Elizabeth
Thanks for your help with this.
I also wonder if there is a way in MatchIT to prioritize some covariates
over others.
I think not, but I thought I'd double check.
On Mon, Dec 5, 2016 at 12:00 PM, <matchit-request(a)lists.gking.harvard.edu>
wrote:
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> 1. Re: SUM.all (Elizabeth Stuart)
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> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sun, 4 Dec 2016 18:49:47 +0000
> From: Elizabeth Stuart <estuart(a)jhu.edu>
> To: William Dudley <wndudley(a)uncg.edu>
> Cc: MatchIt <matchit(a)lists.gking.harvard.edu>
> Subject: Re: [matchit] SUM.all
> Message-ID: <0949463C-AA01-4AFD-98C5-E100DCDAAEB8(a)jhu.edu>
> Content-Type: text/plain; charset="utf-8"
>
> Dear William,
> If you use the following commands MatchIt will output the standardized
> mean differences; you certainly don?t need to calculate the SMDs by hand!
>
> summary(MI_mah_ctakPCT_11_20.out, standardize=TRUE)
>
> Thanks,
> Liz
>
>
> On Nov 28, 2016, at 10:55 AM, William Dudley <wndudley(a)uncg.edu<mailto:
> wndudley(a)uncg.edu>> wrote:
>
> I am currently working with a matching task in which I need to establish
> balance within funder's guidelines (SD <= .25). At this point, I am
> running matchIT (Syntax provided below) and then saving the matching
> solution as a CSV file and using Excel to compute the SD's for each of the
> covariates.
>
> However, I see in the Matchit documentation that the sum.all may
> accomplish this within the program in one step.
>
> My problem is that I cannot figure out how to include the sum.all command.
> Thanks in advance for any help,
>
> Bill
>
>
>
> MI_mah_ctakPCT_11_20.out <- matchit(tx ~ CtakPCT +dropout + race + pov +
> Mathprfc + Readprfc +ACTComZ + size , data = MI11, method = "optimal",
> ratio=4,Distance ="Mahalanobis")
>
> MI_mah_ctakPCT_11_20.out
>
> MI_mah_ctakPCT_11_20.dat <- match.data(MI_mah_ctakPCT_11_20.out)
>
> MI_mah_ctakPCT_11_20.dat
>
> summary(MI_mah_ctakPCT_11_20.dat)
>
> write.table(MI_mah_ctakPCT_11_20.dat,"C:/SECEP/match/MI match
> output/MI_mah_ctakPCT_11_20.txt",sep="\t",row.names=FALSE)
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>
> --
> William N. Dudley, PhD
> Professor - Public Health Education
> The School of Health and Human Sciences
> The University of North Carolina at Greensboro
> 437-L Coleman Building
> Greensboro, NC 27402-6170
> Visit my Web Site<http://www.uncg.edu/phe/faculty/dudley.html>
> VOICE 336.256 2475
>
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>
I am currently working with a matching task in which I need to establish
balance within funder's guidelines (SD <= .25). At this point, I am
running matchIT (Syntax provided below) and then saving the matching
solution as a CSV file and using Excel to compute the SD's for each of the
covariates.
However, I see in the Matchit documentation that the sum.all may accomplish
this within the program in one step.
My problem is that I cannot figure out how to include the sum.all command.
Thanks in advance for any help,
Bill
*MI_mah_ctakPCT_11_20.out <- matchit(tx ~ CtakPCT +dropout + race + pov +
Mathprfc + Readprfc +ACTComZ + size , data = MI11, method = "optimal",
ratio=4,Distance ="Mahalanobis")*
*MI_mah_ctakPCT_11_20.out*
*MI_mah_ctakPCT_11_20.dat <- match.data(MI_mah_ctakPCT_11_20.out)*
*MI_mah_ctakPCT_11_20.dat*
*summary(MI_mah_ctakPCT_11_20.dat)*
*write.table(MI_mah_ctakPCT_11_20.dat,"C:/SECEP/match/MI match
output/MI_mah_ctakPCT_11_20.txt",sep="\t",row.names=FALSE)*
--
William N. Dudley, PhD
Professor - Public Health Education
The School of Health and Human Sciences
The University of North Carolina at Greensboro
437-L Coleman Building
Greensboro, NC 27402-6170
Visit my Web Site <http://www.uncg.edu/phe/faculty/dudley.html>
VOICE 336.256 2475
