[R-sig-ME] R-sig-mixed-models Digest, Vol 26, Issue 12

Iasonas Lamprianou lamprianou at yahoo.com
Sun Feb 8 20:24:59 CET 2009


Dear Douglas Bates

we all support you and you should not allow anyone make you feel upset. You are contributing/offering a lot to all of us and we are greateful. Keep on good work and try to ignore other nuisances. lme4 is the reason why a number of people considered R at the first place

jason

Dr. Iasonas Lamprianou
Department of Education
The University of Manchester
Oxford Road, Manchester M13 9PL, UK
Tel. 0044  161 275 3485
iasonas.lamprianou at manchester.ac.uk


--- On Sun, 8/2/09, r-sig-mixed-models-request at r-project.org <r-sig-mixed-models-request at r-project.org> wrote:

> From: r-sig-mixed-models-request at r-project.org <r-sig-mixed-models-request at r-project.org>
> Subject: R-sig-mixed-models Digest, Vol 26, Issue 12
> To: r-sig-mixed-models at r-project.org
> Date: Sunday, 8 February, 2009, 11:00 AM
> Send R-sig-mixed-models mailing list submissions to
> 	r-sig-mixed-models at r-project.org
> 
> To subscribe or unsubscribe via the World Wide Web, visit
> 	https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> or, via email, send a message with subject or body
> 'help' to
> 	r-sig-mixed-models-request at r-project.org
> 
> You can reach the person managing the list at
> 	r-sig-mixed-models-owner at r-project.org
> 
> When replying, please edit your Subject line so it is more
> specific
> than "Re: Contents of R-sig-mixed-models
> digest..."
> 
> 
> Today's Topics:
> 
>    1. Lack of replies from me (Douglas Bates)
>    2. Re: Lack of replies from me (Andrew Robinson)
>    3. logistic growth, vexing choice of which timepoints
>       (Nicholas Lewin-Koh)
> 
> 
> ----------------------------------------------------------------------
> 
> Message: 1
> Date: Sat, 7 Feb 2009 08:33:59 -0600
> From: Douglas Bates <bates at stat.wisc.edu>
> Subject: [R-sig-ME] Lack of replies from me
> To: R Models Mixed <r-sig-mixed-models at r-project.org>
> Message-ID:
> 	<40e66e0b0902070633s428cbf0ekd3e37f1e82ccf2be at mail.gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1
> 
> I regret that I have been absent from the list for some
> time.  It
> happens that in the last couple of weeks I have been
> involved in a
> series of extremely unpleasant interactions on another,
> private email
> list that have left me with little enthusiasm for
> developing and
> supporting CRAN packages.  One conclusion I have reached
> from these
> interactions is that I will never allow lme4 to be a
> recommended
> package in R.  I am even having doubts about whether I want
> it to
> continue to be a CRAN package at all, as opposed to, say,
> moving it to
> Bioconductor or even switching development to another
> language.
> 
> I'm sure the last option would be "cutting off my
> nose to spite my
> face" and I don't expect I would ever do that. 
> There are many
> wonderful aspects to R and many reasons why I want to
> continue to use
> it.  But right now I find myself forced to evaluate options
> other than
> putting a package on CRAN.
> 
> 
> 
> ------------------------------
> 
> Message: 2
> Date: Sun, 8 Feb 2009 07:13:06 +1100
> From: Andrew Robinson <A.Robinson at ms.unimelb.edu.au>
> Subject: Re: [R-sig-ME] Lack of replies from me
> To: Douglas Bates <bates at stat.wisc.edu>
> Cc: R Models Mixed <r-sig-mixed-models at r-project.org>
> Message-ID:
> <20090207201306.GP51827 at ms.unimelb.edu.au>
> Content-Type: text/plain; charset=us-ascii
> 
> On Sat, Feb 07, 2009 at 08:33:59AM -0600, Douglas Bates
> wrote:
> > I regret that I have been absent from the list for
> some time.  It
> > happens that in the last couple of weeks I have been
> involved in a
> > series of extremely unpleasant interactions on
> another, private email
> > list that have left me with little enthusiasm for
> developing and
> > supporting CRAN packages.  One conclusion I have
> reached from these
> > interactions is that I will never allow lme4 to be a
> recommended
> > package in R.  I am even having doubts about whether I
> want it to
