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st: Re: Stata package -diagt- version 2.0.5.
Dear Allesandro,
Bootstrapping should not be necessary, as the CI for sensitivity &
specificity
are based on the exact Binomial distribution. In fact, if you do not use
the -bca- option with bootstrap, you will get symmetrical intervals
based on 1.96 SE, which are definitely worse.
Alo, for speed with long runs, you are very often better off writing
your own version of
a program that only does the bare minimum you need, as otherwise, you
will be asking the
computer to work out a lot of unneeded values, which can be quite time
consuming.
I have done this below for diagt.
*****************************
prog drop _all
prog define mydiagt, rclass
*! mydiagt version 1.0 written 12 May 2009 by PT Seed ([email protected])
*! stripped-down version of -diagt- for use with -bootstrap- command.
* Note: it assumes that values of test & true variables are 0 and 1 only.
version 6.0
* Syntax
syntax varlist(min=2 max=2 numeric) [if]
tempvar touse
mark `touse' `if'
tokenize "`varlist'"
local true `1'
local test `2'
su `true' if `test' == 1 & `touse', meanonly
return scalar sens = r(mean)
su `true' if `test' == 0 & `touse', meanonly
return scalar spec = (1-r(mean))
end mydiagt
bootstrap sens=r(sens) spec=r(spec), reps(100) bca: mydiagt true test
estat bootstrap, all
**********************************
Paul T Seed MSc CStat CSci, Senior Lecturer in Medical Statistics,
tel (+44) (0) 20 7188 3642, fax (+44) (0) 20 7620 1227
Wednesdays: (+44) (0) 20 7848 4208
[email protected], [email protected]
King's College London, Division of Reproduction and Endocrinology
St Thomas' Hospital, Westminster Bridge Road, London SE1 7EH
Alessandro A. Leidi wrote:
Dear Paul,
Just to bring to your attention that I have hit a snag with your excellent Stata package -diagt- version 2.0.5, which does not like to be prefixed by-bootstrap-, since it calls -diagti- for computations, as explained by Thomas Steichen below.
Tried but failed to locate an earlier version like 2.0.0: do you know where I can find one?
Meanwhile I'll try to delve into diagt.ado and diagti.ado fo version 2.0.5 to see if I can contribute.
Thank you and regards
Sandro Leidi
________________________________________
From
"Steichen, Thomas J." <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: RE: RE: bootstrap with a user-contributed command
Date
Mon, 11 May 2009 16:09:37 -0400
________________________________________
Assuming you are running version 2.0.5 or later of -diagt-, the problem appears to be that -diagt- calls -diagti-, wherein r(spec) and r(sens) are generated, then -diagt- reads these values and attempts to repost them. The values appear to get lost when -bootstrap- is wrapped around everything.
Version 2.0.0 of -diagt- does its own computations (i.e., doesn't call -diagti-), so it works fine with -bootstrap-:
. diagti 80 17 11 44
True |
disease | Test result
status | Pos. Neg. | Total
-----------+----------------------+----------
Abnormal | 80 17 | 97
Normal | 11 44 | 55
-----------+----------------------+----------
Total | 91 61 | 152
[95% Conf. Inter.]
-------------------------------------------------------------------------
Sensitivity Pr( +| D) 82.47% 73.43% 89.45%
Specificity Pr( -|~D) 80.00% 67.03% 89.57%
Positive predictive value Pr( D| +) 87.91% 79.40% 93.81%
Negative predictive value Pr(~D| -) 72.13% 59.17% 82.85%
-------------------------------------------------------------------------
Prevalence Pr(D) 63.82% 55.64% 71.44%
-------------------------------------------------------------------------
Likelihood Ratio of Pos. Test LR+ 4.12 2.41 7.05
Likelihood Ratio of Neg. Test LR- 0.22 0.14 0.34
-------------------------------------------------------------------------
. which diagt
h:\ado\diagt.ado
*! diagt 2.0.0 21 Feb 2001 PTS -- added DR and FPR
. bootstrap sens=r(sens) spec=r(spec): diagt true test
(running diagt on estimation sample)
Warning: Since diagt is not an estimation command or does not set e(sample),
bootstrap has no way to determine which observations are used in
calculating the statistics and so assumes that all observations are used.
This means no observations will be excluded from the resampling because of
missing values or other reasons.
If the assumption is not true, press Break, save the data, and drop the
observations that are to be excluded. Be sure that the dataset in memory
contains only the relevant data.
Bootstrap replications (50)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
.................................................. 50
Bootstrap results Number of obs = 152
Replications = 50
command: diagt true test
sens: r(sens)
spec: r(spec)
------------------------------------------------------------------------------
| Observed Bootstrap Normal-based
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
sens | 82.47423 3.475202 23.73 0.000 75.66296 89.2855
spec | 80 4.271629 18.73 0.000 71.62776 88.37224
------------------------------------------------------------------------------
-----------------------------------
Thomas J. Steichen
[email protected]
-----------------------------------
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Alessandro A. Leidi
Sent: Monday, May 11, 2009 1:13 PM
To: [email protected]
Subject: st: RE: bootstrap with a user-contributed command
I had already tried bootstrapping -diagt- directly without a user-written program, see below.
-bootstrap- squawks like it does when used with -rclass- functions but it does not deliver for -diagt-.
Of course it may be my mistake, but where am I going wrong?
Thank you for your consideration.
Sandro Leidi
[email protected]
. quietly diagti 80 17 11 44
. which diagt
c:\ado\plus\d\diagt.ado
*! diagt 2.052, 30 June 2003
*! by PT Seed ([email protected])
*! based on diagtest.ado (Aurelio Tobias, STB-56: sbe36)
*! and further suggestions from Tom Steichen
. bootstrap sens=r(sens) spec=r(spec): diagt true test
(running diagt on estimation sample)
Warning: Since diagt is not an estimation command or does not set e(sample), bootstrap has no way to determine which observations are used in calculating the statistics and so assumes that all observations are used. This means no observations will be excluded from the resampling because of missing values or other reasons.
If the assumption is not true, press Break, save the data, and drop the observations that are to be excluded.
Be sure that the dataset in memory contains only the relevant data.
Bootstrap replications (50)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
post __000002 not found
post __000002 not found
r(111);
.
*
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