Re: [R] lme nesting/interaction advice
On 11 May 2008, at 22:45, Andrew Robinson wrote: lme(y ~ selection * males, random = ~1|replica/selection/males, mydata) forgive me, but I seem to see nesting in the random statement. That is what happens when we separate factors with a '/'; they are nested. We would expect that statement to not provide the correct df for the bog-standard fully crossed design. Please read page 23/24 of the Pinheiro and Bates book, Mixed-Effects Models in S and S-PLUS. It might prove enlightening. F -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ 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.
Re: [R] lme nesting/interaction advice
On 12 May 2008, at 01:05, Andrew Robinson wrote: On Mon, May 12, 2008 at 10:34:40AM +1200, Rolf Turner wrote: On 12/05/2008, at 9:45 AM, Andrew Robinson wrote: On Sun, May 11, 2008 at 07:52:50PM +0100, Federico Calboli wrote: The main point of my question is, having a 3 way anova (or ancova, if you prefer), with *no* nesting, 2 fixed effects and 1 random effect, why is it so boneheaded difficult to specify a bog standard fully crossed model? I'm not talking about some rarified esoteric model here, we're talking about stuff tought in a first year Biology Stats course here[1]. That may be so, but I've never needed to use one. So what? This is still a standard, common, garden-variety model that you will encounter in exercises in many (if not all!) textbooks on experimental design and anova. To reply in similar vein, so what? Why should R-core or the R community feel it necessary to reproduce every textbook example? How many times have *you* used such a model in real statistical work, Rolf? There is a very important reason why R (or any other stats package) should *easily* face the challenge of bog standard models: because it is a *tool* for an end (i.e. the analysis of data to figure out what the heck they tell us) rather than a end in itself. Bog standard models are *likely* to be used over and over again because they are *bog standard*, and they became such by being used *lots*. If someone with a relatively easy model cannot use R for his job s/he will use something else, and the R community will *not* increase in numbers. Since R is a *community driven project*, you do the math on what that would mean in the long run. Regards, Federico -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ 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.
Re: [R] lme nesting/interaction advice
On 12 May 2008, at 09:29, Dieter Menne wrote: Federico: First, mixed models are different from standard 101 Anova, and quite a lot of the nesting stuff I used to ponder about 30 year ago when I started teaching this is no longer relevant and works implicitely when you code the parameters correctly. with effect3 being random (all all the jazz that comes from this fact). I fully apprecciate that the only reasonable F-tests would be for effect1, effect2 and effect1:effect2, but there is no way I can use lme to specify such simple thing without getting the *wrong* denDF. Good to know that you are sure what is right; probably == SAS. Since most people active in the lme-business have read http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests http://finzi.psych.upenn.edu/R/Rhelp02a/archive/76742.html carefully, you might be rather lonely. I will. While I do, feel free to have a look at Appendix A.3 (page App6, at the end of the book) of the Zar 'Biostatistical Analysis', IV ed, second table from the top. That's where I get the feeling for what's right or wrong. I surely cannot get it from SAS because I never had it. I never had the budget for it, so much so I had to lear how to use R from the start because it was free and that was the budget of my department had for stats software All in all, if you feel statistical analysis has moved forth from such humble beginnings (the book I mean, not SAS), and you can convince of that every ref for every paper you submit, please do tell me how you do it, it would be more valuable than knowing how to fit my model. Cheers, Federico -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ 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.
Re: [R] lme nesting/interaction advice
On 11 May 2008, at 23:34, Rolf Turner wrote: It doesn't seem to me to be a complaint as such. It is a request for insight. I too would like some insight as to what on earth is going on. And why do you say Federico shows no evidence of having searched the archives? One can search till one is blue in the face and come away no wiser on this issue. cheers, Rolf Turner Cheers for the support Rolf. I have searched the archives, and have the Pinheiro and Bates book in front of my nose (plus MASS4 and many others). The bottom line here is, I'm pretty cool with RTFM and all that, my problem is that I do not have a clear FM to read about my issue, and hence I have to pester (because that how people seem to feel) the list. I apologise for asking an inconvenient question. Fede -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ 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.
