Displaying 20 results from an estimated 1000 matches similar to: "bootcov or robcov for odds ratio?"
2011 May 03
0
Bootstrapping confidence intervals
Hi,
Sorry for repeated question.
I performed logistic regression using lrm and penalized it with pentrace
function. I wanted to get confidence intervals of odds ratio of each
predictor and summary(MyModel) gave them. I also tried to get
bootstrapping standard errors in the logistic regression. bootcov
function in rms package provided them. Then, I found that the confidence
intervals provided by
2009 Apr 13
3
Clustered data with Design package--bootcov() vs. robcov()
Hi,
I am trying to figure out exactly what the bootcov() function in the Design
package is doing within the context of clustered data. From reading the
documentation/source code it appears that using bootcov() with the cluster
argument constructs standard errors by resampling whole clusters of
observations with replacement rather than resampling individual
observations. Is that right, and is
2011 May 15
5
Question on approximations of full logistic regression model
Hi,
I am trying to construct a logistic regression model from my data (104
patients and 25 events). I build a full model consisting of five
predictors with the use of penalization by rms package (lrm, pentrace
etc) because of events per variable issue. Then, I tried to approximate
the full model by step-down technique predicting L from all of the
componet variables using ordinary least squares
2009 Jul 24
1
Making rq and bootcov play nice
I have a quick question, and I apologize in advance if, in asking, I
expose my woeful ignorance of R and its packages. I am trying to use
the bootcov function to estimate the standard errors for some
regression quantiles using a cluster bootstrap. However, it seems that
bootcov passes arguments that rq.fit doesn't like, preventing the
command from executing. Here is an example:
2008 Jul 25
1
extracting Pr>ltl from robcov/ols (Design)
I am trying to extract significance levels out of a robcov+ols call.
For background: I am analysing data where multiple measurements(2 per
topic) were taken from individuals(36) on their emotional reaction
(dependent variable) to various topics (3 topics). Because I have
several emotions and a rotation to do on the topics, I'd like to have
the results pumped into a nice table.
2010 Apr 09
0
Bootcov for two stage bootstrap
Dear users,
I'm trying to implement the nonparametric "two-stage" bootstrap (Davison and
Hinkley 1997, pag 100-102) in R. As far as I understood, 'bootcov' is the
most appropriate method to implement NONPARAMETRIC bootstrap in R when you
have clustered data (?). I read the 'bootcov' manual but I still have a few
questions:
1 - When the variable 'cluster' is
2010 Nov 09
1
Bootstrap confidence intervals using bootcov from the rms package
Hello,
I am using R.12.2.0. I am trying to generate bootstrap confidence intervals
using bootcov from the rms package. I am able to impute the missing data
using aregImpute and to perform a linear regression on the imputed datasets
using fit.mult.impute, but I am unable to use bootcov to generate the
confidence intervals for the R-squared. Here is a small example that should
duplicate the
2009 Jul 24
1
Fwd: Making rq and bootcov play nice
John,
You can make a local version of bootcov which either:
deletes these arguments from the call to fitter, or
modify the switch statement to include rq.fit,
the latter would need to also modify rq() to return a fitFunction
component, so the first option is simpler. One of these days I'll
incorporate clustered se's into summary.rq, but meanwhile
this seems to be a good alternative.
2004 Mar 22
2
Handling of NAs in functions lrm and robcov
Hi R-helpers
I have a dataframe DF (lets say with the variables, y, x1, x2, x3, ...,
clust) containing relatively many NAs.
When I fit an ordinal regression model with the function lrm from the
Design library:
model.lrm <- lrm(y ~ x1 + x2, data=DF, x=TRUE, y=TRUE)
it will by default delete missing values in the variables y, x1, x2.
Based on model.lrm, I want to apply the robust covariance
2003 Oct 07
1
Adjusting for within-cluster correlation: robcov() in Design-package and 'ids' in survey-package
Dear all,
I would like to know if it possible to use the the robcov()-command in the Design-
package in order to obtain a robust variance-estimate that adjusts for within-cluster
correlation. Does the ids-option in the survey-package the same job?
TIA,
Bernd
2007 Feb 15
1
bootcov and cph error
Hi all,
I am trying to get bootstrap resampled estimates of covariates in a Cox
model using cph (Design library).
