Re: [R] Effect display of proportional odds model
I REALLY found this paper to be helpful. Will you please let the list know once you have made the update? Thank you, Jeff Miller University of Florida -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of John Fox Sent: Friday, March 23, 2007 9:07 AM To: 'Jan Wijffels' Cc: r-help@stat.math.ethz.ch Subject: Re: [R] Effect display of proportional odds model Dear Jan, First, I inadvertently removed material on these displays from my web site when the paper was published in Sociological Methodology 2006. I'll update and repost the material some time in the next couple of days, including a copy of the published paper (with a link on my home page). Second, the appendix to the paper and the originally posted examples didn't include the code for Figure 8 (which is Figure 10 in the published version of the paper). I'll add that. Regards, John John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox > -Original Message- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Jan Wijffels > Sent: Friday, March 23, 2007 7:36 AM > To: r-help@stat.math.ethz.ch > Subject: [R] Effect display of proportional odds model > > Dear useRs, > I very much like the effect display of the proportional odds model on > page 29 (Figure 8) of the following paper by John Fox: > http://socserv.mcmaster.ca/jfox/Papers/logit-effect-displays.pdf > It really gives a very concise overview of the model. I would like to > use it to illustrate the proportional odds mixed models we fit here > for a project on Diabetes but I can't seem to reproduce the plot. Does > anyone have code for the plot? > Maybe John Fox himself? I would appreciate it very much. > Thanks, > Jan > > Jan Wijffels > University Center for Statistics > W. de Croylaan 54 > 3001 Heverlee > Belgium > tel: +32 (0)16 322784 > fax: +32 (0)16 322831 > <http://www.kuleuven.be/ucs> http://www.kuleuven.be/ucs > > > > Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm > > > [[alternative HTML version deleted]] > > __ > R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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@stat.math.ethz.ch 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] logistic regression TRY LOGISTF
If Ted is right, then one work-around is to use Firth's method for penalized log-likelihood. The technique is originally intended to reduce small sample bias. However, it's now being extended to deal with complete and quasi separation problems. I believe the library is called logistf but I haven't had a chance to try itI know the SAS version (called the fl macro) works fine. Reference -- http://www.meduniwien.ac.at/user/georg.heinze/techreps/tr2_2004.pdf Hope this helps, Jeff Miller University of Florida AlphaPoint05, Inc. -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Ted Harding Sent: Thursday, March 15, 2007 2:39 PM To: R-help Subject: Re: [R] logistic regression On 15-Mar-07 17:03:50, Milton Cezar Ribeiro wrote: > Dear All, > > I would like adjust and know the "R2" of following presence/absence > data: > > x<-1:10 > y<-c(0,0,0,0,0,0,0,1,1,1) > > I tryed use clogit (survival package) but it don´t worked. > > Any idea? > > miltinho You are trying to fit an equation P[y = 1 ; x] = exp((x-a)/b))/(1 + exp((x-a)/b)) to data x = 1 2 3 4 5 6 7 8 9 10 y = 0 0 0 0 0 0 0 1 1 1 by what amounts to a maximum-likelihood method, i.e. which chooses the parameter values to maximize the probability of the observed values of y (given the values of x). The maximum probability possible is 1, so if you can find parameters which make P[y = 1] = 0 for x = 1, 2, ... , 7 and P[y = 1] for x = 8, 9, 10 then you have done it. This will be approximated as closely as you please for any value of a between 7 and 8, and sufficiently small values of b, since for such parameter values P[y = 1 ; x] -> 0 for x < a, and -> 1 for x > a. You therefore have a solution which is both indeterminate (any a such that 7 < a < 8) and singular (b -> 0). So it will defeat standard estimation methods. That is the source of your problem. In a more general context, this is an instance of the "linear separation" problem in logistic regression (and similar methods, such a probit analysis). Basically, this situation implies that, according to the data, there is a perfect prediction for the results. There is no well-defined way of dealing with it; any approach starts from the proposition "this perfect prediction is not a reasonable result in the context of my data", and continues