_count” (which basically count the years, 1,2,3, etc). The X1 and X2
>> is the agreement that countries have either signed (1) or not (0). Note
>> though that I want the variable to capture all the years up to 4 and 5. If
>> it’s only 2 years, it should still be ==1 (please see the example below).
>>
>> To illustrate the logic: the country A has signed the agreement X1 in 1972
>> in the sample data, then, the (i) and (ii) variables as above should be =1
>> for the years 1970, 1971, and =0 from 1972 until the end of the study
>> period.
>>
>> The country A has signed the agreement X2 in 1975, then, the (i) variable
>> should be =1 from 1971 to 1974 (post 4 years) and (ii) should be =1 for the
>> 1970-1974 period (post 5 years before the agreement is signed).
>>
>> Later, I would also like to create post_4 and post_5 variables, but I think
>> I’ll be able to figure it out once I know how to generate the pre/before
>> variables.
>>
>> All suggestions are much appreciated!
>>
>>
>>
>> data<–structure(list(country = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
>> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>> 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
>> 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("A", "B", "C"), class = "factor"),
>> year = c(1970L, 1971L, 1972L, 1973L, 1974L, 1975L, 1976L,
>> 1977L, 1978L, 1979L, 1980L, 1981L, 1982L, 1983L, 1984L, 1985L,
>> 1986L, 1987L, 1988L, 1970L, 1971L, 1972L, 1973L, 1974L, 1975L,
>> 1976L, 1977L, 1978L, 1979L, 1980L, 1981L, 1982L, 1983L, 1984L,
>> 1985L, 1986L, 1987L, 1988L, 1970L, 1971L, 1972L, 1973L, 1974L,
>> 1975L, 1976L, 1977L, 1978L, 1979L, 1980L, 1981L, 1982L, 1983L,
>> 1984L, 1985L, 1986L, 1987L, 1988L, 1989L, 1990L, 1991L),
>> X1 = c(0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
>> 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
>> 1L, 1L), X2 = c(0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L,
>> 1L, 1L, 1L, 1L), X1_pre4 = c(1L, 1L, 0L, 0L, 0L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
>> 0L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), X2_pre4 = c(0L, 1L, 1L,
>> 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
>> 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
>> 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), X1_pre5 = c(1L,
>> 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
>> 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L),
>> X1_pre5_count = c(1L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 3L,
>> 4L, 5L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 3L, 4L, 5L, 0L, 0L, 0L,
>> 0L, 0L, 0L, 0L, 0L)), class = "data.frame", row.names = c(NA,
>> -60L))
>>
>>
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> [email protected] mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> [email protected] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: [email protected] Priv: [email protected]
______________________________________________
[email protected] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
