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st: RE: RE: bootstrap with a user-contributed command


From   "Steichen, Thomas J." <SteichT@RJRT.com>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
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
------------------------------------------------------------------------------

. bootstrap sens=r(sens) spec=r(spec), reps(1000): 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 (1000)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
..................................................   900
..................................................   950
..................................................  1000

Bootstrap results                               Number of obs      =       152
                                                Replications       =      1000

      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    3.88919    21.21   0.000     74.85155     90.0969
        spec |         80   5.674551    14.10   0.000     68.87808    91.12192
------------------------------------------------------------------------------



-----------------------------------
Thomas J. Steichen
steicht@rjrt.com
-----------------------------------

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Alessandro A. Leidi
Sent: Monday, May 11, 2009 1:13 PM
To: statalist@hsphsun2.harvard.edu
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
a.a.leidi@rdg.ac.uk

. quietly diagti 80 17 11 44

. desc

Contains data
  obs:           152
 vars:             2
 size:           912 (99.9% of memory free)
---------------------------------------------------------------------------------------------------------------              storage  display     value
variable name   type   format      label      variable label
---------------------------------------------------------------------------------------------------------------true            byte   %8.0g       true       True disease status
test            byte   %8.0g       test       Test result
---------------------------------------------------------------------------------------------------------------Sorted by:
     Note:  dataset has changed since last saved

. 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);

.

st: RE: bootstrap with a user-contributed command

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