by following up what you think should be meant by "not a reasonable result". What this is likely to mean would be on the lines of "b should not be that small", which then imposes upon you the need to be more specific about how small b may reasonably be. Then carry on from there (perhaps by fixing the value of b at different reasonable levels, and simply fitting a for each value of b). Hoping this helps ... but I'm wondering how it happens that you have such data ... ?? best wishes, Ted. E-Mail: (Ted Harding) <[EMAIL PROTECTED]> Fax-to-email: +44 (0)870 094 0861 Date: 15-Mar-07 Time: 19:38:51 -- XFMail -- __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] Zero-inflated predictor
Hi all, Does anyone know how to deal with a zero-inflated count PREDICTOR? I know we can use ZIP, Hurdle, etc for zero-inflated response variables, but what if the problem occurs with one of the covariates? I have already found that the literature is correct in stating that any transformation will just lead to a distribution with a different inflated value, so the arcsin is out. Thanks, Jeff __ R-help@stat.math.ethz.ch 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] Multilevel Modeling in R
Wow, would someone please send pdf links like that for SEM? Thanks, Jeff -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Chuck Cleland Sent: Monday, December 04, 2006 1:01 PM To: Matthew Bridgman Cc: r-help@stat.math.ethz.ch Subject: Re: [R] Multilevel Modeling in R Matthew Bridgman wrote: > Can anyone recommend a good text or resource for learning how to do > Multilevel modeling in R? Here are a few other resources in addition to Pinheiro & Bates (2000): http://finzi.psych.upenn.edu/R/library/mlmRev/doc/MlmSoftRev.pdf http://cran.r-project.org/doc/packages/multilevel.pdf http://stat.ethz.ch/CRAN/doc/Rnews/Rnews_2003-3.pdf [Lockwood, Doran & McCaffrey] http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-mixed-models.pd f > Thanks, >Matt > > __ > R-help@stat.math.ethz.ch 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. -- Chuck Cleland, Ph.D. NDRI, Inc. 71 West 23rd Street, 8th floor New York, NY 10010 tel: (212) 845-4495 (Tu, Th) tel: (732) 512-0171 (M, W, F) fax: (917) 438-0894 __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] creating column based on another variable
Hi all, I hope someone can help me with this. Suppose I import a text file and one of the columns looks like this: New York New York England Spain Spain Orlando New York England France I want to add a variable that is based on the previous one US US Europe Europe Europe US US Europe Europe How do that? Also, I would like to be able to export the data as a text file that retains this new variable. Any suggestions are greatly appreciated, Jeff Miller [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] McQuitty method
Is anyone able to explain the McQuitty method in hclust? Thanks in advance, Jeff Miller [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] multiple R listservs?
I thought more about this last night after my email about putting an end to "Read the Manual" replies. It seems that there are a handful of R Super-Programmers. If I were one, I would get tired of 100's of questions like "How can I get my Excel file into R!!!". Concurrently, R is experiencing an exponential increase in new users to the extent that there are now discussions about the use of R in academia. Further, this increase is occurring across a breadth of disciplines. So, to brush aside easy questions is to potentially brush aside new users and put us in snooty-camp. A potential solution is to offer two lists.one for newbies and one for.umm.not-newbies. Some not-newbies may prefer subscribing to both and setting up 2 email folders. Jeff [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] Repeated measures by lme and aov give different results
Nothing personal against Spencer. However, I feel that the response was
similar to just saying, "Let's not use the listserv anymore". Personally, I
find most, if not all, of the questions to be very helpful. I use them to
learn the language. When something looks over-my-head, I put it in a folder
for future reference. It's nice now to respond to the easy questions...
I would also suggest an end to the "Why don't you read the R guides at
CRAN?" responses...unless accompanied by a response to the actual question.
Pushing people away from posting to the listserv seems to be against both
the purpose of a listserv and open-source ideology.