Using the following I get the error:
> ddist2.abr <- datadist(data2.abr)
> options(datadist='ddist2.abr')
> cph1.abr <- cph(Surv(strt3.abr,loc3.abr)~cov.a.abr+cov.b.abr,
data=data2.abr, x=T, y=T)
> boot.cph1 <- bootcov(cph1.abr, B=100, coef.reps=TRUE,
2013 Apr 19
2
NAMESPACE and imports
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:
2003 Apr 24
1
"Missing links": Hmisc and Design docs
Hi folks,
Using R Version 1.6.2 (2003-01-10)
on SuSE Linux 7.2,
I just installed Hmisc_1.5-3.tar.gz and Design_1.1-5.tar.gz
These were taken from
http://hesweb1.med.virginia.edu/biostat/s/library/r
Checked the dependencies:
Hmisc: grid, lattice, mva, acepack -- all already installed
Design: Hmisc, survival -- survival already installed, so
installed Hmisc first
All seems to go
2006 Apr 04
1
F test for clustered data regression ?
I am using the Design library and robcov to compute
variance-covariance matrices for clustered data
regression.
Is there an easy way to compute the F-test (i.e.
linear hypothesis) for clustered data regression ?
Thanks in advance!
Benn
2007 Feb 20
0
Problems with obtaining t-tests of regression coefficients applying consistent standard errors after run 2SLS estimation. Clearer !!!!!
First I have to say I am sorry because I have not been so clear in my
previous e-mails. I will try to explain clearer what it is my problem.
I have the following model:
lnP=Sc+Ag+Ag2+Var+R+D
In this model the variable Sc is endogenous and the rest are all objective
exogenous variables. I verified that Sc is endogenous through a standard
Hausman test. To determine this I defined before a new
2005 Jan 17
2
Omitting constant in ols() from Design
Hi!
I need to run ols regressions with Huber-White sandwich estimators and
the correponding standard errors, without an intercept. What I'm trying
to do is create an ols object and then use the robcov() function, on the
order of:
f <- ols(depvar ~ ind1 + ind2, x=TRUE)
robcov(f)
However, when I go
f <- ols(depvar ~ ind1 + ind2 -1, x=TRUE)
I get the following error:
Error in
2013 Jul 11
0
[R-pkgs] Major Update to rms package
The rms ("Regression Modeling Strategies") package has undergone a
massive update. The entire list of updates is at the bottom of this
note. CRAN has the update for linux and will soon have it for Windows
and Mac - check http://cran.r-project.org/web/packages/rms/ for
availability. This rms update relies on a major update of the Hmisc
package.
The most user-visible changes are:
2009 May 08
2
Probit cluster-robust standard errors
If I wanted to fit a logit model and account for clustering of observations, I would do something like:
library(Design)
f <- lrm(Y1 ~ X1 + X2, x=TRUE, y=TRUE, data=d)
g <- robcov(f, d$st.year)
What would I do if I wanted to do the same thing with a probit model?
?robcov says the input model must come from the Design package, but the Design package appears not to do probit?
Thanks very
2007 Jan 25
1
summary of the effects after logistic regression model
Dear all, my aim is to estimate the efficacy over time of a treatment for
headache prevention. Data consist of long sequences of repeated binary
outcomes (1 if the subject has at least 1 episode of headache , 0
otherwise) on subjects randomized to placebo or treatment.
I have fit a logistic regression model with Huber-White cluster sandwich
covariance estimator.
I have put in the model the
2003 Jan 22
1
Intercept in model formulae
Hi,
I'm a new user of R and I'm trying to make a linear model from this kind of
dataset
x
[1] 16.87 19.93 25.85 20.94 17.06 19.49 19.93 25.45 27.74 20.15 25.81
21.06 17.17 20.03 25.50 27.79 20.44 16.88 19.93 25.79
z<-x-10
y
[1] 0.80 1.27 2.22 1.32 0.90 1.18 1.84 2.41 2.97 1.25 2.07 1.41 1.14 1.66
2.59 3.51 1.53 0.81 1.26 2.30
plot(x,y)
I want to be able to force the line of