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Message-ID: <33A1BBE99423A247A16CC54ECE08D865C8B49C@c1bzaek>
Date: 2009-04-06T11:13:58Z
From: Kunzler, Andreas
Subject: time-series data and time-invariant missing values

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
____________________________
Bundeszahn?rztekammer (BZ?K)
Chausseestra?e 13
10115 Berlin

Tel.: 030 40005-113
Fax:  030 40005-119

E-Mail: a.kunzler at bzaek.de