Hello,
Suppose I run an lm model on data with NAs. It won't (and shouldn't)
produce residuals for entries that are excluded or that already have NAs in
them. The residual vector skips the numbers for these entries. How could I
produce a vector of residuals that includes NAs in the spots that have been
skipped?
Thanks,
Laurence
This is not for the assignment for this class, but it is an R
question that I thought someone might know.
I just want something like a histogram (or maybe a polygon), but with
relative frequencies rather than frequencies or densities. Is there a
straightforward way to make this happen?
the closer the better. ideally the results should match exactly.
From: Aakanksha Pande [mailto:aaka.pande at gmail.com]
Sent: Thursday, March 27, 2008 4:31 PM
To: Jens Hainmueller
Subject: Re: Replication
thanks jens. i was wondering how close to the published estimates we have to
be? i get almost similar estimates but not quite the same numbers.
aaka
On Thu, Mar 27, 2008 at 3:26 PM, Jens Hainmueller <jhainmueller at gmail.com>
wrote:
Aaka,
It's best to send such question to the list. No clue why you are getting
this error (hard to tell from the given information, maybe a variable that
is missing in the dataset because the variable name is miss-spelled).
However, I am also not clear on what you want to do exactly. In this model
all but what is within the tag() would be a FEs and all what is within the
tag() are REs. Take a look at the documentation on how FE and RE are
specified. Also the Bates book has many examples of models that combine RE
and FE.
Hth,
Jens
From: Aakanksha Pande [mailto:aaka.pande at gmail.com]
Sent: Thursday, March 27, 2008 3:37 PM
To: Jens Hainmueller
Subject: Re: Replication
hi jens
following up on your advice i am trying to do a FIXED effects model now in R
and keep getting this error. any ideas?
a<-zelig(eabs.100~male+years.here+years.here.sq+born.dist+doctor+night.shift
+field.visit+provided.house+inspec.2m+dist.min.health+toilets.avail+water.av
ail+dist.road+round1+round2+Monday.int+Tuesday.int+Wednesday.int+Thursday.in
t+Friday.int+phc+tag(1|dist), data=data, model="ls.mixed")
Error in `[.data.frame`(d, , all.vars(as.expression(formula))) :
undefined columns selected
the model is say y~x1+x2 with fe at x3(district level)
thanks!
Aaka
On Wed, Mar 26, 2008 at 10:56 AM, Jens Hainmueller <jhainmueller at gmail.com>
wrote:
Zelig's ls.mixed does RE models, drawing from the lm4 package. The
bibliography in the zelig documentation on this model also has many helpful
references (ie. the Bates papers and book on this which many examples).
there is plenty of documentation out there.
you can also use the nlme package. I think lm4 is the latest version and
they may have changed the syntax a little bit, but here is a quick example
from nlme:
library(nlme)
# FE for age and experience, random intercept for classroom
summary(lme(fixed=score~age+experience,random=~1|classroom,data=data2))\par
# FE for experience, random coefficient for age and random intercept for
classroom
summary(lme(fixed=score~age+experience,random=~age|classroom,data=data2))
\par
hth,
jens
From: Aakanksha Pande [mailto:aaka.pande at gmail.com]
Sent: Wednesday, March 26, 2008 11:40 AM
To: Jens Hainmueller
Cc: larson.jenn at gmail.com; Gary King
Subject: Re: Replication
Thanks Jens.I am trying to replicate my work in STATA in R. I am trying to
do a hierarchical linear model (with random effects) and was wondering how
to do that in R?
best
Aaka
I am still trying to work with sampling weights. I found that I can
apply the weights using library(survey); svydesign() and then do
parameter estimates using svymle(). This is fine, but I still wonder
if there is an easier way to do this. Is there some argument that I
can pass to zelig to make it estimate the model with these sampling
weights? I think the likelihood that I will make an error when I try
to simulate things is much smaller if I can do it in zelig.
Hey yall,
The author of the paper we're replicating did a logit model in stata
using xtlogit with, in his words, "random effects for country code." I
haven't been able to replicate his numbers in either stata or R...
