[R] Invito a collegarsi su LinkedIn
Vorrei aggiungerti alla mia rete professionale su LinkedIn. -giovanni giovanni parrinello Senior Statistical Consultant at University of Brescia Italy Confirm that you know giovanni parrinello: https://www.linkedin.com/e/-92ffr2-gvmdq8pr-1/isd/5085379353/o5O4tnc8/?hs=falsetok=0BYzKxkO2MnB01 -- You are receiving Invitation to Connect emails. Click to unsubscribe: http://www.linkedin.com/e/-92ffr2-gvmdq8pr-1/vxMuFwS2PpRnFjm0VsifityWSt9K_bXjxepMJ1/goo/R-help%40stat%2Emath%2Eethz%2Ech/20061/I1773723218_1/?hs=falsetok=0xPSvS6c2MnB01 (c) 2011 LinkedIn Corporation. 2029 Stierlin Ct, Mountain View, CA 94043, USA. [[alternative HTML version deleted]] __ 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] problems with randomSurvivalForest
summary(ma.dati2$death.status)- censoring Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.0 0.0 0.0 0.05332 0.0 1.0 39.0 ## summary(ma.dati2$time.death)--- time Min. 1st Qu. MedianMean 3rd Qu.Max.NA's 1 370 370 356 370 370 39 formula timi.out - rsf(Survrsf(time.death,death.status)~sex, ma.dati2.rid, ntree = 1000,na.action='na.omit') Errore in rsf.default(Survrsf(time.death, death.status) ~ sex, ma.dati2.rid[, : Outcome is not a random survival object. Use 'Survrsf' for the formula. But time.death is strictly positivi and death.status assume only two value:,0,1. Where is the error??? TIA Giovanni [[alternative HTML version deleted]] __ 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] Solved problems with randomSurvivalForest
Only a confusion with two dataset with similar names... Sorry Giovanni [[alternative HTML version deleted]] __ 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] problems with Sweave and the function latex(HMISC)
latex(s6a2,title=,caption=Baseline vs zonr,file=,label=Base,long=TRUE,landscape=F, middle.bold=TRUE,here=T, + ,size=smaller[5],outer.size=smaller,Nsize=smaller,midsize=smaller) latex is not reconized \as a internalor external command , un programma eseguibile o un file batch. Warning message: In shell(cmd, wait = TRUE, intern = output) : 'cd C:\DOCUME~1\giovanni\IMPOST~1\Temp\RtmpgUEV1B latex -interaction=scrollmode C:\DOCUME~1\giovanni\IMPOST~1\Temp\RtmpgUEV1B\file6df11649' execution failed with error code 1 TIA GIOVanni str(s6a2) List of 14 $ stats :List of 1 Sys.info() sysname release version Windows XP build 2600, Service Pack 3 nodename machinelogin PC43 x86 giovanni user giovanni [1] .GlobalEnv.GlobalTemp package:Hmisc package:tools [5] package:stats package:graphics package:grDevices package:utils [9] package:datasets package:methods Autoloads package:base R version 2.7.2 -- dr. Giovanni Parrinello Department of Biotecnologies Medical Statistics Unit University of Brescia Viale Europa, 11 25123 Brescia email: parri...@med.unibs.it Phone: +390303717528 Fax: +390303717488 __ 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] error message of RODBC...
channel - odbcConnectExcel(nuova tabella terapia occupazionale mod.xls) ## list the spreadsheets sqlTables(channel) TABLE_CAT TABLE_SCHEM TABLE_NAME 1 c:\\TABELLE DEFINITIVE\\nuova tabella terapia occupazionale mod NA 'emi tot 2006 OAI_60g TO FU1$' 2 c:\\TABELLE DEFINITIVE\\nuova tabella terapia occupazionale mod NA 'emi tot 2006 OAI_60g TO FU2$' 3 c:\\TABELLE DEFINITIVE\\nuova tabella terapia occupazionale mod NA 'emi tot 2006 OAI_60GG divisi$' 4 c:\\TABELLE DEFINITIVE\\nuova tabella terapia occupazionale mod NA 'emi tot 2006$' 5 c:\\TABELLE DEFINITIVE\\nuova tabella terapia occupazionale mod NA'RMI E SCALA SPECIFICA$' 6 c:\\TABELLE DEFINITIVE\\nuova tabella terapia occupazionale mod NA'VALORI RANKIN RMI CSS$' TABLE_TYPE REMARKS 1 TABLENA 2 TABLENA 3 TABLENA 4 TABLENA 5 TABLENA 6 TABLENA table1=sqlFetch(channel,emi tot 2006 OAI_60g TO FU1$) str(table1) chr [1:2] [RODBC] ERROR: Could not SQLExecDirect(?) ... sqlTables(channel) [[alternative HTML version deleted]] __ 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] Orthogonal polynomials and poly
Dear All, I have found in the poly help this sentence: The orthogonal polynomial is summarized by the coefficients, which can be used to evaluate it via the three-term recursion given in Kennedy Gentle (1980, pp. 3434), and used in the predict part of the code. My question: which type of orthogonal polynomials are used by this function? Hrmite, legendre.. TIA Giovanni [[alternative HTML version deleted]] __ 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] Left censored responses in mixed effects models
