+ Reply to Thread
Results 1 to 6 of 6

Thread: Proportional hazards and Cox Model

  1. #1
    Points: 3,621, Level: 37
    Level completed: 81%, Points required for next Level: 29
    askazy's Avatar
    Location
    Holand
    Posts
    160
    Thanks
    4
    Thanked 0 Times in 0 Posts

    Proportional hazards and Cox Model




    I'm trying to fit a Cox model, but there is some problems. I have the following variables in the model.

    - Group: 1, 2, ..., 9
    - Sex: 1 female and 0 male
    - Weight
    - Age

    The first thing that I did is split the variables Age and Weight in 4 different groups and check if the assumption of proportional hazards is met for each variable. I did the plot of log-log(S(t))xt

    The plot below is from Groups



    For all the four variables the proportional hazard assumption is violated (crossed curves). Then I check it with hypothesis test and run the model

    Code: 
    model<-coxph(Surv(Time,Event)~ Group + Sex + Weight + Age,data= dataset)
        summary(model)
                 coef          exp(coef)      se(coef)   z       Pr(>|z|)
        G2  0.1705602  1.1859691  0.1956226  0.872 0.383272    
        G3 -1.0036611  0.3665351  0.2386762 -4.205 2.61e-05 ***
        G4 -0.8381683  0.4325020  0.2399613 -3.493 0.000478 ***
        G5 -0.4544249  0.6348130  0.2092611 -2.172 0.029888 *  
        G6 -0.9123168  0.4015927  0.3471589 -2.628 0.008590 ** 
        G7 -0.9977854  0.3686950  0.2413699 -4.134 3.57e-05 ***
        G8 -1.7056585  0.1816527  0.3097035 -5.507 3.64e-08 ***
        G9 -1.1614730  0.3130248  0.2488757 -4.667 3.06e-06 ***
        Sex    -0.0307328  0.9697347  0.1331374 -0.231 0.817443    
        Weight 0.0004572  1.0004573  0.0004121  1.109 0.267330    
        Age    0.0044168  1.0044266  0.0036702  1.203 0.228815
    From the `summary` of model, Sex, Weight, Age are not significant. Then the model just have groups as variables.

    So I did

    Code: 
    cox.zph(model,transform="rank",global=TRUE)
        
                      rho   chisq        p
        G2 -0.1142  4.2426 0.039423
        G3 -0.1732 10.6197 0.001119
        G4 -0.0989  3.2302 0.072293
        G5 -0.1588  8.7741 0.003055
        G6 -0.1284  5.4636 0.019416
        G7 -0.0508  0.9136 0.339165
        G8  0.0984  3.3136 0.068709
        G9 -0.1062  4.1598 0.041395
        Sex    0.0085  0.0242 0.876276
        Weight     0.1121  5.1191 0.023664
        Age      -0.0109  0.0372 0.846986
        GLOBAL         NA 36.2568 0.000153
    I don't understand well this output, Group7 have prorportional hazard alone? How Sex, Age have proportional hazards if the curves of plot crossed?


    If one level of categorical variable not hold the proportional hazard assumption, then the categorical variable not met the assumption right?
    The difference between stupidity and genius is that genius has its limits.
    "Albert Einstein"

  2. #2
    Points: 3,621, Level: 37
    Level completed: 81%, Points required for next Level: 29
    askazy's Avatar
    Location
    Holand
    Posts
    160
    Thanks
    4
    Thanked 0 Times in 0 Posts

    Re: Proportional hazards and Cox Model

    I tested several models using likelihood ratio test, and the only significant explanatory variable is group, but the proportional hazard assumption is not valid for all levels of this variable. What I should do in this case?

    I have just one significant variable, and some levels of this variable don't met the proportional hazard assumption.
    The difference between stupidity and genius is that genius has its limits.
    "Albert Einstein"

  3. #3
    Points: 143, Level: 2
    Level completed: 86%, Points required for next Level: 7

    Posts
    3
    Thanks
    0
    Thanked 0 Times in 0 Posts

    Re: Proportional hazards and Cox Model

    Quote Originally Posted by askazy View Post
    Group7 have prorportional hazard alone? .
    answering this question ... I'd say yes ... it means Group 7 has PH relative to your baseline group (group 1 I think).
    I think the first thing I'd ask is why are you categorising age and weight - unless there's a good reason (cutoffs are clinically relevant ie not just quartiles) then I'd keep those as continuous and do PH tests for a continuous variable (then I'd prefer the cumulative martingale tests of Wei both for PH and for functional form is should it be a log transform)

  4. #4
    Points: 3,621, Level: 37
    Level completed: 81%, Points required for next Level: 29
    askazy's Avatar
    Location
    Holand
    Posts
    160
    Thanks
    4
    Thanked 0 Times in 0 Posts

    Re: Proportional hazards and Cox Model

    Quote Originally Posted by azStats View Post
    answering this question ... I'd say yes ... it means Group 7 has PH relative to your baseline group (group 1 I think).
    I think the first thing I'd ask is why are you categorising age and weight - unless there's a good reason (cutoffs are clinically relevant ie not just quartiles) then I'd keep those as continuous and do PH tests for a continuous variable (then I'd prefer the cumulative martingale tests of Wei both for PH and for functional form is should it be a log transform)
    I just categorising age and weight when I did the plot of loglog(S(t)) to see if exists violation of proportional hazard assumption, in the cox.phz I didn't did it.
    The difference between stupidity and genius is that genius has its limits.
    "Albert Einstein"

  5. #5
    Omega Contributor
    Points: 38,281, Level: 100
    Level completed: 0%, Points required for next Level: 0
    hlsmith's Avatar
    Location
    Not Ames, IA
    Posts
    6,990
    Thanks
    397
    Thanked 1,185 Times in 1,146 Posts

    Re: Proportional hazards and Cox Model

    I get what you are trying to do. Is that the normal approach for testing proportional hazard, the categorizing of a continuous variable? I haven't used PHReg in awhile.
    Stop cowardice, ban guns!

  6. #6
    Points: 3,621, Level: 37
    Level completed: 81%, Points required for next Level: 29
    askazy's Avatar
    Location
    Holand
    Posts
    160
    Thanks
    4
    Thanked 0 Times in 0 Posts

    Re: Proportional hazards and Cox Model


    Quote Originally Posted by hlsmith View Post
    I get what you are trying to do. Is that the normal approach for testing proportional hazard, the categorizing of a continuous variable? I haven't used PHReg in awhile.
    This is one of the possible approaches to verify whether the proportionality hypothesis is satisfied, although the interpretation is somewhat subjective. Even if I use the Cox model stratified by groups, and assume that the weight variable satisfies the hypothesis of proportionality (it does not satisfy, has p-value 0.02) the output of the stratified model is as follows
    Code: 
                 coef  exp(coef)   se(coef)      z Pr(>|z|)
    Sex -0.0295480  0.9708843  0.1331459 -0.222    0.824
    Weight    0.0004545  1.0004546  0.0004111  1.105    0.269
    Age    0.0043919  1.0044016  0.0036679  1.197    0.231
    Here I have two main points

    1) The explanatory variables are not significant

    2) The explanatory variables don't have significant effect, since the exp(coef) is almost 1.

    I'm really lost about this cox model for this data.
    The difference between stupidity and genius is that genius has its limits.
    "Albert Einstein"

+ Reply to Thread

           




Posting Permissions

  • You may not post new threads
  • You may not post replies
  • You may not post attachments
  • You may not edit your posts






Advertise on Talk Stats