Displaying 20 results from an estimated 100 matches similar to: "Mitools and lmer"
2010 Nov 07
2
How is MissInfo calculated? (mitools)
What does missInfo compute and how is it computed?
There is only 1 observation missing the ethnic3 variable. There is no other
missing data.
N=1409
> summary(MIcombine(mod1))
Multiple imputation results:
with(rt.imp, glm(G1 ~ stdage + female + as.factor(ethnic3) + u,
family = binomial()))
MIcombine.default(mod1)
results se
(lower upper)
2010 Jun 30
3
Logistic regression with multiple imputation
Hi,
I am a long time SPSS user but new to R, so please bear with me if my
questions seem to be too basic for you guys.
I am trying to figure out how to analyze survey data using logistic
regression with multiple imputation.
I have a survey data of about 200,000 cases and I am trying to predict the
odds ratio of a dependent variable using 6 categorical independent variables
(dummy-coded).
2007 May 31
0
Using MIcombine for coxph fits
R-helpers:
I am using R 2.5 on Windows XP, packages all up to date. I have run
into an issue with the MIcombine function of the mitools package that I
hoped some of you might be able to help with. I will work through a
reproducible example to demonstrate the issue.
First, make a dataset from the pbc dataset in the survival package
---------------
# Make a dataset
library(survival)
d <-
2009 Feb 24
1
Initialize varFunc in R
Hi,
I am running R2.8.1 under Linux, and I am having trouble using the
variance functions in nlme
My basic model was something like:
model0 <- lme( log(growth) ~ light * species.group , data=data,
random=~light|species ) # with 20 odd species divided in 2 groups
Following the methods in Pinheiro&Bates I tried to put a variance
function in the model:
model1 <- update(model0,
2007 Jun 07
1
MITOOLS: Error in eval(expr, envir, enclos) : invalid 'envir' argument
R-users & helpers:
I am using Amelia, mitools and cmprsk to fit cumulative incidence curves
to multiply imputed datasets. The error message that I get
"Error in eval(expr, envir, enclos) : invalid 'envir' argument"
occurs when I try to fit models to the 50 imputed datasets using the
"with.imputationList" function of mitools. The problem seems to occur
2007 Aug 15
0
mitools and plm packages
Hi all,
I am trying to use the functions in the plm package with multiply
imputed datasets. I had tried to combine the datasets using the
imputationList() function of mitools. plm, however, requires a data
argument, and I don't know where to point it to. I'd appreciate any
help people might have.
A (possible) fuller description of the problem and code is in a
previous
2004 Oct 11
3
logistic regression
Hello,
I have a problem concerning logistic regressions. When I add a quadratic
term to my linear model, I cannot draw the line through my scatterplot
anymore, which is no problem without the quadratic term.
In this example my binary response variable is "incidence", the explanatory
variable is "sun":
> model0<-glm(incidence~1,binomial)
>
2010 Aug 27
1
step
Hi,
how can I change the significance level in test F to select
variable in step command?
I used
step(model0, ~x1+x2+x3+x4, direction=c("forward"), test='F',
alpha=.05)
but it does't work.
--------------------------------------
Silvano Cesar da Costa
Departamento de Estat?stica
Universidade Estadual de Londrina
Fone: 3371-4346
2005 Jun 15
1
Kalman Filtering?
1. The function "KalmanLike" seems to change its inputs AND
PREVIOUSLY MADE copies of the inputs. Consider the following (using R
2.1.0 patched under Windows XP):
> Fig2.1 <- StructTS(x=Nile, type="level")
> unlist(Fig2.1$model0[2:3])
a P
1120 286379470
> tst2 <- tst <- Fig2.1$model0
> tst23 <- tst[2:3]
> tst23u <-
2006 Oct 14
1
mitools, multiple imputation
R 2.2.0
windows XP
I am beginning to explore the mitools package contributed by Thomas
Lumley (thank you Thomas) and I have a few questions:
(1) In the examples given in the mitools documentation, the only family
argument used is family=binomial. Does the package support
family=gaussian and other link functions? I ran the with function with
family=gaussian and I obtained results, but I am not
2011 Dec 13
8
How to compute 95%CI for OR from logistic regression?
