I am conducting a 20 year longitudinal study on firm survival using a number of variable such as size, profitability, cash resource etc. What is the difference between the Kaplan Meier and Cox proportional hazard and are these the right tests to use? Does anyone have an example of how this is done in SPSS?
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$\begingroup$ Whether you are using the "right" test depends on what you want to test exactly. $\endgroup$– AndyCommented May 5, 2016 at 11:47
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The Kaplan-Meier estimator is for estimating a homogeneous cumulative survival or cumulative incidence function in the absence of competing events. In order for the distribution to be homogeneous, all the regression coefficients in the Cox model would have to be zero in the population. So it is very uncommon for Kaplan-Meier estimates to be the focus. Instead you can get survival curve estimates in the Cox model context. There are several options in some software packages for which survival estimator is used with the Cox model. One of the methods is the Kalbfleisch-Prentice estimator which is exactly Kaplan-Meier if all the regression coefficients are estimated to be exactly zero.
When obtaining survival estimates from a Cox model fit you have to specify the values of all the covariates. You can vary one of the covariates at a time to see their effects. In R this is extremely easy to do.
answered May 5, 2016 at 12:48
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$\begingroup$ Thank you so much Frank- I am going to try find software on SPSS that can do the cox modelling. Really appreciate it. $\endgroup$ Commented May 7, 2016 at 10:53