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@lists.gking.harvard.edu <cem-request@lists.gking.harvard.edu> wrote:


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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@unimi.it>
To: Emina Omerovic <emina.omerovic@mcri.edu.au>
Cc: "king-assist@iq.harvard.edu" <king-assist@iq.harvard.edu>,
    "cem@lists.gking.harvard.edu" <cem@lists.gking.harvard.edu>
Subject: Re: [cem] Matching for a continuous variable
Message-ID: <EE3D260F-F995-43CE-9253-3BD276C1C1A1@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: https://doi.org/10.1017/pan.2018.29)

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@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@mcri.edu.au>
> Cc: cem@lists.gking.harvard.edu; king-assist@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@mcri.edu.au <mailto:emina.omerovic@mcri.edu.au>> wrote:



> From: cem-bounces@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@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@mcri.edu.au <mailto:emina.omerovic@mcri.edu.au>
> W  mcri.edu.au <https://www.mcri.edu.au/>


>
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