Dear Bert, a solution is the 'package' censre3 by Hughes JP Reference: Hughes JP: Mixed effects models with censored data with application to HIV RNA levels. Biometrics, 55:625-629, 1999. Giovanni Don MacQueen ha scritto: I assume you've looked at the NADA package(?) While I don't believe it goes as far as dealing the mixed effects models, it might give you a starting point, and possibly some additional references. -Don At 9:08 AM -0700 5/12/08, Bert Gunter wrote: Dear R Fellow-Travellers: What is your recommended way of dealing with a left-censored response (non-detects) in (linear Gaussian) mixed effects models? Specifics: Response is a numeric positive measurement (of volume, actually); but when it falls below some unknown and slightly random value (depending on how the sample is prepared and measured), it cannot be measured and is recorded as 0. There is some statistical literature on this, but I was unable to find anything that appeared to me to implement a strategy in any R package. If it matters, I am less interested in inference than in removing possible bias in estimation. Feel free to respond off-list if you feel that this would not be of general interest. Cheers, Bert Gunter Genentech __ 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. -- dr. Giovanni Parrinello Department of Biotecnologies Medical Statistics Unit University of Brescia Viale Europa, 11 25123 Brescia email: [EMAIL PROTECTED] Phone: +390303717528 Fax: +390303717488 __ 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] Left censored responses in mixed effects models(II)
Dear Bert, you can also translate in nlme, as I'm trying to do, the approach of Thiébaut and *Gadda( *Mixed models for longitudinal left-censored repeated measures. Computer Methods and Programs in Biomedicine 74 http://www.informatik.uni-trier.de/%7Eley/db/journals/cmpb/cmpb74.html#ThiebautJ04(3): javascript:void(0)(2004)) written in nlmixed(SAS) Giovanni Bert Gunter ha scritto: Dear R Fellow-Travellers: What is your recommended way of dealing with a left-censored response (non-detects) in (linear Gaussian) mixed effects models? Specifics: Response is a numeric positive measurement (of volume, actually); but when it falls below some unknown and slightly random value (depending on how the sample is prepared and measured), it cannot be measured and is recorded as 0. There is some statistical literature on this, but I was unable to find anything that appeared to me to implement a strategy in any R package. If it matters, I am less interested in inference than in removing possible bias in estimation. Feel free to respond off-list if you feel that this would not be of general interest. Cheers, Bert Gunter Genentech __ 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. -- dr. Giovanni Parrinello Department of Biotecnologies Medical Statistics Unit University of Brescia Viale Europa, 11 25123 Brescia email: [EMAIL PROTECTED] Phone: +390303717528 Fax: +390303717488 __ 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] Translating NLMIXED in nlme
Dear All, reading an article by Rodolphe Thiebaut and Helene Jacqmin-Gadda (Mixed models for longitudinal left-censored repeated measures) I have found this program in SAS proc nlmixed data=TEST QTOL=1E-6; parms sigsq1=0.44 ro=0.09 sigsq2=0.07 sigsqe=0.18 alpha=3.08 beta=0.43; bounds $B!](B1 ro 1, sigsq1 sigsq2 sigsqe = 0; pi=2*arsin(1); mu=alpha+beta*TIME+a i+b i*TIME; if OBS=1 then ll=(1/(sqrt(2*pi*sigsqe)))*exp(-(RESPONSE-mu)**2/(2*sigsqe)); if OBS=0 then ll=probnorm((RESPONSE-mu)/sqrt(sigsqe)); L=log(ll); ... I haven't found a simple solution for the conditional LL: if OBS=1 then ll=(1/(sqrt(2*pi*sigsqe)))*exp(-(RESPONSE-mu)**2/(2*sigsqe)); if OBS=0 then ll=probnorm((RESPONSE-mu)/sqrt(sigsqe)); using nlme. Any suggestion will be appreciated. Giovanni sessionInfo() R version 2.6.2 (2008-02-08) i386-pc-mingw32 locale: LC_COLLATE=Italian_Italy.1252;LC_CTYPE=Italian_Italy.1252;LC_MONETARY=Italian_Italy.1252;LC_NUMERIC=C;LC_TIME=Italian_Italy.1252 attached base packages: [1] splines tools stats graphics grDevices utils datasets methods base other attached packages: [1] JM_0.1-0MASS_7.2-41 Design_2.1-1survival_2.34-1 nlme_3.1-88 [6] Hmisc_3.4-3 loaded via a namespace (and not attached): [1] cluster_1.11.10 grid_2.6.2 lattice_0.17-6 [[alternative HTML version deleted]] __ 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.
