HI I am trying to analyse data which is left-censored (i.e. has values below the detection limit). I have been using the NADA package of R to derive summary statistics and do some regression. I am now trying to carry out regression on paired data where both my X and Y have left-censored data within them.
I have tried various commands in R: rega = cenreg(Cen(conc, cens_ind) ~ Gp_ident)) with all X and Y data stacked and using a group identifier to look at the differences this doesn't take account of the paired data though. I have also tried splitting the data and regessing one on the other rega = cenreg(Cen(conc1, censind1) ~ Cen(conc2,censind2)) which doesn't work. Does anyone know of a command that will work - or perhaps suggest another package that I could use? I have also looked at multiple imputation packages but they all seem to impute data depending on other columns - whereas I would want to impute data between zero and the censored value. Any guidance/advice would be very much appreciated. Laura Dr Laura MacCalman Msci MSc PhD Gradstat Senior Statistician Institute of Occupational Medicine Research Avenue North Riccarton Edinburgh EH14 4AP Tel: 0131 449 8078 Fax: 0131 449 8084 Mob: 07595 054 881 Email: laura.maccal...@iom-world.org Web: http://www.iom-world.org -------------------------------------------------------------------------- The Institute of Occupational Medicine (IOM) is a company limited by guarantee, registered in Scotland (No.SC123972) and a Registered Scottish Charity (No.SC000365). IOM Consulting Ltd is a wholly owned subsidiary of IOM and a private limited company registered in Scotland (No. SC205670). Registered Office: Research Avenue North, Riccarton, Edinburgh, EH14 4AP, Tel +44 (0)131 449 8000. This email and any files transmitted with it are confide...{{dropped:18}} ______________________________________________ R-help@r-project.org mailing list 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.
