I would probably start with maximum likelihood estimation. I suppose you could impute X and Y separately using ros() from the NADA package, and then run you ordinary regression on the imputed values. Obviously, this ignores any relationship between X and Y, since each is imputed independently of the other. I have no idea whether ordinary inferences on the parameter estimates would be valid. Probably not. Probably, MLE would be better.
-Don -- Don MacQueen Lawrence Livermore National Laboratory 7000 East Ave., L-627 Livermore, CA 94550 925-423-1062 On 4/15/13 8:55 AM, "Laura MacCalman" <laura.maccal...@iom-world.org> wrote: > >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. ______________________________________________ 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.