similar to: 6315567 gcc still does not like biosint despite recent gifts

Author: eota Repository: /hg/zfs-crypto/gate Revision: 50021b84343742e322d24ce75d5cf4b26369fd38 Log message: 6310483 boot needs some more help for gcc on SPARC Files: create: usr/src/psm/stand/boot/sparc/common/util.h update: usr/src/psm/promif/ieee1275/common/prom_node.c update: usr/src/psm/promif/ieee1275/common/prom_test.c update: usr/src/psm/stand/boot/common/readfile.c update:

Author: setje Repository: /hg/zfs-crypto/gate Revision: bb9f8eccd7d8aef91c3bf4f6b393f812a8d0ce16 Log message: 6362643 GRUB graphics still not in line with unified "coolstart" branding 6363028 progress indicator needs to move and turn green to accommodate "coolstart" branding 6363031 boot progress graphics need to be updated with unified "coolstart" branding 6372042

I am using psm to model some parametric survival data, the data is for length of stay in an emergency department. There are several ways a patient's stay in the emergency department can end (discharge, admit, etc..) so I am looking at modeling the effects of several covariates on the various outcomes. Initially I am trying to fit a survival model for each type of outcome using the psm

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Does Surv in psm handle interval2 data? The argument list seems to indicate it does but I get an error. Thanks, Chris # code library('survival') left <- c(1, 3, 5, NA) right <-c(2, 3, NA, 4) Surv(left, right, type='interval2') survreg(Surv(left, right, type='interval2') ~ 1) library('rms') Surv(left, right, type='interval2') # error args(Surv)

Full_Name: Oleg Raisky Version: 1.8.1 OS: Windows 2000 Submission from: (NULL) (63.246.203.107) This is a completely fresh R install. I'm trying to use Design package. Every time I run the first example for psm() I'm getting an error <<couldn't find function "survreg.fit">>. However, survreg.fit does exists in the search path. Is there something I can do to fix

Hola chic en s, alguien con experiencia en propensión score matching? Planteo duda: Clasicamente el PSM se ha utilizado en un intento de homogeneizar cohortes de enfermos quienes han estado ?expuestos? a un tratamiento x Vs aquellos que no han estado expuestos (no expuestos). Esto aplica para medicamentos o procedimientos quirúrgicos o no. Bien, En algún articulo he leído que el PSM se puede

Has anyone here managed to send files from a mobile phone to a CentOS system via Bluetooth? I'm trying with a Samsung E1310, using the GNOME tools, but can't get it to work. I can send files from the Linux box to this phone using the Nautilus bluetooth plugin (nautilus-sendto-bluetooth), and have also managed to "pull" some data I've been trying to send, via

Hola chic en s, alguien con experiencia en propensión score matching? Planteo duda: Clasicamente el PSM se ha utilizado en un intento de homogeneizar cohortes de enfermos quienes han estado ?expuestos? a un tratamiento x Vs aquellos que no han estado expuestos (no expuestos). Esto aplica para medicamentos o procedimientos quirúrgicos o no. Bien, En algún articulo he leído que el PSM se puede

I am cleaning up the rms package to not export functions not to be called directly by users. rms uses generic functions defined in other packages. For example there is a latex method in the Hmisc package, and rms has a latex method for objects of class "anova.rms" so there are anova.rms and latex.anova.rms functions in rms. I use:

While sm4.6ll<-fit.mult.impute(Surv(agesi, si)~partner+ in.love+ pubty+ FPA+ strat(gender),fitter = cph, xtrans = dated.sexrisk2.i, data = dated.sexrisk2, x=T,y=T,surv=T, time.inc=16) runs perfectly using Hmisc, Design and mice under R11 run via Sciviews-K, with library(Design) library(mice) ds2d<-datadist(dated.sexrisk2) options(datadist="ds2d")

The rms package, a replacement for the Design package, has been updated on CRAN. The most major change is the addition of smooth calibration curves for externally (val.surv function) or internally (calibrate.cph, calibrate.psm) validating a survival model with right-censored data. The polspline package is used to estimate the survival probability at a fixed time point as a function of the

The rms package, a replacement for the Design package, has been updated on CRAN. The most major change is the addition of smooth calibration curves for externally (val.surv function) or internally (calibrate.cph, calibrate.psm) validating a survival model with right-censored data. The polspline package is used to estimate the survival probability at a fixed time point as a function of the

Hi, I've recently installed FreeBSD 6.3, and I've got a problem with synaptics. I've installed it, followed the pkg-message : hw.psm.synaptics_support=1 It works, dmesg gives : psm0: <PS/2 Mouse> irq 12 on atkbdc0 psm0: [GIANT-LOCKED] psm0: model Synaptics Touchpad, device ID 0 moused_enable="NO" ps shows me that moused doesn't run. xorg.conf : InputDevice

Rick Graves wrote: > John, > > I think the error that I encountered earlier this week > was because I am now blocked from accessing the main > CentOS mirror. > > At any rate, today I tried a different mirror, and at > least yum would run. > > I am still on the RH9 X install. > > I tried yum update, and got this: > > Resolving dependencies >

Author: mike_s Repository: /hg/zfs-crypto/gate Revision: 26b4dcfa6ca883a2a536b9452873ec3a59d49d72 Log message: 6325869 master.h grows every time header.sh/Makefile is touched Files: update: usr/src/cmd/wbem/provider/c/filesystems/wbem_nfs/lib/Makefile

Author: mike_s Repository: /hg/zfs-crypto/gate Revision: e144729d8b901f4092085ea17a31bf10d1089f79 Log message: 6273860 gcc and sgs/gprof don''t get along 6273866 gcc and sgs/prof don''t get along Files: update: usr/src/cmd/sgs/gprof/Makefile.com update: usr/src/cmd/sgs/gprof/common/arcs.c update: usr/src/cmd/sgs/gprof/common/dfn.c update: usr/src/cmd/sgs/gprof/common/gprof.c

Author: mike_s Repository: /hg/zfs-crypto/gate Revision: 1e50029b6341eb8c25e8d3feaf0e24f32afe6eba Log message: 6309399 gcc and bofi don''t get along Files: update: usr/src/uts/common/io/bofi.c

Dear All, I would like to fit some parametric survival models using left truncated, right censored data in R. However I am having problems finding a function to fit parametric survival models which can handle left truncated data. I have tested both the survreg function in package survival: fit1 <- survreg(Surv(start, stop, status) ~ X + Y + Z, data=data1) and the psm function in package

I am using psm to fit a survival model with a dataset that has missing values, e.g., DS <-psm(Surv(los,DSCHRG) ~AGE + SEX + ACUITY, data=LOS,dist='weibull',x=TRUE,y=TRUE) and I notice that when I look at the output there are 0 missing values and when I use the summary function e.g., summary(DS) plot(summary(DS)) the missing values are showing up as a category e.g., for Sex F: F:M