Displaying 20 results from an estimated 2000 matches similar to: "Problem: Update of glm-object cannot find where the data object is located"
2012 May 28
0
GLMNET AUC vs. MSE
Hello -
I am using glmnet to generate a model for multiple cohorts i. For each i, I
run 5 separate models, each with a different x variable. I want to compare
the fit statistic for each i and x combination.
When I use auc, the output is in some cases is < .5 (.49). In addition, if
I compare mean MSE (with upper and lower bounds) ... there is no difference
across my various x variables, but
2009 Feb 12
0
Comparing slopes in two linear models
Hi everyone,
I have a data frame (d), wich has the results of mosquitoes trapping in
three different places.
I suspect that one of these places (Local=='Palm') is biased by low
numbers and will yield slower slopes in the variance-mean regression over
the areas. I wonder if these slopes are diferents.
I've looked trought the support list for methods for comparing slopes and
found the
2011 Mar 25
2
A question on glmnet analysis
Hi,
I am trying to do logistic regression for data of 104 patients, which
have one outcome (yes or no) and 15 variables (9 categorical factors
[yes or no] and 6 continuous variables). Number of yes outcome is 25.
Twenty-five events and 15 variables mean events per variable is much
less than 10. Therefore, I tried to analyze the data with penalized
regression method. I would like please some of the
2008 Jan 05
1
Likelihood ratio test for proportional odds logistic regression
Hi,
I want to do a global likelihood ratio test for the proportional odds
logistic regression model and am unsure how to go about it. I am using
the polr() function in library(MASS).
1. Is the p-value from the likelihood ratio test obtained by
anova(fit1,fit2), where fit1 is the polr model with only the intercept
and fit2 is the full polr model (refer to example below)? So in the
case of the
2020 Sep 30
0
2 KM curves on the same plot
Hi John,
Brilliant solution and the best sort - when you finally solve your
problem by yourself.
Jim
On Thu, Oct 1, 2020 at 2:52 AM array chip <arrayprofile at yahoo.com> wrote:
>
> Hi Jim,
>
> I found out why clip() does not work with lines(survfit.object)!
>
> If you look at code of function survival:::lines.survfit, in th middle of the code:
>
> do.clip <-
2017 Dec 20
1
Nonlinear regression
You also need to reply-all so the mailing list stays in the loop.
--
Sent from my phone. Please excuse my brevity.
On December 19, 2017 4:00:29 PM PST, Timothy Axberg <axbergtimothy at gmail.com> wrote:
>Sorry about that. Here is the code typed directly on the email.
>
>qe = (Qmax * Kl * ce) / (1 + Kl * ce)
>
>##The data
>ce <- c(15.17, 42.15, 69.12, 237.7, 419.77)
2004 Jun 11
1
comparing regression slopes
Dear List,
I used rlm to calculate two regression models for two data sets (rlm
due to two outlying values in one of the data sets). Now I want to
compare the two regression slopes. I came across some R-code of Spencer
Graves in reply to a similar problem:
http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg06666.html
The code was:
> df1 <- data.frame(x=1:10, y=1:10+rnorm(10))
2017 Dec 20
0
Nonlinear regression
Should I repost the question with reply-all?
On Tue, Dec 19, 2017 at 6:13 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us>
wrote:
> You also need to reply-all so the mailing list stays in the loop.
> --
> Sent from my phone. Please excuse my brevity.
>
> On December 19, 2017 4:00:29 PM PST, Timothy Axberg <
> axbergtimothy at gmail.com> wrote:
> >Sorry about
2011 Oct 06
1
anova.rq {quantreg) - Why do different level of nesting changes the P values?!
Hello dear R help members.
I am trying to understand the anova.rq, and I am finding something which I
can not explain (is it a bug?!):
The example is for when we have 3 nested models. I run the anova once on
the two models, and again on the three models. I expect that the p.value
for the comparison of model 1 and model 2 would remain the same, whether or
not I add a third model to be compared
2009 Jul 28
2
A hiccup when using anova on gam() fits.
I stumbled across a mild glitch when trying to compare the
result of gam() fitting with the result of lm() fitting.
The following code demonstrates the problem:
library(gam)
x <- rep(1:10,10)
set.seed(42)
y <- rnorm(100)
fit1 <- lm(y~x)
fit2 <- gam(y~lo(x))
fit3 <- lm(y~factor(x))
print(anova(fit1,fit2)) # No worries.
print(anova(fit1,fit3)) # Likewise.
print(anova(fit2,fit3)) #
2003 Dec 30
1
odd results from polr vs wilcoxon test
Dear R helpers,
I would like to ask why polr occasionally generates results that look very
odd.
