[R] regression with paired left-censored data

[MacQueen, Don]

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.MacCalman at 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
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>
>Tel: 0131 449 8078
>Fax: 0131 449 8084
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>Email: Laura.MacCalman at iom-world.org
>
>Web: http://www.iom-world.org
> 
>
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