Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: st: Survival Analysis estat phtest with very large sample size--need help


From   Peter Rymkiewicz <peter.rymkiewicz@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Survival Analysis estat phtest with very large sample size--need help
Date   Fri, 06 Dec 2013 10:55:18 -0700

Hi Adam,

Thanks for your response. I agree with all that you have said... part of the issue is that this work is towards a thesis and I need to reference literature or statistics materials. Will try to use the TVC option with the original model and look to see what the resulting effect is on the HR of each of the covariates in the model.

I am also running an alternative model which actually captures time dependance. as you predicted the AIC is higher but this model actually includes information past baseline.

Thanks,
Peter

On 13-12-05 7:41 PM, Adam Olszewski wrote:
Hi Peter,
As with any statistical test that uses a null hypothesis, the p-value
for the phtest is dependent on the sample size. These tests were not
developed for such large datasets. In population-based survival
analyses violations of PH assumptions are universal, just as linearity
assumptions are. One way to deal with it on a practical level is to
see how much inclusion of a time-varying effect would affect your main
effect HR. If the difference is null, then the PH violation is
practically of no significance. This helps if you are only interested
in one coefficient (more of a problem if your variable of interest
violates the PH, in which you should rethink your interpretation).
Other ways of dealing with it are: 1) relying on the graphical
interpretation of residuals alone, as you did, 2) using AIC as a
measure of model fit: does the inclusion of time-varying effects (or
stratification in Cox model) significantly alter model fit? More often
than no the AIC will actually increase.
I cannot quote you literature on this off the top of my head though.
Best,
AO

On Thu, Dec 5, 2013 at 9:26 PM, prymkiewicz <peter.rymkiewicz@gmail.com> wrote:
Hi,

I need a bit of help.

I am doing a survival analysis on a large population ~435732 people.  I have
been testing the PH assumption using estat phtest and schoenfled residuals.
I believe that the large sample size is causing the phtest indicate evidence
against the PH assumption while the schoenfeld plot would indicate that the
model variables adheres to the PH assumption. I have included the global and
individual variable tests, as well as the plot for one of our variables
(mets). Could you let me know the cause of this and could you let me know if
there are alternative methods or references in literature acknowledging the
phtest and alternative methods for very large study populations.

Thanks,
Peter

. estat phtest, detail

       Test of proportional-hazards assumption

       Time:  Time
       ----------------------------------------------------------------
                   |       rho            chi2       df       Prob>chi2
       ------------+---------------------------------------------------
       male        |      0.01247        11.18        1         0.0008
       age         |      0.05331       252.06        1         0.0000
       0b.urban    |            .            .        1             .
       1.urban     |     -0.01640        19.44        1         0.0000
       99.urban    |     -0.00225         0.36        1         0.5472
       1b.quintile |            .            .        1             .
       2.quintile  |     -0.00620         2.74        1         0.0976
       3.quintile  |     -0.00745         3.98        1         0.0461
       4.quintile  |     -0.00025         0.00        1         0.9457
       5.quintile  |     -0.00311         0.70        1         0.4039
       99.quintile |     -0.00119         0.10        1         0.7499
       mi_1        |     -0.00795         4.63        1         0.0314
       chf_1       |     -0.02492        47.01        1         0.0000
       pvd_1       |      0.00206         0.32        1         0.5734
       cevd_1      |     -0.02076        32.80        1         0.0000
       dem_1       |      0.00630         3.05        1         0.0807
       copd_1      |     -0.01545        17.10        1         0.0000
       rheum_1     |     -0.00840         5.06        1         0.0245
       pub_1       |     -0.00712         3.67        1         0.0553
       mildld_1    |     -0.00959         6.59        1         0.0102
       diab_uc_1   |     -0.02159        34.32        1         0.0000
       diab_c_1    |      0.01731        21.99        1         0.0000
       para_1      |     -0.01532        17.14        1         0.0000
       rd_1        |     -0.03307        82.48        1         0.0000
       cancer_1    |     -0.03237        72.39        1         0.0000
       mlsd_1      |     -0.00246         0.43        1         0.5099
       mets_1      |     -0.06236       272.50        1         0.0000
       hiv_1       |     -0.00863         5.31        1         0.0213
       ------------+---------------------------------------------------
       global test |                   1392.71       26         0.0000
       ----------------------------------------------------------------

<http://statalist.1588530.n2.nabble.com/file/n7580460/phtest_plot_mets_1.jpg>



--
View this message in context: http://statalist.1588530.n2.nabble.com/Survival-Analysis-estat-phtest-with-very-large-sample-size-need-help-tp7580460.html
Sent from the Statalist mailing list archive at Nabble.com.
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/
*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index