Re: [R] lme nesting/interaction advice
On Mon, May 12, 2008 at 10:50:03AM +0100, Federico Calboli wrote: On 12 May 2008, at 01:05, Andrew Robinson wrote: On Mon, May 12, 2008 at 10:34:40AM +1200, Rolf Turner wrote: On 12/05/2008, at 9:45 AM, Andrew Robinson wrote: On Sun, May 11, 2008 at 07:52:50PM +0100, Federico Calboli wrote: The main point of my question is, having a 3 way anova (or ancova, if you prefer), with *no* nesting, 2 fixed effects and 1 random effect, why is it so boneheaded difficult to specify a bog standard fully crossed model? I'm not talking about some rarified esoteric model here, we're talking about stuff tought in a first year Biology Stats course here[1]. That may be so, but I've never needed to use one. So what? This is still a standard, common, garden-variety model that you will encounter in exercises in many (if not all!) textbooks on experimental design and anova. To reply in similar vein, so what? Why should R-core or the R community feel it necessary to reproduce every textbook example? How many times have *you* used such a model in real statistical work, Rolf? There is a very important reason why R (or any other stats package) should *easily* face the challenge of bog standard models: because it is a *tool* for an end (i.e. the analysis of data to figure out what the heck they tell us) rather than a end in itself. But a tool that mostly (entirely?) appears in textbooks. Bog standard models are *likely* to be used over and over again because they are *bog standard*, and they became such by being used *lots*. Well. I have documentation relevant to nlme that goes back about 10 years. I don't know when it was first added to S-plus, but I assume that it was about then. Now, do you think that if the thing that you want to do was really bog standard, that noone would have raised a fuss or solved it within 10 years? If someone with a relatively easy model cannot use R for his job s/he will use something else, and the R community will *not* increase in numbers. Since R is a *community driven project*, you do the math on what that would mean in the long run. Fewer pestering questions? ;) Andrew -- Andrew Robinson Department of Mathematics and StatisticsTel: +61-3-8344-6410 University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 http://www.ms.unimelb.edu.au/~andrewpr http://blogs.mbs.edu/fishing-in-the-bay/ __ 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.
Re: [R] lme nesting/interaction advice
On 12 May 2008, at 11:16, Andrew Robinson wrote: Well. I have documentation relevant to nlme that goes back about 10 years. I don't know when it was first added to S-plus, but I assume that it was about then. Now, do you think that if the thing that you want to do was really bog standard, that noone would have raised a fuss or solved it within 10 years? I'm pretty unpleasant, more so in person, so I'll tell you this. If people raised the issue and got the answer I got, I would not be surprised if they'd migrated to 'any other stats software' in droves. I have no doubt that, given the cryptic and sparse nature of the documentation of the issue, most people migrated well before asking -- on the grounds most people have a job to do, papers to publish, grants to write, kids to pick up from school and pretty little time for RTFM and all that sanctimonious attitude. Once people stop nagging about 'whatever', the reason is because they finally got the message things ain't gonna improve, so cut your losses and look elsewhere. Being unpleasant, thick skinned and cheap I will keep nagging and use R (the fact I do like it very much might be a factor). But given the selection users go through, it will be Vogon time sooner or later ;). /F -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St. Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 75941602 Fax +44 (0)20 75943193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ 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.
Re: [R] lme nesting/interaction advice
On 10 May 2008, at 07:36, Kingsford Jones wrote: Federico, I think you'll be more likely to receive the type of response you're looking for if you formulate your question more clearly. The inclusion of commented, minimal, self-contained, reproducible code (as is requested at the bottom of every email sent by r-help) is an effective way to clarify the issues. Also, when asking a question about fitting a model it's helpful to describe the specific research questions you want the model to answer. snip I apprecciate that my description of the *full* model is not 100% clear, but my main beef was another. The main point of my question is, having a 3 way anova (or ancova, if you prefer), with *no* nesting, 2 fixed effects and 1 random effect, why is it so boneheaded difficult to specify a bog standard fully crossed model? I'm not talking about some rarified esoteric model here, we're talking about stuff tought in a first year Biology Stats course here[1]. Now, to avoid any chances of being misunderstood in my use of the words 'fully crossed model', what I mean is a simple y ~ effect1 * effect2 * effect3 with effect3 being random (all all the jazz that comes from this fact). I fully apprecciate that the only reasonable F-tests would be for effect1, effect2 and effect1:effect2, but there is no way I can use lme to specify such simple thing without getting the *wrong* denDF. I need light on this topic and I'd say it's a general enough question not to need much more handholding than this. Having said that, I did look at the mixed-effects mailing list before posting here, and it looks like it was *not* the right place to post anyway: 'This mailing list is primarily for useRs