Hi all:
My data has 3 variables:
age(3levels : <30y=1 30-50y=2, >50y=3)
gender(Male=0, Female=1)
CD4 cell count(raw lab measurement)
y(1:death 0:alive)
I perform logistic regression to find out the factors that influence y.
result<-glm(y ~ factor(age) + factor(gender) + CD4,family = binomial)
>From the result,I can get OR(Odds Ratio) of gender via exp(Estimate of Female,
2008 May 28
1
manipulating multiply imputed data sets
Hi folks,
I have five imputed data sets and would like to apply the same
recoding routines to each. I could do this sort of thing pretty
easily in Stata using MIM, but I've decided to go cold turkey on other
stats packages as a incentive for learning more about R. Most of the
recoding is for nominal variables, like race, religion, urbanicity,
and the like. So, for example, to recode race
2003 Oct 23
1
Can you create a MySQL database with RMySQL?
Is it possible to create a database in MySQL via RMySQL?
Also, is the format for the authorization field
'userName/password at databasename'? I saw an example like this somewhere
in the documenation, but I haven't found the actual specification.
Thanks,
Barnet Wagman
2010 Jun 29
3
mixed-effects model with two fixed effects: interaction
Dear all,
In a greenhouse experiment we tested performance of 4 different species (B,H,P,R) under 3 different water levels in 10 replications. As response variable e.g. the number of emerging sprouts were measured on three dates. A simple Anova considering every measurement date separately shows a higly significant effect of species and moisture (and partly the interaction of both). The
2007 Aug 14
0
Panel data and imputed datasets
Hi all,
I am hardly an expert, so I expect that this code is not the easiest/
most efficient way of getting where I want. Any suggestions in that
direction would also be helpful.
I am working on panel analysis with five imputed datasets, generated
by Amelia. To do panel analysis, it seemed that the plm package was
the best, providing a convenient wrapper for fixed and random effects
2011 Jun 30
1
Analysing insecticide biossays using lmer
Hi all,
Here is my problem: I performed bioassays using a unique insecticide on 9
different genotypes and got their mortality depending on the dose of
insecticide used.
Now, I want to see wether some genotypes are different or not in their
responses to insecticide.
My problem is that I have up to four replicates for some genotypes, but only
one for other... Due to this unbalanced design, I
2010 Mar 26
1
Linear mixed models with custom link functions in R
Hello All,
I am looking for an R library/function that allows the specification
of a custom link function in a linear mixed model. I've been using
glm() in library MASS to fit fixed-effect models with a custom link but
my study design demands mixed models. Any suggestions on the best R
library/function to achieve this would be greatly appreciated. I have
tried, to no avail, to
2011 May 16
2
Post-hoc tests in MASS using glm.nb
I am struggling to generate p values for comparisons of levels (post-hoc
tests) in a glm with a negative binomial distribution
I am trying to compare cell counts on different days as grown on different
media (e.g. types of cryogel) so I have 2 explanatory variables (Day and
Cryogel), which are both factors, and an over-dispersed count variable
(number of cells) as the response. I know that both
2009 Jan 22
1
Is there any function can be used to compare two probit models made from same data?
hi, people
How can we compare two probit models brought out from the same data?
Let me use the example used in "An Introduction to R".
"Consider a small, artificial example, from Silvey (1970).
On the Aegean island of Kalythos the male inhabitants suffer from a
congenital eye disease, the effects of which become more marked with
increasing age. Samples of islander males
2008 May 30
0
imputationlist, update, and recode
I'm stumbling my way through manipulating data in multiply imputed datasets,
and have run into a problem translating code I used to run on my pre-imputed
dataset to multiple datasets. The imputation runs just fine, as does the
reading of the mi data sets into an imputationList. I run into trouble,
though, when I try to construct a scale across all the data sets. Is there
a simple way to do