Re: REML models for Double censored data

From: MacNeil, Mike <Mike.Macneil_at_ARS.USDA.GOV>
Date: Wed, 27 Feb 2008 07:59:34 -0700

We might have usable data sets for such an endeavor. I have not looked
closely at the data, yet. We have been collecting age at puberty
observations in beef heifers. Some heifers are already puberal when data
collection begins and some don't attain puberty before we quit observing
them. Obviously, if more censoring were desired than is actually present
in the data, observations could be truncated at either end of the
distribution. Another appilcation for which we would also have data is
in studying functional longevity of beef cows. Some heifers might never
be exposed and thus censored. Other, still functional, cows might be
culled and thus also censored. Both data sets would have pedigree
information ammenable to genetic analysis.
If either of these data sets are of potential interest let me know. I
would be happy to address specific questions regarding either of them.
Michael D. MacNeil
Research Geneticist
USDA- Agricultural Research Service
Miles City, MT 59301
(406) 874-8213 voice
(406) 874-8289 fax


From: ASReml users discussion group [mailto:ASREML-L_at_AGRIC.NSW.GOV.AU]
On Behalf Of arthur.gilmour_at_DPI.NSW.GOV.AU
Sent: Tuesday, February 26, 2008 6:58 PM
Subject: REML models for Double censored data

Dear ASREMLers,

A colleague of mine has developed a method to fit a normal linear mixed
model with doubly censored data, that is some of data are recorded as
less than some value and some are recorded as greater than some value.
An example could be analytical results obtained via an instrument having
lower and upper analytical thresholds. The thresholds need not be the
same for each observation but must be independent of the (un)observed

The method developed allows for an unlimited number of uncorrelated
random terms in the model and can include spline models.

In order to prepare a manuscript detailing the method it would be useful
to have an interesting real data example to include.

This email is a search for such a data set. That is, the data must
include doubly censored data fitting the above model requirements
(including more than one non-residual random term) and be available for
inclusion in a manuscript. What would also be useful is knowing how the
data was originally analysed.

Please direct all replies to this request to Remy van de Ven (Email:


May Jesus Christ be gracious to you in 2008,

Arthur Gilmour, His servant .

Mixed model regression mapping for QTL detection in experimental
crosses. Computational Statistics and Data Analysis 51:3749-3764 at

Personal website:
Skype: arthur.gilmour,
Principal Research Scientist (Biometrics)
NSW Department of Primary Industries
Orange Agricultural Institute, Forest Rd, ORANGE, 2800, AUSTRALIA

fax: 02 6391 3899; 02 6391 3922 Australia +61
telephone work: 02 6391 3815; home: 02 6364 3288; mobile: 0438 251 426

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Received on Sat Feb 27 2008 - 07:59:34 EST

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