Dear list,
When I try using cem in Stata 10,* *I get the error* "*no variables
defined in option treatment(), r(111);" even though my syntax looks fine.
(My command was "cem AGCYTYPE POPULATION region lblackproportion, tr
(POLYEXAM).") The website <http://gking.harvard.edu/cem/> indicates it
works in version 10.
When I try using it in Stata 12, I think the program gets a little farther.
But I still get the error "cem_weights not found" after the commands:
cem AGCYTYPE POPULATION region lblackproportion, tr (POLYEXAM)
reg lblackproportion POLYEXAM YP YEAR [iweight=cem_weights]
Any ideas how to troubleshoot? My best guess is that I skipped important
pre-cem steps and the program is protesting that sort of human error.
Perhaps the matched N (672) is too small and so I should simulate more data
to produce more matches?
Many thanks,
Katelyn
--
Katelyn Sack, Ph.D. candidate
University of Virginia
Hello, CEM list:
I would like to use CEM with survey data. The sampling design is stratified
with survey weights (1500 observations). I would like, if possible, to
estimate population estimates (PATE and PATT).
My questions:
1. Is it possible to get this estimations with CEM? (if yes, how?)
2. Can imbalance be used with survey data? (if yes, how?)
3. I see that, with CEM, the researcher must specify interactions. Exist
any kind of advice on which interactions to include with CEM?
After the matching, I would like to test mediator effects (SEM with Mplus),
using the CEM matched observations and weights (perhaps the weights to be
used are a product of CEM weights and survey weights?), and the correct
sampling design (stratified, on the subpopultation of matched cases?).
Thanking you in advance,
Fernando
Dear moderator,
Please ignore my previous message with a request to post to the CEM listserv. I was able to solve the problem on my own.
Thank you,
P. Zachary
Department of Political Science
George Washington University
Hello everyone,
I am running into an issue trying to use CEM on a dataset where the treatment variable can take different values within the same unit. Because countries in my panel data set can have different values of the treatment variable in different country years, CEM is matching the same country from before it receives the treatment to the same country after it receives the treatment. For example, if Panama received the treatment I am looking at in 1950 (treatment =1), and was coded with treatment = 1 from 1950 - 1970, CEM is matching Panama to itself. Instead, I'd like to match only countries who always have treatment = 0 to those that take treatment =1.
Is there a way to prevent CEM from doing this?
Thank you!
P. Zachary
Department of Political Science
George Washington University
Dear list members
having installed CEM for SPSS19 I get the following error.
****begin message****
CEM TREATMENT=brandx VARIABLES=sex edu lft.
Traceback (most recent call last):
File "<string>", line 16, in <module>
File "C:\PROGRA~1\IBM\SPSS\STATIS~1\19\extensions\CEM.py", line 81, in Run
newds = spss.Dataset(name = "cemoutdata")
File "C:\Python26\lib\site-packages\spss190\spss\dataStep.py", line
91, in __init__
raise SpssError,error
spss.errMsg.SpssError: [errLevel 99] Cannot create specified dataset.
**** end message ****
I received the same message on a different PC, but Windows7 and 64bit
Can someone point out what the problem might be?
best wishes
Maurice
--
___________________________________________________________________
Maurice Vergeer
To contact me, see http://mauricevergeer.nl/node/5
To see my publications, see http://mauricevergeer.nl/node/1
___________________________________________________________________
Dear colleagues,
Hi,
I am a cardiologist of south korea.
i am fully satisfied with cem in R, and delighted to know cem for spss has been released.
however, i met some problems during trying to introduce cem to my colleagues, who use spss.
after some bothersome processes, i managed to run cem with spss.
(the package needs not only python plugin, but also numpy and scipy packages for python. you had better add the information on the intallation guide.)
but i could not use cem options, such as k2k or no-imbalance.
especially, k2k is essential for my colleagues and me.
in addition, other functions do not work either, such as cutpoints or grouping.
i attached the error message with a ppt file.
i really appreciate your work to implant cem to spss,
and also hope this information would help your further development.
Sincerely,
- DH Shin
==================================
Dong-Ho Shin, MD, MPH,
Clinical Assistant Professor
Division of Cardiology, Severance Cardiovascular Hospital
Yonsei University College of Medicine
50 Yonseiro, Seodaemun-gu, Seoul, 120-752, Korea
Tel. (82)-2-2227-3606 / (82)-2-2228-8460
Fax. (82)-2-2227-7732 / (82)-2-2227-7015
CP. (82)-10-3369-5651
E-mail: dhshin(a)yuhs.ac<mailto:kimbk@yuhs.ac> / johnshine.md(a)gmail.com<mailto:kimbk03@gmail.com>
==================================
I am using cem to match treatment and control group members from 5 multiply
imputed datasets from Amelia. I've encountered two types of problems.
First, when I run a logit model after calling cem on the multiply imputed
datasets:
> run <- att(new1, Pass ~ SEQ + O_GPA + O_HRS_EARNED + AGE + PELL1 +
LOG_CA_SCORE + LOG_CM_SCORE, data = imputed, model = "logit")
I get the following warning messages, one for each multiply imputed
dataset:
Warning messages:
1: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
2: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
3: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
4: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
5: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
My dependent variable had no missing cases, so the values for it were not
imputed for any observations, and I have checked that the values of it are
either 0 or 1. Any ideas why I am getting this warning? I've noticed from
searching online that this warning arises when weights are included in a
binomial glm model, so I wonder if it might have something to do with how
cem is weighting the control observations.
(2) The second issue relates to displaying the output of the model. When I
type:
> run
I get:
Logistic model on CEM matched data:
SATT point estimate: 1.509872 (p.value=0.001640)
95% conf. interval: [0.570028, 2.449717]
which is fine, but when I type:
> summary(run)
I get:
Treatment effect estimation for data:
NULL
Logistic model estimated on matched data only
Coefficients:
Error in symnum(pv, corr = FALSE, na = FALSE, cutpoints = c(0, 0.001, :
'x' must be between 0 and 1
Any idea why I'm getting this error?
Thanks for any help you can provide,
Bill