and programmeRs interested in *development* and beta-testing of the lme4 package.' although the R-Me is now CC'd in this. I fully apprecciate that R is developed for love, not money, and if I knew how to write an user friendly frontend for nlme and lme4 (and I knew how to actually get the model I want) I'd be pretty happy to do so and submit it as a library. In any case, I feel my complaint is pefectly valid, because specifying such basic model should ideally not such a chore, and I think the powers that be might actually find some use from user feedback. Once I have sorted how to specify such trivial model I'll face the horror of the nesting, in any case I attach a toy dataset I created especially to test how to specify the correct model (silly me). Best, Federico Calboli [1] So much bog standard that the Zar, IV ed, gives a nice table of how to compute the F-tests correctly, taking into account that one of the 3 effects is randon (I'll send the exact page and table number tomorrow, I don't have the book at home). selection linemales month block y L L1 1 a 1 13.8156357121188 L L1 1 a 1 12.5678496952169 L L1 1 a 1 17.1313698710874 L L1 1 a 1 3.87016302696429 L L1 1 a 1 13.2627072110772 L L2 1 a 1 17.835768135963 L L2 1 a 1 19.3615794742946 L L2 1 a 1 1.73416316602379 L L2 1 a 1 12.9440758333076 L L2 1 a 1 2.09191741654649 S S1 1 a 1 1.56137526640669 S S1 1 a 1 17.6580698778853 S S1 1 a 1 18.1417595115490 S S1 1 a 1 15.5621050691698 S S1 1 a 1 17.0240987658035 S S2 1 a 1 12.4378062419128 S S2 1 a 1 6.63962595071644 S S2 1 a 1 16.6060689473525 S S2 1 a 1 7.1222553497646 S S2 1 a 1 18.0590278783347 L L1 2 a 1 1.24710303940810 L L1 2 a 1 4.62720696791075 L L1 2 a 1 16.0327167815994 L L1 2 a 1 6.12926463945769 L L1 2 a 1 7.65810538828373 L L2 2 a 1 7.44077128893696 L L2 2 a 1 14.9197938004509 L L2 2 a 1 13.4244954204187 L L2 2 a 1 11.5361888066400 L L2 2 a 1 2.60056478204206 S S1 2 a 1 14.8965472229756 S S1 2 a 1 18.777876078384 S S1 2 a 1 6.80722737265751 S S1 2 a 1 13.1697203880176 S S1 2 a 1 3.74557441123761 S S2 2 a 1 5.41025308240205 S S2 2 a 1 19.8277674221899 S S2 2 a 1
Re: [R] lme nesting/interaction advice
On Sun, May 11, 2008 at 07:52:50PM +0100, Federico Calboli wrote: The main point of my question is, having a 3 way anova (or ancova, if you prefer), with *no* nesting, 2 fixed effects and 1 random effect, why is it so boneheaded difficult to specify a bog standard fully crossed model? I'm not talking about some rarified esoteric model here, we're talking about stuff tought in a first year Biology Stats course here[1]. That may be so, but I've never needed to use one. If it's bog-standard and yet boneheaded difficult, then presumably someone else would have had this problem before you. Perhaps a search of the archives will help? If you try, you will find many qualifiers to the effect that lme isn't very well set up for crossed random effects. Now, to avoid any chances of being misunderstood in my use of the words 'fully crossed model', what I mean is a simple y ~ effect1 * effect2 * effect3 with effect3 being random (all all the jazz that comes from this fact). I fully apprecciate that the only reasonable F-tests would be for effect1, effect2 and effect1:effect2, but there is no way I can use lme to specify such simple thing without getting the *wrong* denDF. I need light on this topic and I'd say it's a general enough question not to need much more handholding than this. Perhaps there are some circumstances unique to your situation. I fully apprecciate that R is developed for love, not money, ... as is the R-help community ... and if I knew how to write an user friendly frontend for nlme and lme4 (and I knew how to actually get the model I want) I'd be pretty happy to do so and submit it as a library. In any case, I feel my complaint is pefectly valid, because specifying such basic model should ideally not such a chore, and I think the powers that be might actually find some use from user feedback. This is not feedback. It is a compliant. But, the complaint boils down to the fact that you don't know what you're doing, and you show no evidence of having searched the R-help archives. How is that helpful? Once I have sorted how to specify such trivial model I'll face the horror of the nesting, in any case I attach a toy dataset I created especially to test how to specify the correct model (silly me). Well, these data seem to differ. Is replica block? If not, then how can we reproduce your results? And, if I assume that it is, then the output df differ from what you sent in your original mail. So, I find this confusing. Then, from your original mail, The easiest model ignores the nested random effects and uses just selection, males and replica and the relative interactions. The model lme(y ~ selection * males, random = ~1|replica/selection/males, mydata) forgive me, but I seem to see nesting in the random statement. That is what happens when we separate factors with a '/'; they are nested. We would expect that statement to not provide the correct df for the bog-standard fully crossed design. Perhaps if you were to comply with the request at the bottom of each R-help email, and provide commented, minimal, self-contained, reproducible code, that actually ran, ideally with fewer value judgements, you might get more attention from the people who are smarter than you and me, but have less time than either of us. Andrew -- Andrew Robinson Department of Mathematics and StatisticsTel: +61-3-8344-6410 University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 http://www.ms.unimelb.edu.au/~andrewpr http://blogs.mbs.edu/fishing-in-the-bay/ __ 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.