In R, I've been doing:
a<-zelig(y~x1+x2...+tag(1|ccode), data=dat, model="logit.mixed")
But I'm not sure if finding a different intercept for each country
(which is what the above code does) is the same as what the author did.
Can anybody clarify what the author meant? (we don't have his exact
stata code - only what he provided above.)
thanks,
didi & shahrzad
We are trying to estimate a multinomial logit model with robust standard errors
(the cases are clustered by country). Can anyone help with these questions...
1) We have a dependent variable with three factors. It seems that Zelig takes
one as the base and estimates coefficients and SE for the other two. Is there
any way to know which ones it is taking? Is it possible to change which one the
base should be and which should be estimated? The Zelig mlogit function does not
seem to take a "robust=" argument. Does this mean it cannot do robust SE or is
there some other way to set it up?
2) We also tried to use the multinom function in the nnet package. This function
automatically gives us the right coefficients for the two factors we want, but
the SE's are wrong, probably because they are not the robust ones. Is there a
way to estimate robust SE's in the multinom function, or perhaps in another
package or function? We have not found other options, but perhaps someone else
has.
Thanks!
I am trying to subset my sample based on the logical operators below.
If anybody could shed some light on why I am getting syntax errors, I
would be grateful.
sample=brfss[HADHYST2==2 && CTYCODE != 777 && CTYCODE != 999 $$ AGE
>= 40]
Error: syntax error
Thanks,
Keith
Low priority question (I've found a work-around), but I'd like to know why I'm
having problems with this R code:
data3$epop.inequal.11[data3$ordepop == 1 & data3$ordinequality == 1] <- 1
data3$epop.inequal.11[data3$ordepop != 1 | data3$ordinequality != 1] <- 0
data3$epop.inequal.11[data3$ordepop == NA | data3$ordinequality == NA] <- NA
What I'm trying to do with this is create a new dummy variable based on the
values of two ordinal variables. The two that it's drawing from are scaled 1-3
(low, medium, high), and this particular dummy variable is supposed to be a 1
when both of the ordinal variables = 1, otherwise 0.
It's correctly re-coding the 1s and 0s, but the second line is causing some of
the missing values to be coded as missing and others to be coded as 0s.
The following code works, but it's not as straightforward or as easy to
describe. Why is the first set of commands working mostly correctly but not
fully?
data3$epop.inequal.11[data3$ordepop == 1 & data3$ordinequality == 1] <- 1
data3$epop.inequal.11[data3$ordinequality != 1] <- 0
data3$epop.inequal.11[data3$ordepop != 1 & data3$ordinequality == 1] <- 0
Hi all,
We are working on our replication project and have loaded an SPSS file into
R. We are attempting to select rows based on values of three variables. The
first two have values of 1 and 2. We can easily select for the value of 1.
The third variable has values of 0 and 1. When we try to select for any
value (either 0 or != 1), we get an error message that reads:
Error in if (plomin[i, 11] == TRUE) { :
missing value where TRUE/FALSE needed
This is what our code looked like:
vec <- c()
k <- 0
for(i in 1:nrow(plomin)){
if (plomin[i,7] == 1) & plomin[i,3] == 1 & plomin[i,11] == 0 )
{
k <- k + 1
vec[k] <- i}
}
mat.corr.gesl <- plomin[vec,c(20,21)]
Does anyone have any idea why we should be getting this message? Or,
alternatively, is there a better way of selecting for values of our
variables?
Thanks!
Best wishes,
Jill and Jeremy (Hodgen)
Let's say I have a variable called "variable," which is a dummy
variable, and I want to do a logistic regression only for cases in
which variable=1. I give Zelig the following command:
m1 <- zelig(Y ~ x1 + x2 + x3, model="logit", data="mydata",
by="variable")
And Zelig tells me:
"Error in dat[, by] : incorrect number of dimensions"
Can anybody shed some light on what I'm doing wrong?
Thanks,
Keith