> > continue to be a CRAN package at all, as opposed to,
> say, moving it to
> > Bioconductor or even switching development to another
> language.
> > 
> > I'm sure the last option would be "cutting
> off my nose to spite my
> > face" and I don't expect I would ever do
> that.  There are many
> > wonderful aspects to R and many reasons why I want to
> continue to use
> > it.  But right now I find myself forced to evaluate
> options other than
> > putting a package on CRAN.
> 
> I'm very sorry to hear about your frustrations, Doug. 
> I'm sure that I
> speak for all of us when I say that we'll continue to
> use and support
> lme4 regardless of the delivery mechanism.
> 
> Warm wishes
> 
> Andrew
> -- 
> Andrew Robinson  
> Department of Mathematics and Statistics            Tel:
> +61-3-8344-6410
> University of Melbourne, VIC 3010 Australia              
> (prefer email)
> http://www.ms.unimelb.edu.au/~andrewpr              Fax:
> +61-3-8344-4599
> http://blogs.mbs.edu/fishing-in-the-bay/
> 
> 
> 
> ------------------------------
> 
> Message: 3
> Date: Sat, 07 Feb 2009 14:16:56 -0800
> From: "Nicholas Lewin-Koh"
> <nikko at hailmail.net>
> Subject: [R-sig-ME] logistic growth, vexing choice of which
> timepoints
> To: r-sig-mixed-models at r-project.org
> Cc: Jenny Bryan <jenny at stat.ubc.ca>
> Message-ID:
> <1234045016.6848.1299107865 at webmail.messagingengine.com>
> Content-Type: text/plain; charset="ISO-8859-1"
> 
> Hi Jenny
> What Steven said below is true, the zeros are below the
> detection limit.
> However,
> one might ask if the time until the populations cross the
> detection
> threshold matters?
> For instance if two wells treated differently both have
> similar logistic
> curves, but one 
> starts accelerating at t(i) and the other at t(j), j > i
> that does
> provide some information about
> what is going on below the detection limit. A sophisticated
> approach
> might be to fit a joint model
> modeling the time to the event, and the logistic growth
> simultaneously.
> Given that that is 
> hard, and there may not be any software to do it, you might
> want to fit
> the survival model (time to event)
> and then the logistic growth model n the non-zero data.
> This is very
> add-hoc, but will at least give you
> some idea of whether it is worth chasing a more complicated
> model. This
> will be more effective if 
> you have replicate wells. 
> 
> Nicholas
> 
> > Message: 1
> > Date: Fri, 6 Feb 2009 13:54:47 -0800
> > From: Jenny Bryan <jenny at stat.ubc.ca>
> > Subject: [R-sig-ME] logistic growth,	vexing choice of
> which timepoints
> > 	to include
> > To: r-sig-mixed-models at r-project.org
> > Message-ID:
> <4B7E17CD-C967-479F-85CD-97404D975969 at stat.ubc.ca>
> > Content-Type: text/plain; charset=US-ASCII;
> format=flowed; delsp=yes
> > 
> > Hello.  I'm looking for advice on how to make a
> seemingly unavoidable  
> > subjective choice in an analysis I'm doing, using
> the logistic growth  
> > model.  I'm using nlme, but that has nothing to do
> with my question,  
> > so I hope it's not too inappropriate for me to
> post this here.   
> > Reading the list archive suggests that it's not
> too hard to tempt this  
> > group into philosophical discussions :-)
> > 
> > I have growth data that can be reasonably modelled
> with a four- 
> > parameter logistic curve.  The experimental unit is a
> well in a  
> > microtitre plate and I get light absorbance readings
> over time that  
> > reflect cell density.  There are many wells on a
> plate, e.g. 96 or  
> > 384, and experiments often span many plates. 
> Systematic differences  
> > between the wells can be, for example, specific
> genetic mutations  
> > carried by the cells and/or different chemicals added
> to the growth  
> > medium.  I am mostly interested in performing
> inference on the fixed  
> > effects, i.e. how the genetic perturbations, the
> chemicals, or their  
> > interactions, modify key growth parameters, especially
> the one  
> > inversely related to the underlying exponential growth
> rate we'd see  
> > in the absence of resource constraints (phi_4 in