Jeff
P.S. I'm not sure why aov and lme gave you discrepant findings; however, I'm
not sure why anyone would use aov for this model.
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Spencer Graves
Sent: Thursday, November 16, 2006 4:14 PM
To: Vicki Allison
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] Repeated measures by lme and aov give different results
RSiteSearch("lme and aov") returned 350 hits for me just now. I'm
sure that many are not relevant to your question, but I believe some
are. Beyond this, there is now and R Wiki, accessible via
www.r-project.org -> Documentation: Wiki (or directly as
http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests&s=lme%20and%20
aov).
The first hit in a search there for "lme and aov" "is an edited
transcript of a long thread in R-help starting Sept 7, 2006 from a
comment by Hank Stevens, with Douglas Bates as leading actor."
(http://wiki.r-project.org/rwiki/doku.php?id=guides:lmer-tests&s=lme%20and%2
0aov).
If that fails to answer your questions on this, please submit
another post. Please realize however that the expected number and
quality of replies is inversely proportional to some large power of the
length and complexity of your question.
Hope this helps.
Spencer Graves
Vicki Allison wrote:
> I am analyzing data from an experiment with two factors: Carbon (+/-)
> and O3 (+/-), with 4 replicates of each treatment, and 4 harvests over a
> year. The treatments are assigned in a block design to individual
> Rings.
>
> I have approaches this as a repeated measures design. Fixed factors
> are Carbon, O3 and Harvest, with Ring assigned as a random variable. I
> have performed repeated measures analysis on this data set two different
> ways: one utilizing lme (as described in Crawley, 2002), and the second
> using aov (based on Baron and Li, 2006). Using lme I get very
> conservative p-values, while aov gives me significant p-values,
> consistent with those I obtain performing this analysis in SYSTAT. Can
> anyone explain how these models differ, and which is more appropriate to
> the experimental design I have described? The code I use, and the
> output obtained follow:
>
> 1 lme model
>
> library(nlme)
> M5 <-lme(ln_tot_lgth ~ Carbon*O3*Harv., random = ~-1|Ring)
> anova(M5, type="marginal")
>
> # Output
> numDF denDF F-value p-value
> (Intercept) 144 176.59692 <.0001
> Carbon 112 0.42187 0.5282
> O3 112 0.06507 0.8030
> Harv. 144 17.15861 0.0002
> Carbon:O3 112 0.23747 0.6348
> Carbon:Harv.144 0.85829 0.3593
> O3:Harv.144 0.04524 0.8325
> Carbon:O3:Harv. 144 0.05645 0.8133
>
>> plot(M5)
>>
>
>
> 2 aov model
>
> M6<-aov(ln_tot_lgth ~ O3*Harv.*Carbon + Error (Ring/Carbon+O3))
> summary(M6)
> plot(M6)
>
> # Output
> Error: Ring
> Df Sum Sq Mean Sq F value Pr(>F)
> O3 1 1.76999 1.76999 8.2645 0.01396 *
> Carbon 1 0.64766 0.64766 3.0241 0.10760
> O3:Carbon 1 0.15777 0.15777 0.7366 0.40756
> Residuals 12 2.57002 0.21417
>
> Error: Within
> Df Sum Sq Mean Sq F value Pr(>F)
> Harv.1 33.541 33.541 84.0109 9.14e-12 ***
> O3:Harv. 1 0.001 0.001 0.0036 0.9524
> Harv.:Carbon 1 0.414 0.414 1.0362 0.3143
> O3:Harv.:Carbon 1 0.020 0.020 0.0508 0.8226
> Residuals 44 17.567 0.399
>
>
> *** Note change of location***
>
> Victoria Allison
> Landcare Research
> Private Bag 92170
> Auckland 1142
> New Zealand
> Phone: +64 9 574 4164
>
> WARNING: This email and any attachments may be confidential ...{{dropped}}
>
> __
> R-help@stat.math.ethz.ch 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@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-projec
Re: [R] multiple plots in the same graph
