Why not apply first CEM using all vars but kbitssw5 and then a matching with caliper
using onl kbitssw5?
Kind Regards Cesare A.F. Riillo
On Wednesday, 10 October 2018, 03:04:16 CEST, cem-request(a)lists.gking.harvard.edu
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Today's Topics:
1. Re: Matching for a continuous variable (stefano iacus)
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Message: 1
Date: Wed, 10 Oct 2018 03:04:03 +0200
From: stefano iacus <stefano.iacus(a)unimi.it>
To: Emina Omerovic <emina.omerovic(a)mcri.edu.au>
Cc: "king-assist(a)iq.harvard.edu" <king-assist(a)iq.harvard.edu>du>,
"cem(a)lists.gking.harvard.edu" <cem(a)lists.gking.harvard.edu>
Subject: Re: [cem] Matching for a continuous variable
Message-ID: <EE3D260F-F995-43CE-9253-3BD276C1C1A1(a)unimi.it>
Content-Type: text/plain; charset="utf-8"
Hi Emina,
strata should not overlap in order to have all the CEM statistical properties to hold,
i.e. the assumptions of our theory of statistical inference are not fulfilled (see, or
last paper:
)
so, I am sorry, the answer is negative (unless you find a way to transform the 1-sd
intervals into a sequence of cutpoint.)
Stefano
On 10 Oct 2018, at 00:30, Emina Omerovic
<emina.omerovic(a)mcri.edu.au> wrote:
Hi Stefano,
So if I have a variable of continuous scores and want to match the sample based on scores
within 1 sd (e.g. 15) rather than applying the cutpoints which creates categories of
scores such that
cem gender kbitssw5 (70 85 100 115 130), treatment (group)
becomes the equivalent of
recode kbitssw5 (0/70 = 1 "Well below average") (70/85 = 2 "Below
average") (85/115 = 2 "Average") (115/130 = 3 "Above average")
(130/200 = 3 "Well above average"), gen(kbittssw5_5cat)
cem gender kbittssw5_5cat, treatment(group)
Can I match based on freely changing cutpoints to maintain that 1 sd ? Eg. A participant
with a score of 80 could be matched to someone with a score anywhere between 65 and 95,
and not just between 70 and 85
Kind regards
Emina
From: stefano iacus [mailto:stefano.iacus@unimi.it]
Sent: Tuesday, 2 October 2018 1:55 PM
To: Emina Omerovic <emina.omerovic(a)mcri.edu.au>
Cc: cem(a)lists.gking.harvard.edu; king-assist(a)iq.harvard.edu
Subject: Re: [cem] Matching for a continuous variable
Hi,
if I understand correctly, you just need to specify the cutpoints argument in the cem()
function like on page 10 (bottom) of the pdf document you mention.
Usually the best thing to do is to write a simple reproducible example (R code + sample
of data) so that we can help you to solve your problem.
Best regards
Stefano
On 26 Sep 2018, at 04:11, Emina Omerovic <emina.omerovic(a)mcri.edu.au
<mailto:emina.omerovic@mcri.edu.au>> wrote:
From: cem-bounces(a)lists.gking.harvard.edu
<mailto:cem-bounces@lists.gking.harvard.edu>
[mailto:cem-bounces@lists.gking.harvard.edu
<mailto:cem-bounces@lists.gking.harvard.edu>] On Behalf Of Emina Omerovic
Sent: Wednesday, 26 September 2018 11:38 AM
To: cem(a)lists.gking.harvard.edu <mailto:cem@lists.gking.harvard.edu>
Subject: [cem] Matching for a continuous variable
Hello,
Using the example provided
http://scholar.harvard.edu/files/gking/files/cem.pdf
<http://scholar.harvard.edu/files/gking/files/cem.pdf> I am not sure how to
approach matching for continuous scores eg. An IQ score. Using my data sample and the
automated method, it appears all matches are within about 8 score points. If we wanted to
define the coarsening to about within 15 points (eg within 1 SD) how could I do this?
Thank you
Looking forward to the reply
Emina Omerovic BSc, MClAud
Research Assistant
Intergenerational Health
Murdoch Children's Research Institute
The Royal Children's Hospital, 50 Flemington Road
Parkville, Victoria 3052 Australia
E emina.omerovic(a)mcri.edu.au <mailto:emina.omerovic@mcri.edu.au>
W mcri.edu.au <https://www.mcri.edu.au/>
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