[SOLVED] What is the difference between psm and cph in RMS package in R

What is the difference between psm and cph in RMS package in R

I have a survival data, but I'm not sure what's the different between psm and cph. How can I determine the model?

Different model will establish the different nomogram, but I'm not really sure which model I should use?

library(rms)
f2 <- psm(Surv(follow_time_5y, DEATH_5y) ~ age+ID_SEX+MH_CCI_total_score, 
          data =sci_20190505, dist='lognormal')

f2 <- cph(Surv(follow_time_5y, DEATH_5y) ~ age+ID_SEX+MH_CCI_total_score, 
               data =sci_20190505,x=TRUE,y=TRUE,surv=TRUE, time.inc=1825)

Solution

Depending of what you want.

PSM:

psmis a modification of Therneau survreg function for fitting the accelerated failure time family of parametric survival models.psmuses therms class for automatic anova, fastbw, calibrate, validate, and other functions.Hazard.psm,Survival.psm,Quantile.psm, and Mean.psmcre-ate S functions that evaluate the hazard, survival, quantile, and mean (expected value) functions analytically, as functions of time or probabilities and the linear predictor values.

CPH:

Modification of Therneau coxph function to fit the Cox model and its extension, the Andersen-Gill model. The latter allows for interval time-dependent covariables, time-dependent strata, and repeated events. The Survival method for an object created by cph returns an S function for computing estimates of the survival function. The Quantile method for cph returns an S function for computing quantiles of survival time (median, by default).

So to answer your question: "Whats the difference?"

The difference is in the model used.

psm (parametric survival model) uses a survival model based on functions and their parameters. A good paper for parametric survival is this

cph (Cox Proportional Hazards Model and Extensions) is using the cox model (and the Anderson-Gill model) which is based on the hazard functions. You can check the wikipedia article here