Li, What type of plot? A profile plot would be interaction.plot(factor1,factor2,y) Jeff -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Li Zhang Sent: Friday, November 03, 2006 9:55 PM To: R-help@stat.math.ethz.ch Subject: [R] multiple plots in the same graph I'd like to plot y vs x according to the third variable "group" which has three levels. I am wondering how can I put the three plots in one graph? Thank you (http://groups.yahoo.com) __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] plotting residuals
Does anyone know how to obtain a plot of residuals by predicted values for a main-effects aov? I want to check that the residuals are distributed equally across treatment means. Thanks, Jeff [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] getMethod(s) and var.test
Dimitris, I like your version better than the one-line commands such as methods(). It appears that your version gives ALL of the code. Jeff -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Dimitris Rizopoulos Sent: Tuesday, October 31, 2006 11:12 AM To: Benjamin Otto Cc: r-help@stat.math.ethz.ch Subject: Re: [R] getMethod(s) and var.test you may try something like this: body.fun <- lapply(methods(var.test), get, envir = environment(var.test), mode = "function") names(body.fun) <- methods(var.test) body.fun I hope it helps. Best, Dimitris Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/(0)16/336899 Fax: +32/(0)16/337015 Web: http://med.kuleuven.be/biostat/ http://www.student.kuleuven.be/~m0390867/dimitris.htm - Original Message - From: "Benjamin Otto" <[EMAIL PROTECTED]> To: "R-Help" Sent: Tuesday, October 31, 2006 4:15 PM Subject: [R] getMethod(s) and var.test > Hi, > > > > How do I retrieve the var.test() function code? I had a similar > problem once > before with another function but getMethods() solved the problem > then. Now I > tried several combinations for var.test() without success. > > > > Regards > > > > benjamin > > > > -- > Benjamin Otto > Universitaetsklinikum Eppendorf Hamburg > Institut fuer Klinische Chemie > Martinistrasse 52 > 20246 Hamburg > > > > > [[alternative HTML version deleted]] > > __ > R-help@stat.math.ethz.ch 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. > Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] getMethod(s) and var.test
I have found that you need this to see the stats package code getAnywhere(var.test.default) Jeff -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Benjamin Otto Sent: Tuesday, October 31, 2006 10:15 AM To: R-Help Subject: [R] getMethod(s) and var.test Hi, How do I retrieve the var.test() function code? I had a similar problem once before with another function but getMethods() solved the problem then. Now I tried several combinations for var.test() without success. Regards benjamin -- Benjamin Otto Universitaetsklinikum Eppendorf Hamburg Institut fuer Klinische Chemie Martinistrasse 52 20246 Hamburg [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] getMethod(s) and var.test
On second thought, sometimes you need the .default (as in your case and for
t.test) but not always...for aov you just need getAnywhere(aov)
Not sure why...
It seems the best choices to get package code are
1. body()
2. methods()
3. methods("packagename","default")
4. methods("packagename","mod")
5. getAnywhere(packagename)
6. getAnywhere(packagename.default)
Jeff
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Benjamin Otto
Sent: Tuesday, October 31, 2006 10:15 AM
To: R-Help
Subject: [R] getMethod(s) and var.test
Hi,
How do I retrieve the var.test() function code? I had a similar problem once
before with another function but getMethods() solved the problem then. Now I
tried several combinations for var.test() without success.
Regards
benjamin
--
Benjamin Otto
Universitaetsklinikum Eppendorf Hamburg
Institut fuer Klinische Chemie
Martinistrasse 52
20246 Hamburg
[[alternative HTML version deleted]]
__
R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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] standardized coefficients in lda
Does anyone know if the discriminant coefficients in lda are standardized? Thanks, Jeff [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] disaggregating table
Hi all, This should be easy, but I can't seem to figure it out. I have a table like this named newtable a1 a2 a3 a4 Cnts Score 1 100 4 3.28 1 011 2 2.63 I want the following: a1 a2 a3 a4 Cnts Score 1 100 4 3.28 1 100 4 3.28 1 100 4 3.28 1 100 4 3.28 1 011 2 2.63 1 011 2 2.63 Actually, the Cnts column could be removed, but it doesn't matter if it stays. Anyone know how to disaggregate with Cnts as the index? Thanks, Jeff [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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] superimposing histograms con't
I was just thinking about this last night. I would like to do the same but WITH overlapping. For example, I graph 2 sets of count data. Say the bars for the 1`s overlap...I would like to show that with a different shading for the group that has the higher frequency. For example, it could be black up to a frequency of 5 followed by diagonal-dashes from 5-7 representing the higher frequency of a second group. Thank you, Jeff Miller -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Bill Shipley Sent: Wednesday, June 28, 2006 3:54 PM To: R help list Subject: [R] superimposing histograms con't Earlier, I posted the following question: I want to superimpose histograms from three populations onto the same graph, changing the shading of the bars for each population. After consulting the help files and the archives I cannot find out how to do this (seemly) simple graph. To be clear, I want - a single x axis (from -3 to 18) - three groups of bars forming the histograms of each population (they will not overlap much, but this is a detail) - the bars from each histogram having different shadings or other visually distinguishing features. Gabor Grothendieck [EMAIL PROTECTED] pointed to some code to to this but I have found another way that works even easier. hist(x[sel1],xlim=c(a,b),ylim=c(A,B)) - this plots the histogram for the first group (indexed by sel1) but with an x axis and a y axis that spans the entire range. par(new=T) - to keep on the same graph hist(x[sel2],main=Null,xlab=NULL,ylab=NULL,axes=F) -superimposes the second histogram par(new=T) - to keep on the same graph hist(x[sel3],main=Null,xlab=NULL,ylab=NULL,axes=F) -superimposes the third histogram Bill Shipley North American Editor, Annals of Botany Editor, "Population and Community Biology" series, Springer Publishing Dipartement de biologie, Universiti de Sherbrooke, Sherbrooke (Quibec) J1K 2R1 CANADA [EMAIL PROTECTED] http://callisto.si.usherb.ca:8080/bshipley/ [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] hurdle and zip model
This is more of a stats question, but since I'm using R. Can someone tell me if the standard errors produced by hurdle(), zicounts(), poisson, and the negative binomial formulations of three are directly comparable? Why or why not? Thank you, Jeff [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] storing/retrieving simulation data
Hi all, Would someone please provide efficient code for sending Monte Carlo simulation results and/or graphs run by run to an output file. This is followed by pulling the file back in for subsequent analyses. This is probably topic-specific, so here is a basic example. Suppose I want to examine R2 in multiple regression given X1 and X2. I set the 2 betas and run 10,000 simulations of N=500. This is done separately for 3 different correlations between X1 and X2 and for 2 distributions. Each of the 6 sets of results should be stored separately. I then want to pull in the 6 files to compare R2 between them. What is the most efficient way to export and then import the results? I was using SAS but got tired of the DATA/PROC step problems, and I hear that R is simpler to implement. Thanks in advance, Jeff Miller [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] variance specification using glm and quasi
Hi all, Cameron and Trivedi in their 1998 Regression Analysis of Count Data refer to NB1 and NB2 NB1 is the negative binomial model with variance = mu + (alpha * mu^1) yielding (1+alpha)*mu NB2 sets the power to 2; hence, variance = mu + (alpha*mu^2) I think that NB2 can be requested via negbin2<-glm(hhm~sex+age,family=quasi(var="mu^2",link="log")) Is that right? If so, how I can get NB1? The quasi family appears to be very limited in variance specification options. Thanks, Jeff [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] zero-inflated mixed models
Does anyone know of an existing R package or code to run a mixed Hurdle model? I found glmmADMB, but that seems to be ZIP. Any recommendations? Thanks, Jeff [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
