[R] coxph | anova results

[Daniel Malter]

Hi,
 
I ran a coxph model and in the summary the independent variables are
reported highly significant. However, if I run anova() on that model, some
of the variables are reported to explain basically no deviance and other
variables which are reported insignificant in the model summary are reported
to explain some deviance here. Can somebody give advice how to make sense of
this output and interpret the results if the two outputs are somewhat
contradictory? Is it due to anova() including the variables sequentially? Do
I rely on the model or on the anova for interpretation?

Thanks much,
Daniel
 
 
Call:
coxph(formula = Surv(DurBeg, Closed) ~ SumInvested + numberofgainstocksheld
+ 
    numberoflossstocksheld + TotalInvested + WorseThanMarket + 
    Loss + posilow + posihigh + negalow + negahigh + Loss:posilow + 
    Loss:posihigh + Loss:negalow + Loss:negahigh)

  n=11232 (28 observations deleted due to missingness)
                            coef exp(coef) se(coef)       z       p
SumInvested            -2.24e-05     1.000 1.12e-05  -1.999 4.6e-02
numberofgainstocksheld -5.37e-02     0.948 1.20e-02  -4.493 7.0e-06
numberoflossstocksheld -1.72e-01     0.842 1.22e-02 -14.032 0.0e+00
TotalInvested           3.18e-05     1.000 1.65e-05   1.919 5.5e-02
WorseThanMarket1       -9.83e-02     0.906 4.60e-02  -2.139 3.2e-02
Loss1                   3.45e-01     1.412 9.67e-02   3.570 3.6e-04
posilow                -6.72e-02     0.935 3.73e-02  -1.803 7.1e-02
posihigh                6.93e-02     1.072 3.62e-02   1.914 5.6e-02
negalow                 1.87e-01     1.206 4.28e-02   4.367 1.3e-05
negahigh               -2.42e-01     0.785 4.78e-02  -5.060 4.2e-07
Loss1:posilow           9.06e-03     1.009 5.25e-02   0.172 8.6e-01
Loss1:posihigh         -1.04e-01     0.901 5.07e-02  -2.054 4.0e-02
Loss1:negalow          -2.98e-01     0.742 6.10e-02  -4.891 1.0e-06
Loss1:negahigh          2.66e-01     1.305 6.70e-02   3.971 7.2e-05

                       exp(coef) exp(-coef) lower .95 upper .95
SumInvested                1.000      1.000     1.000     1.000
numberofgainstocksheld     0.948      1.055     0.926     0.970
numberoflossstocksheld     0.842      1.187     0.822     0.863
TotalInvested              1.000      1.000     1.000     1.000
WorseThanMarket1           0.906      1.103     0.828     0.992
Loss1                      1.412      0.708     1.168     1.707
posilow                    0.935      1.069     0.869     1.006
posihigh                   1.072      0.933     0.998     1.151
negalow                    1.206      0.829     1.109     1.311
negahigh                   0.785      1.274     0.715     0.862
Loss1:posilow              1.009      0.991     0.910     1.118
Loss1:posihigh             0.901      1.110     0.816     0.995
Loss1:negalow              0.742      1.348     0.658     0.836
Loss1:negahigh             1.305      0.766     1.144     1.488

Rsquare= 0.035   (max possible= 0.967 )
Likelihood ratio test= 399  on 14 df,   p=0
Wald test            = 400  on 14 df,   p=0
Score (logrank) test = 412  on 14 df,   p=0

> anova(cluster4,test="Chisq")
Analysis of Deviance Table
 Cox model: response is Surv(DurBeg, Closed)
Terms added sequentially (first to last)

                          Df  Deviance Resid. Df Resid. Dev P(>|Chi|)
NULL                                       11232      38469          
SumInvested                1         0     11231      38526         1
numberofgainstocksheld     1        55     11230      38471 1.032e-13
numberoflossstocksheld     1       271     11229      38200 7.454e-61
TotalInvested              1         4     11228      38196 3.964e-02
WorseThanMarket            1         7     11227      38189 8.439e-03
Loss                       1        13     11226      38176 4.021e-04
posilow                    1        66     11225      38110 4.306e-16
posihigh                   1 1.502e-01     11224      38110         1
negalow                    1 3.036e-01     11223      38110         1
negahigh                   1        10     11222      38100 1.321e-03
Loss:posilow               1         1     11221      38099 3.385e-01
Loss:posihigh              1         2     11220      38096 1.208e-01
Loss:negalow               1        11     11219      38085 9.707e-04
Loss:negahigh              1        16     11218      38070 7.283e-05