I am a physician and clearly not a statistician (I try to understand why and how to perform the right analysis, but I don't understand the formulas). I am using SPSS v.19 in analyzing my data. I try to analyze if a biomarker is associated with an increased mortality risk in a subpopulation from my study and I don't know if my analysis is correctly performed.

This the result (part of it) for the entire population:

This is for the one of the subgroups:

This is for the other subgroup:

In this situation, I wanted to see if the association with the mortality risk in the second group was truly significant and I performed a Cox survival analysis with an interaction term: Biomarker value*LOT_1:

Is this analysis correct? And if it is, from this output I should understand that there is no statistically significant association with mortality for the studied biomarker in the second subgroup (no difference for this association in between the two subgroups)? Thank you.

I am a physician and clearly not a statistician (I try to understand why and how to perform the right analysis, but I don't understand the formulas). I am using SPSS v.19 in analyzing my data. I try to analyze if a biomarker is associated with an increased mortality risk in a subpopulation from my study and I don't know if my analysis is correctly performed.

This the result (part of it) for the entire population:

This is for the one of the subgroups:

This is for the other subgroup:

In this situation, I wanted to see if the association with the mortality risk in the second group was truly significant and I performed a Cox survival analysis with an interaction term: Biomarker value*LOT_1:

Is this analysis correct? And if it is, from this output I should understand that there is no statistically significant association with mortality for the studied biomarker in the second subgroup (no difference for this association in between the two subgroups)? Thank you.

LE: This is the output including also the main effect of LOT_1.

This the result (part of it) for the entire population:

            **Variables in the Equation
                              95.0% CI for Exp(B)
           B     SE Wald    df  Sig.    Exp(B)  Lower   Upper

Biomarker value .182 .179 1.032 1 .310 1.200 .844 1.705**

This is for the one of the subgroups:

            **Variables in the Equation(a)
                              95.0% CI for Exp(B)
           B    SE  Wald    df  Sig.    Exp(B)  Lower   Upper

Biomarker value -.191 .228 .702 1 .402 .826 .529 1.291

a. LOT_1 = HD**

This is for the other subgroup:

            **Variables in the Equation(a)
                              95.0% CI for Exp(B)
          B SE  Wald    df  Sig.    Exp(B)  Lower   Upper

Biomarker value .739 .267 7.665 1 .006 2.094 1.241 3.535

a. LOT_1 = PD**

In this situation, I wanted to see if the association with the mortality risk in the second group was truly significant and I performed a Cox survival analysis with an interaction term: Biomarker value*LOT_1:

              **Variables in the Equation
                                     95.0% CI for Exp(B)
                  B SE  Wald    df  Sig.    Exp(B)  Lower   Upper

Biomarker value .181 .180 1.008 1 .315 1.198 .842 1.704 LOT_1*Biomarker value .010 .079 .017 1 .897 1.010 .865 1.181**

This the result (part of it) for the entire population:

This is for the one of the subgroups:

This is for the other subgroup:

In this situation, I wanted to see if the association with the mortality risk in the second group was truly significant and I performed a Cox survival analysis with an interaction term: Biomarker value*LOT_1: