This really depends on what you want to do. I will try to give some example below.
1. Coding the missing values But you definitely do not need to delete observations BEFORE loading them into R. By default any empty cells or "NA" is treated as NA, when you load the data using read.delim(). You can adjust the na.string option in read.delim() to change this default behaviour. Ensure the coding is ok before you proceed. You can check using is.na() for example to see if R will treat them as missing values. 2. Perform calculations with missing values as defined by na.action() X <- c(1,2,3,NA, 4) sum(X, na.rm=T) # gives you 10 See ?na.action for more interestin detail. Some algorithms are capable of automatically handle missing values. In the classification context, rpart can handle missing values. 3. Missing value imputation There are many imputation methods (eg. EMV, e1071, hmisc, norm, permax, pamr libraries). The type of imputation depends on your application, area of research and type of missingness (if at missing completely at random, missing/observed at random, informative missing). Good luck. -----Original Message----- From: Tor A Strand [mailto:[EMAIL PROTECTED] Sent: Wednesday, July 16, 2003 6:12 PM To: R-list Subject: [R] how to handle missing values This group impresses me, so far I have been helped with all my questions within 24 hours. Thanks. Therefore another one. I am used to programs (such as STATA) where observations with missing values that are included in a model are simply ignored in the analysis. So far I have not been able to figure out how to deal with missing values in R and have solved the problem by deleting observations with missing values before loading them into R. Can anyone give me a hint on how to do this in a simpler way? Sincerely, Dr. Tor A Strand Centre for International Health Haukeland Hospital University of Bergen 5021 Bergen Norway Phone: (country prefix 47) Residence:56 51 10 88, office: 55 97 49 80, fax: 55 97 49 79, cellular: 90 97 10 86 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
