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Maybe this question is too general, but I think it's worthy to post to clarify me some standard procedures in survival analysis. As we know, there are a list of method and models like parametric (exp, weibull, AFT), nonparametric (KW, NA), and semi-parametric (cox prop, prop) methods in survival analysis. Suppose I have a data frame like this:

set.seed(123)
require(survival)
df<-data.frame(time=as.integer(rnorm(100,50,5)), 
               status=rbinom(100,1,0.7), 
               age=rnorm(100,60, 5), 
               gender=rbinom(100,1,0.5))
df$time<-ifelse(df$time>=50,50,df$time)
df
    time status   age gender
1     47      1 63.94      0
2     48      0 63.85      0
3     50      1 61.66      0
...
98    50      1 53.20      0
99    48      1 56.68      1
100   44      0 62.43      0

I'd like to know what's an appropriate way to check which model I should use for this survival analysis.

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