> Pinheiro & Bates p.  
> > 517).
> > 
> > Problem:  The number of cells inoculated into the
> wells at the start  
> > is quite small -- well below the detection threshhold
> for the light  
> > absorbance readings.  Therefore, each timecourse
> begins with a loooong  
> > string of zeros, before the classic sigmoidal shape
> kicks in.  And, of  
> > course, the timing of this happy event is both
> ill-defined and very  
> > variable across the wells.
> > 
> > For figure-making purposes, I removed some early
> timepoints that were  
> > uniformly zero for all wells.  Which made me wonder:
> why couldn't  
> > (shouldn't?) I do the same prior to model fitting?
>  When I fit the  
> > logistic growth model with and without these early
> timepoints, I get  
> > essentially the same estimated fixed effects and,
> even, estimated  
> > variances for the random effects.  But there *is* a
> substantial  
> > difference in the estimate of residual variance, which
> then obviously  
> > has a noticeable effect on the inference for the fixed
> effects and,  
> > especially, the one I care about.  Including all the
> timepoints drives  
> > the residual variance down, as you might expect.  But
> that almost  
> > seems misleading or artificial ... other collaborators
> I work with  
> > don't even start taking OD readings until the
> first 12 hours have  
> > passed, which makes their initial strings of zeros
> quite short,  
> > which ... gives them less statistical significance for
> the same  
> > observed effect size?!?
> > 
> > Does anyone have a comment or advice?
> > 
> > Thanks in advance for reading this,
> > Jenny
> > 
> > Jennifer Bryan
> > Department of Statistics and
> >    the Michael Smith Laboratories
> > University of British Columbia
> > 
> > 
> > 
> > ------------------------------
> > 
> > Message: 2
> > Date: Fri, 6 Feb 2009 15:18:53 -0800
> > From: Steven McKinney <smckinney at bccrc.ca>
> > Subject: Re: [R-sig-ME] logistic growth,	vexing choice
> of which
> > 	timepoints to include
> > To: "Jenny Bryan" <jenny at stat.ubc.ca>,
> > 	<r-sig-mixed-models at r-project.org>
> > Message-ID:
> >
> 	<0BE438149FF2254DB4199E2682C8DFEB0328A5AC at crcmail1.BCCRC.CA>
> > Content-Type: text/plain;
> charset="iso-8859-1"
> > 
> > Hi Jenny,
> > 
> > [Caveat: Comments from an applied statistician, not
> > a world-heavyweight likelihood theorist]
> > 
> > In the logistic world a zero value maps to a 
> > minus infinity value.  It seems to me that only
> > the 'last' zero value contains any information
> > relevant to the likelihood (equivalently only
> > the 'first' one value (plus infinity in the
> > logistic realm) contains any information
> > relevant to the likelihood).  Perhaps the
> > coding for the likelihood has not been set
> > up to take this into account so you are getting
> > the artificial contribution of the rest of the
> > zero values folded into the likelihood, artificially
> > deflating the variance estimates.
> > 
> > I would exclude or set to NA all but the last
> > (or even all of) the zero values for any well
> > and all but the first (or even all of) the one 
> > values.
> > 
> > The zero values are really below the detection
> > limit of the sensor involved so should theoretically
> > be handled as truncated data but that's another
> > level of complexity for the analysis.
> > 
> > Steven McKinney
> > 
> > Statistician
> > Molecular Oncology and Breast Cancer Program
> > British Columbia Cancer Research Centre
> > 
> > email: smckinney +at+ bccrc +dot+ ca
> > 
> > tel: 604-675-8000 x7561
> > 
> > BCCRC
> > Molecular Oncology
> > 675 West 10th Ave, Floor 4
> > Vancouver B.C. 
> > V5Z 1L3
> > Canada
> > 
> > 
> > 
> >
> 
> 
> 
> ------------------------------
> 
> _______________________________________________
> R-sig-mixed-models mailing list
> R-sig-mixed-models at r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> 
> 
> End of R-sig-mixed-models Digest, Vol 26, Issue 12
> **************************************************







More information about the R-sig-mixed-models mailing list