As discussed in Section 11.4, we can perform a log-rank test to compare the survival of males to females, using the survdiff() function.

> logrank.test <- survdiff(Surv(time, status) ~ sex)
> logrank.test
Call:
survdiff(formula = Surv(time, status) ~ sex)

            N Observed Expected (O-E)^2/E (O-E)^2/V
sex=Female 45       15     18.5     0.676      1.44
sex=Male   43       20     16.5     0.761      1.44

 Chisq= 1.4  on 1 degrees of freedom, p= 0.23 

The resulting p-value is 0.23, indicating no evidence of a difference in survival between the two sexes.

Questions

• MC1:
  On the publication dataset, perform a log-rank test to answer the following question: Is there evidence of a difference in time-to-publication between studies with positive versus negative results on a 95% significance level? (Store the output of the survdiff() function in logrank.pub)
  1. Yes
  2. No

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Assume that:

• The ISLR2 and survival libraries has been loaded
• The Publication dataset has been loaded and attached