Re: [R] lme nesting/interaction advice
On 12/05/2008, at 9:45 AM, Andrew Robinson wrote:
On Sun, May 11, 2008 at 07:52:50PM +0100, Federico Calboli wrote:
The main point of my question is, having a 3 way anova (or ancova, if
you prefer), with *no* nesting, 2 fixed effects and 1 random effect,
why is it so boneheaded difficult to specify a bog standard fully
crossed model? I'm not talking about some rarified esoteric model
here, we're talking about stuff tought in a first year Biology Stats
course here[1].
That may be so, but I've never needed to use one.
So what? This is still a standard, common, garden-variety
model that you will encounter in exercises in many (if not
all!) textbooks on experimental design and anova.
If it's bog-standard and yet boneheaded difficult, then presumably
someone else would have had this problem before you. Perhaps a search
of the archives will help? If you try, you will find many qualifiers
to the effect that lme isn't very well set up for crossed random
effects.
But that avoids the question as to *why* it isn't very well
set up for crossed random effects? What's the problem?
What are the issues? The model is indeed bog-standard.
It would seem not unreasonable to expect that it could be
fitted in a straightforward manner, and it is irritating to
find that it cannot be. If SAS and Minitab can do it at
the touch of a button, why can't R do it?
Now, to avoid any chances of being misunderstood in my use of the
words 'fully crossed model', what I mean is a simple
y ~ effect1 * effect2 * effect3
with effect3 being random (all all the jazz that comes from this
fact). I fully apprecciate that the only reasonable F-tests would be
for effect1, effect2 and effect1:effect2, but there is no way I can
use lme to specify such simple thing without getting the *wrong*
denDF. I need light on this topic and I'd say it's a general enough
question not to need much more handholding than this.
Perhaps there are some circumstances unique to your situation.
Huh?
I fully apprecciate that R is developed for love, not money,
... as is the R-help community ...
and if I
knew how to write an user friendly frontend for nlme and lme4 (and I
knew how to actually get the model I want) I'd be pretty happy to do
so and submit it as a library. In any case, I feel my complaint is
pefectly valid, because specifying such basic model should ideally
not such a chore, and I think the powers that be might actually find
some use from user feedback.
This is not feedback. It is a compliant. But, the complaint boils
down to the fact that you don't know what you're doing
That's rubbish. I think it's fairly clear that Federico does
have a pretty good idea of what he's doing, but is flummoxed
by the arcana of lme(). As am I.
and you show
no evidence of having searched the R-help archives. How is that
helpful?
It doesn't seem to me to be a complaint as such. It is a
request for insight. I too would like some insight as to
what on earth is going on. And why do you say Federico
shows no evidence of having searched the archives? One can
search till one is blue in the face and come away no wiser
on this issue.
cheers,
Rolf Turner
##
Attention:\ This e-mail message is privileged and confid...{{dropped:9}}
__
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.
