R - Calculate Time Elapsed Since Last Events with Multiple Event Types and IDs

You could subset your Dates for all with a specific event encoding, e.g.:

date.2 = DATAFRAME[which(DATAFRAME[,2]==2),1]

and then just do

DATAFRAME[which(DATAFRAME[,2]==2),5] = as.numeric(diff.Date(date.2))

and so on. Possibly this is even easier to do, but this was the first thing coming to my mind. DATAFRAME is just the name of your dataframe here.

edit: If I see it correctly you want NAs wherever ID and event column are different to each other? Then you could just go on with: DATAFRAME[which(DATAFRAME[,2] != DATAFRAME[,3]),c(4,5)] = NA or something like that

The following uses the Chron Library to calculate difference in the dates

library(chron)

df$date <- chron(as.character(df$date),format=c(date="y-m-d"))

for(j in unique(df$id)){
  DaysSince1 <-NA
  DaysSince2 <-NA
  RowsWithID <- grep(j,df$id)

  for(i in RowsWithID){
    df$days_since_event_1[i] <- df$date[i]-df$date[i-DaysSince1]
    df$days_since_event_2[i] <- df$date[i]-df$date[i-DaysSince2]

    if(df$event[i]==1){DaysSince1<-1}
      else{DaysSince1<-DaysSince1+1}

    if(df$event[i]==2){DaysSince2<-1}
      else{DaysSince2<-DaysSince2+1}
  }
}

This code gives the following results

> df
       date event id days_since_event_1 days_since_event_2
1  00-07-06     2  1                 NA                 NA
2  00-07-07     1  1                 NA                  1
3  00-07-09     0  1                  2                  3
4  00-07-10     0  1                  3                  4
5  00-07-15     2  1                  8                  9
6  00-07-16     1  1                  9                  1
7  00-07-20     0  1                  4                  5
8  00-07-21     1  1                  5                  6
9  00-07-06     1  2                 NA                 NA
10 00-07-07     2  2                  1                 NA
11 00-07-15     0  2                  9                  8
12 00-07-16     0  2                 10                  9
13 00-07-17     2  2                 11                 10
14 00-07-18     1  2                 12                  1

To address you comment, you can do the following in Base R to get the number of observations rather than days. No Libraries needed.

for(j in unique(df$id)){
  ObsSince1 <-NA
  ObsSince2 <-NA
  RowsWithID <- grep(j,df$id)

  for(i in RowsWithID){
    df$Obs_since_event_1[i] <- ObsSince1
    df$Obs_since_event_2[i] <- ObsSince2

    if(df$event[i]==1){ObsSince1<-1}
    else{ObsSince1<-ObsSince1+1}

    if(df$event[i]==2){ObsSince2<-1}
    else{ObsSince2<-ObsSince2+1}
  }
}

You should get the following output

> df
         date event id Obs_since_event_1 Obs_since_event_2
1  2000-07-06     2  1                NA                NA
2  2000-07-07     1  1                NA                 1
3  2000-07-09     0  1                 1                 2
4  2000-07-10     0  1                 2                 3
5  2000-07-15     2  1                 3                 4
6  2000-07-16     1  1                 4                 1
7  2000-07-20     0  1                 1                 2
8  2000-07-21     1  1                 2                 3
9  2000-07-06     1  2                NA                NA
10 2000-07-07     2  2                 1                NA
11 2000-07-15     0  2                 2                 1
12 2000-07-16     0  2                 3                 2
13 2000-07-17     2  2                 4                 3
14 2000-07-18     1  2                 5                 1