I have been trying to compare the power of proportional odds logistic
regression with
the Wilcoxon test. I generated random samples, applied both tests and
extracted and
compared the p-values, thus:-
library(MASS)
c1=rep(NA,100); c2=c1
for (run in 1:100)
{
dat=c(rbinom(20,12,0.65),rbinom(20,12,0.35))
2010 Sep 21
1
package gbm, predict.gbm with offset
Dear all,
the help file for predict.gbm states that "The predictions from gbm do not
include the offset term. The user may add the value of the offset to the
predicted value if desired." I am just not sure how exactly, especially for
a Poisson model, where I believe the offset is multiplicative ?
For example:
library(MASS)
fit1 <- glm(Claims ~ District + Group + Age +
2005 Jun 15
1
anova.lme error
Hi,
I am working with R version 2.1.0, and I seem to have run into what looks
like a bug. I get the same error message when I run R on Windows as well as
when I run it on Linux.
When I call anova to do a LR test from inside a function, I get an error.
The same call works outside of a function. It appears to not find the right
environment when called from inside a function. I have provided
2004 Dec 21
0
Fwd: problems with limma
On Wed, December 22, 2004 12:11 am, r.ghezzo at staff.mcgill.ca said:
> ----- Forwarded message from r.ghezzo at staff.mcgill.ca -----
> Date: Mon, 20 Dec 2004 15:45:11 -0500
> From: r.ghezzo at staff.mcgill.ca
> Reply-To: r.ghezzo at staff.mcgill.ca
> Subject: [R] problems with limma
> To: r-help at stat.math.ethz.ch
>
> I try to send this message To Gordon
2011 Jan 05
1
Comparing fitting models
Dear all,
I have 3 models (from simple to complex) and I want to compare them in order to
see if they fit equally well or not.
From the R prompt I am not able to see where I can get this information.
Let´s do an example:
fit1<- lm(response ~ stimulus + condition + stimulus:condition, data=scrd)
#EQUIVALE A lm(response ~ stimulus*condition, data=scrd)
fit2<- lm(response ~ stimulus +
2013 Apr 22
0
Copula fitMdvc:
Hello,
I am trying to do a fit a loglikelihood function with Multivariate
distribution via copulas with fitMdvc. The problem is that it
doesn't recognize that my beta is a vector of km parameter and when I try
to run it it say that the length of my initial values is not the same as
the parameter.
Can somebody guide me where my mistake is.
Thanks,
Elisa.
#################################
2010 Mar 17
1
accessing info in object slots from listed objects using loops
Hey,
I have stacked a couple of garchFit objects in a list with names $fit1,
$fit2, ..., $fiti assigning objects names using a loop, i.e. after running
the loop modelStack = list($fit1, $fit2,...,$fiti).
Thus the following apply;
a = modelStack$fit2, then a is the second garchFit object of formal class
'fGarch' with 11 slots, @call, @formula... etc.
I then want to extract information in
2018 Jan 17
1
Assessing calibration of Cox model with time-dependent coefficients
I am trying to find methods for testing and visualizing calibration to Cox
models with time-depended coefficients. I have read this nice article
<http://journals.sagepub.com/doi/10.1177/0962280213497434>. In this paper,
we can fit three models:
fit0 <- coxph(Surv(futime, status) ~ x1 + x2 + x3, data = data0) p <-
log(predict(fit0, newdata = data1, type = "expected")) lp
2007 Jun 21
1
Result depends on order of factors in unbalanced designs (lme, anova)?
Dear R-Community!
For example I have a study with 4 treatment groups (10 subjects per group) and 4 visits. Additionally, the gender is taken into account. I think - and hope this is a goog idea (!) - this data can be analysed using lme as below.
In a balanced design everything is fine, but in an unbalanced design there are differences depending on fitting y~visit*treat*gender or
2004 Dec 20
2
problems with limma
I try to send this message To Gordon Smyth at smyth at vehi,edu.au but it bounced
back, so here it is to r-help
I am trying to use limma, just downloaded it from CRAN. I use R 2.0.1 on Win XP
see the following:
> library(RODBC)
> chan1 <- odbcConnectExcel("D:/Data/mgc/Chips/Chips4.xls")
> dd <- sqlFetch(chan1,"Raw") # all data 12000
> #
> nzw <-