Re: [R] lme nesting/interaction advice
On Mon, May 12, 2008 at 10:34:40AM +1200, Rolf Turner wrote: On 12/05/2008, at 9:45 AM, Andrew Robinson wrote: On Sun, May 11, 2008 at 07:52:50PM +0100, Federico Calboli wrote: The main point of my question is, having a 3 way anova (or ancova, if you prefer), with *no* nesting, 2 fixed effects and 1 random effect, why is it so boneheaded difficult to specify a bog standard fully crossed model? I'm not talking about some rarified esoteric model here, we're talking about stuff tought in a first year Biology Stats course here[1]. That may be so, but I've never needed to use one. So what? This is still a standard, common, garden-variety model that you will encounter in exercises in many (if not all!) textbooks on experimental design and anova. To reply in similar vein, so what? Why should R-core or the R community feel it necessary to reproduce every textbook example? How many times have *you* used such a model in real statistical work, Rolf? If it's bog-standard and yet boneheaded difficult, then presumably someone else would have had this problem before you. Perhaps a search of the archives will help? If you try, you will find many qualifiers to the effect that lme isn't very well set up for crossed random effects. But that avoids the question as to *why* it isn't very well set up for crossed random effects? What's the problem? What are the issues? The model is indeed bog-standard. It would seem not unreasonable to expect that it could be fitted in a straightforward manner, and it is irritating to find that it cannot be. If SAS and Minitab can do it at the touch of a button, why can't R do it? Bates has made no secret of the fact that lme was intended first and foremost for nested designs, and that support for crossed designs is not promised. He has said so on many occasions, as a search would find. He is now working on lme4, which will support crossed designs. It's not done yet. and you show no evidence of having searched the R-help archives. How is that helpful? It doesn't seem to me to be a complaint as such. It is a request for insight. I too would like some insight as to what on earth is going on. And why do you say Federico shows no evidence of having searched the archives? One can search till one is blue in the face and come away no wiser on this issue. At least one can know that there is an issue, which apparently Federico previously did not. Warm wishes Andrew -- Andrew Robinson Department of Mathematics and StatisticsTel: +61-3-8344-6410 University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 http://www.ms.unimelb.edu.au/~andrewpr http://blogs.mbs.edu/fishing-in-the-bay/ __ 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.
Re: [R] lme nesting/interaction advice
On Fri, May 9, 2008 at 4:04 AM, Federico Calboli [EMAIL PROTECTED] wrote: Note that random can be a list: a one-sided formula of the form ~x1+...+xn, or a pdMat object with a formula (i.e. a non-NULL value for formula(object)), or a list of such formulas or pdMat objects. If you can translate that into *informative* English I'd be grateful. I have the Pinheiro and Bates book under my nose now, and I suspect it's pretty more extensive that the helpfile, but it's still nowhere close to providing a straigtforward answer to my question. Federico, I think you'll be more likely to receive the type of response you're looking for if you formulate your question more clearly. The inclusion of commented, minimal, self-contained, reproducible code (as is requested at the bottom of every email sent by r-help) is an effective way to clarify the issues. Also, when asking a question about fitting a model it's helpful to describe the specific research questions you want the model to answer. I'll offer my interpretation of your study design so you can see where questions might arise. It sounds like you have protein measures (on how many units?) at various levels of 'male' (which at first you described as presence/absence, but later as continuous - also you descibed 'male' as fixed and continuous but then entered it in the formula as though it were a random grouping factor), within the second level of 'selection' (e.g. large1), within the first level of selection (e.g. large), within a random block (what are the blocks?) within a random month. Is this right -- multiple observations within 4 levels of nesting - some of which are random and some fixed? Finally, I'll point out that there's an R list dedicated to mixed models, with a particular focus on the lmer function, which might be the right tool for your analyses ( https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models ). Kingsford Jones Cheers, Federico -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 7594 1602 Fax (+44) 020 7594 3193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ 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.
Re: [R] lme nesting/interaction advice
Federico Calboli f.calboli at imperial.ac.uk writes: Hi everyone, I am confused on how to specify some nesting and interaction terma with lme(). lme(y ~ selection * males, random = ~1|replica/selection/males, mydata) Note that random can be a list: a one-sided formula of the form ~x1+...+xn, or a pdMat object with a formula (i.e. a non-NULL value for formula(object)), or a list of such formulas or pdMat objects. Dieter __ 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.
Re: [R] lme nesting/interaction advice
Note that random can be a list: a one-sided formula of the form ~x1+...+xn, or a pdMat object with a formula (i.e. a non-NULL value for formula(object)), or a list of such formulas or pdMat objects. If you can translate that into *informative* English I'd be grateful. I have the Pinheiro and Bates book under my nose now, and I suspect it's pretty more extensive that the helpfile, but it's still nowhere close to providing a straigtforward answer to my question. Cheers, Federico -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 7594 1602 Fax (+44) 020 7594 3193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ 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.
