Displaying 20 results from an estimated 1000 matches similar to: "Averaging over data sets"
2012 Jan 16
3
Select rows based on multiple comparisons
Dear all,
I have a data set in which the same unit appears 2 or 3 or 4 times. I need
to aggregate this data to maintain only one unit by row. But I need to do
that based on a comparison between the values of such units. I can't find a
function to help me on that. I appreciate any help. Below I provide an
example of what I want:
This is my data:
Units Var1 Var2 Var3
1 B 2
2011 Sep 15
2
Tobit Fixed Effects
Hi there,
I need to run a Tobit Fixed Effects in a panel data with 4500 units for 8
years. It is a huge data set, my dependent variable is left truncated at
zero, the distribution is skewed and my panel is balanced.
Any suggestions on how to do that in R?
I tried stuff like survreg, censReg, and tobit but none of them were
satisfactory.
Thanks,
*Felipe Nunes*
CAPES/Fulbright Fellow
PhD
2010 Dec 22
3
Help with Amelia
Hi
I have used the amelia command from the Amelia R package. this gives me a number
of imputed datasets.
This may be a silly question, but i am not a statistician, but I am not sure how
to combine these results to obtain the imputed dataset to usse for further
statistical analysis. I have looked through the amelia and zelig manuals but
still can not find the answer. This maybe because I dont
2011 Jan 31
2
Rubin's rules of multiple imputation
Hello all, if I have multiple imputed data sets, is there a command or
function in R in any package you know of to combine those, I know one common
MI approach is rubins rules, is there a way to do this using his rules or
others? I know theres ways, like using Amelia from Gary King's website to
create the imputed data sets, but how to make them into one or combine them
for analysis.
2009 Feb 05
3
maptools: Test if point is in polygon
In R's maptools package, is there a built-in function to test if a
given point is "inside" a given polygon on the map? The map was
loaded from an ESRI Shapefile. The point's latitude and longitude are
known.
Thank you!
Aleks
--
------------------------
Aleksandr Andreev
Fulbright Fellow
Graduate School of Management
St Petersburg State University
2009 Apr 24
1
Multiple Imputation in mice/norm
I'm trying to use either mice or norm to perform multiple imputation to fill
in some missing values in my data. The data has some missing values because
of a chemical detection limit (so they are left censored). I'd like to use
MI because I have several variables that are highly correlated. In SAS's
proc MI, there is an option with which you can limit the imputed values that
are
2018 Mar 20
0
Struggling to compute marginal effects !
In that case, I can't work out why the first model fails but not the
second. I would start looking at "Data" to see what it contains. if:
object2 <- polr(Inc ~ Training ,Data,Hess = T,method = "logistic" )
works, the problem may be with the "Adopt" variable.
Jim
On Tue, Mar 20, 2018 at 10:55 AM, Willy Byamungu
<wmulimbi at email.uark.edu> wrote:
>
2012 Jul 21
2
combined EM dataset for missing data?
Hi list,
I am wondering if there is a way to use EM algorithm to handle missing data and get a completed data set in R?
I usually do it in SPSS because EM in SPSS kind of "fill in" the estimated value for the missing data, and then the completed dataset can be saved and used for further analysis. But I have not found a way to get the a completed data set like this in R or SAS. With
2008 Jun 30
3
Is there a good package for multiple imputation of missing values in R?
I'm looking for a package that has a start-of-the-art method of
imputation of missing values in a data frame with both continuous and
factor columns.
I've found transcan() in 'Hmisc', which appears to be possibly suited
to my needs, but I haven't been able to figure out how to get a new
data frame with the imputed values replaced (I don't have Herrell's book).
Any
2012 Jul 21
2
EM for missing data
Hi list,
I am wondering if there is a way to use EM algorithm to handle missing data and get a completed data set in R?
I usually do it in SPSS because EM in SPSS kind of "fill in" the estimated value for the missing data, and then the completed dataset can be saved and used for further analysis. But I have not found a way to get the a completed data set like this in R or SAS. With
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 <-
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
2018 Mar 19
4
Struggling to compute marginal effects !
Dear Oscar,
and any other R-project person,
Can you please help me to figure out the meaning of the following error
message in red ?
Error in eval(predvars, data, env) :
numeric 'envir' arg not of length one
I computed ordered logit models using 'polr' in R (I just followed the
guidance a handout I found on princeton.edu about logit, probit and
multinomial logit models) . The
2012 Jun 03
1
Multiple imputation, multinomial response & random effects
Dear R-group,
Could somebody recommend a package that can deal with a multinomial response variable (choice of breeding tactic in mice, which has four unordered levels), multiply-imputed data (generated using the Amelia package) and two non-nested random effects: individual identity (133 individuals made up to four choices each) and year (for which there are six levels and sample size varies
2007 May 17
1
MICE for Cox model
R-helpers:
I have a dataset that has 168 subjects and 12 variables. Some of the
variables have missing data and I want to use the multiple imputation
capabilities of the "mice" package to address the missing data. Given
that mice only supports linear models and generalized linear models (via
the lm.mids and glm.mids functions) and that I need to fit Cox models, I
followed the previous
2006 Aug 24
1
how to constrast with factorial experiment
Hello, R users,
I have two factors (treat, section) anova design experiment where
there are 3 replicates. The objective of the experiment is to test if
there is significant difference of yield between top (section 9 to 11)
and bottom (section 9 to 11) of the fruit tree under treatment. I
found that there are interaction between two factors. I wonder if I
can contrast means from levels of
2011 May 03
3
ANOVA 1 too few degrees of freedom
I'm running an ANOVA on some data for respiration in a forest. I am having a
problem with my degrees of freedom. For one of my variables I get one fewer
degrees of freedom than I should.
I have 12 plots and I therefore expected 11 degrees of freedom, but instead
I got 10.
Any ideas?
I have some code and output below:
> class(Combined.Plot)
[1] "character"
>
2011 Oct 18
1
getting basic descriptive stats off multiple imputation data
Hi, all,
I'm running multiple imputation to handle missing data and I'm running into a problem. I can generate the MI data sets in both amelia and the mi package (they look fine), but I can't figure out how to get pooled results. The examples from the mi package, zelig, etc., all seem to go right to something like a regression, though all I want are the mean and SE for all the
2011 Mar 07
5
Parsing question, partly comma separated partly underscore separated string
Dear R-list,
I have a partly comma separated partly underscore separated string that I am trying to parse into R.
Furthermore I have a bunch of them, and they are quite long. I have now spent most of my Sunday trying to figure this out and thought I would try the list to see if someone here would be able to get me started.
My data structure looks like this,
(in a example.txt file)
Subject
2007 Mar 14
1
How to transform matrices to ANOVA input datasets?
Hello, R experts,
I have a list called dataHP which has 30 elements (m1, m2, ..., m30).
Each element is a 7x6 matrix holding yield data from two factors
experimental design, with treatment in column, position in row. For
instance, the element 20 is:
dataHP[[20]]
col1 col2 col3 trt1 trt2 trt3
[1,] 22.0 20.3 29.7 63.3 78.5 76.4
[2,]