Hi everyone. I'd like to have you all over to my house for an end of year
party on Saturday May 10th at noon. Please feel free to bring a guest,
kids, etc. We've got 2 dogs, in case that's an issue for anyone. We live
in Brookline about 5 miles from HU, and easy to get to by Bus, T, or car.
Directions are at this hidden link: http://gking.harvard.edu/directions
I'd appreciate if you'd RSVP soon, by responding to me and my assistant
Bev who I've CC'd, so we can get a count for food. Let me know whether
you can make it and if you'll be bringing someone. I hope to see you
there.
Gary
Hi all,
I'm having trouble installing MatchIt, or more specifically, lpSolve... it
looks like the Mac binary isn't working (according to CRAN), though I had it
working last week before I updated R to 2.7.0...
I get the following error when installing from the source:
gcc -arch ppc -isysroot /Developer/SDKs/MacOSX10.4u.sdk
-mmacosx-version-min=10.4 -std=gnu99
-I/Library/Frameworks/R.framework/Resources/include
-I/Library/Frameworks/R.framework/Resources/include/ppc
-I/usr/local/include -I . -DINTEGERTIME -DPARSER_LP -DBUILDING_FOR_R
-DYY_NEVER_INTERACTIVE -DUSRDLL -DCLOCKTIME -DRoleIsExternalInvEngine
-DINVERSE_ACTIVE=INVERSE_LUSOL -DINLINE=static -DParanoia -fPIC -g -O2 -c
lpslink55.c -o lpslink55.o
lpslink55.c:11:20: error: malloc.h: No such file or directory
make: *** [lpslink55.o] Error 1
chmod:
/Library/Frameworks/R.framework/Versions/2.7/Resources/library/lpSolve/libs/ppc/*:
No such file or directory
ERROR: compilation failed for package 'lpSolve'
Any thoughts?
Thanks,
Ben
Just to double check, when I run the setx() and then the sim() command on a
dataset that is an mi()'ed version of Amelia datasets, is Zelig automatically
creating the 1/m number of simulations from each constituent dataset and making
the necessary mathematical corrections?
As in such a case:
Zelig.Imputed <- mi(out1,out2,out3,out4,out5)
ruler <- seq(0,1,0.005)
my.model <-
zelig(dprotestmar.max4~dlprotestmar.max4+polity2l+provcont+eprovcont, model =
"logit", data = Zelig.Imputed)
x.out <- setx(my.model, provcont=ruler, eprovcont=3)
s.out <- sim(my.model, x=x.out)
Thanks!
-Colin
Jen(n|s),
Does a paper copy of the problem set need to be submitted for those of us who
normally submit paper copies, or should we just submit the PDF to the dropbox?
Thanks!
-Colin
Hi,
I am a little confused about the wording in Q1, Part C:
For the counterfactual dataset, are we supposed to switch all import
observations, where a 1 becomes 0 and a 0 becomes 1, or are we just supposed
to switch all the 0's to 1's per #2 in Part B?
Thanks,
Marcy
--
Marcy E. McCullaugh
Ph.D. student
Department of Political Science
University of California, Berkeley
210 Barrows Hall
Berkeley, CA 94720
Exchange Scholar 2007-08
Department of Government and
Davis Center for Russian and Eurasian Studies
Harvard University
1730 Cambridge Street, 3rd Floor
Cambridge, MA 02138
We have a massive output file that took hours to run (a list of R objects).
How do we save it? And how do we save the workspace? I'm working on the
servers...
Thanks!
John
Silly question:
How does one sort a dataframe such that it only sorts on the characteristics
of the first column and preserves each row as an intact unit? I.e., I have a
vector of propensity scores in column one that I want sorted, but the
propensity score corresponds to other variables in columns 2-8 that must
remain connected to those scores.
Thanks!
John
Hi everyone,
I have a quick question. I'm working with several multiply imputed data sets
and would like to simulate quantities of interest at mean/mode values of
explanatory variables. Because of the way I subset data iteratively in a for
loop, I would like to consolidate the five data sets into a single data set,
with each observation simply taking the mean (or, in some cases, mode) value
of the five data cells from the imputed data sets.
So my question: How can I coerce the five imputed data sets into a single
data set with mean/mode values? There must be some straightforward way to do
this.
Thanks in advance for the help. Best,
Brett
I've been trying to figure this out for a little while. When I try to
estimate my model in Zelig, I get:
> model <- zelig(immpol ~ LABOR + IDEO + INCOME + WHITE + BLACK +
ASIAN + HISP + EDUC + AGE + SEX + secon + pecon + jobhard + UNEMPLOY
+ ifriend + iarea, model="ls", data=pew)
Error in data.frame(RESP = c(1, 6, 7, 8, 9, 10, 11, 12, 13, 15, 17,
18, :
arguments imply differing number of rows: 6003, 0
Even though:
> length(pew$immpol); length(pew$LABOR); length(pew$IDEO); length(pew
$INCOME); length(pew$WHITE); length(pew$BLACK); length(pew$ASIAN);
length(pew$HISP); length(pew$EDUC); length(pew$AGE); length(pew$SEX);
length(pew$secon); length(pew$pecon); length(pew$jobhard); length(pew
$UNEMPLOY); length(pew$ifriend); length(pew$iarea)
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
[1] 6003
Does anyone have a theory as to what could be going on here?
Thanks,
Keith