time-series data and time-invariant missing values

x2

Dear list,

I have some problems with time-series data and missing values of time-invariant informations like sex or the birth-date.

Assume a data (d) structure like

id ? ? ?birth ? ? ? ? ? sex ? ? year of observation
1 ? ? ? NA ? ? ? ? ? ? ?NA ? ? ?2006
1 ? ? ? 1976-01-01 ? ? ?male ? ?2007
1 ? ? ? NA ? ? ? ? ? ? ?NA ? ? ?2008

I am looking for a way to replace the missing values.

Right know my answer to this problem slows down R



for (i in 1:length(d[,1])){ # for all observations

? ? ? ?if (is.na(d$birth)[i])==F){ # Check if birth of observation(i) is missing
? ? ? ? ? ?d$birth_2[i] <- as.Date(birth[i],"%d.%m.%Y")
? ? ? ?}else{
? ? ? ? ? ?d$birth2[i] ?<- d$birth[id[i]==d$id & is.na(d$birth)==F],"%d.%m.%Y")[1] # if birth of observation (i) is missing, take a observation of another year
? ? ? ?}
? ?}
}

Result:


id ? ? ?birth ? ? ? ? ? sex ? ? year of observation ? ? birth2
1 ? ? ? NA ? ? ? ? ? ? ?NA ? ? ?2006 ? ? ? ? ? ? ? ? ? ?1976-01-01
1 ? ? ? 01.01.1976 ? ? ?male ? ?2007 ? ? ? ? ? ? ? ? ? ?1976-01-01
1 ? ? ? NA ? ? ? ? ? ? ?NA ? ? ?2008 ? ? ? ? ? ? ? ? ? ?1976-01-01

unfortunately the data consists of over 20000 observations a year.

Does anybody know a better way?

Thanks

Mit freundlichen Gr??en

Andreas Kunzler