Get full P value in R when it's less than 2.225074e-308 (.Machine&double.xmin)











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I have a question in regards to getting very very tiny p-value to print fully in R.



I ran a survival analysis using the code:



x <- coxph(Surv(my_data$Start,my_data$time_variable,my_data$event) ~ 

(my_data$variable1))

s <- summary(x)

print(s)


In the summary results as the P value was so small it just displayed as "< 2e-16"



Normally, if this happens, I just print out the p-value separately to get the actual number using the below command:



coef(summary(x))[1,5]


However, this time it is just printing "0", I think this is because the p-value is less than ".Machine$double.xmin" which is 2.225074e-308.
I have also tried changing this to see if I can print a smaller number but if I change .Machine$double.xmin to less than 2.225074e-308 it just automatically changes the number to 0.



Is there a way to get the actual number for a p-value when it's so small or is this a limitation of R that cannot be gotten around?



Any help would be greatly appreciated! Many thanks!






r p-value







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  • Why do you need the exact value of such a low p-value? The only way to calculate it is to work on the logarithmic scale, which is supported by R's distribution functions. Likely one of these functions is used internally to calculate the p-value here.
    – Roland
    Nov 21 at 16:46










  • I'm jealous this is a problem I never have... :)
    – Ian Wesley
    Nov 21 at 17:10















up vote
0
down vote

favorite












I have a question in regards to getting very very tiny p-value to print fully in R.



I ran a survival analysis using the code:



x <- coxph(Surv(my_data$Start,my_data$time_variable,my_data$event) ~ 

(my_data$variable1))

s <- summary(x)

print(s)


In the summary results as the P value was so small it just displayed as "< 2e-16"



Normally, if this happens, I just print out the p-value separately to get the actual number using the below command:



coef(summary(x))[1,5]


However, this time it is just printing "0", I think this is because the p-value is less than ".Machine$double.xmin" which is 2.225074e-308.
I have also tried changing this to see if I can print a smaller number but if I change .Machine$double.xmin to less than 2.225074e-308 it just automatically changes the number to 0.



Is there a way to get the actual number for a p-value when it's so small or is this a limitation of R that cannot be gotten around?



Any help would be greatly appreciated! Many thanks!






r p-value







share|improve this question






















  • Why do you need the exact value of such a low p-value? The only way to calculate it is to work on the logarithmic scale, which is supported by R's distribution functions. Likely one of these functions is used internally to calculate the p-value here.
    – Roland
    Nov 21 at 16:46










  • I'm jealous this is a problem I never have... :)
    – Ian Wesley
    Nov 21 at 17:10













up vote
0
down vote

favorite









up vote
0
down vote

favorite











I have a question in regards to getting very very tiny p-value to print fully in R.



I ran a survival analysis using the code:



x <- coxph(Surv(my_data$Start,my_data$time_variable,my_data$event) ~ 

(my_data$variable1))

s <- summary(x)

print(s)


In the summary results as the P value was so small it just displayed as "< 2e-16"



Normally, if this happens, I just print out the p-value separately to get the actual number using the below command:



coef(summary(x))[1,5]


However, this time it is just printing "0", I think this is because the p-value is less than ".Machine$double.xmin" which is 2.225074e-308.
I have also tried changing this to see if I can print a smaller number but if I change .Machine$double.xmin to less than 2.225074e-308 it just automatically changes the number to 0.



Is there a way to get the actual number for a p-value when it's so small or is this a limitation of R that cannot be gotten around?



Any help would be greatly appreciated! Many thanks!






r p-value







share|improve this question













I have a question in regards to getting very very tiny p-value to print fully in R.



I ran a survival analysis using the code:



x <- coxph(Surv(my_data$Start,my_data$time_variable,my_data$event) ~ 

(my_data$variable1))

s <- summary(x)

print(s)


In the summary results as the P value was so small it just displayed as "< 2e-16"



Normally, if this happens, I just print out the p-value separately to get the actual number using the below command:



coef(summary(x))[1,5]


However, this time it is just printing "0", I think this is because the p-value is less than ".Machine$double.xmin" which is 2.225074e-308.
I have also tried changing this to see if I can print a smaller number but if I change .Machine$double.xmin to less than 2.225074e-308 it just automatically changes the number to 0.



Is there a way to get the actual number for a p-value when it's so small or is this a limitation of R that cannot be gotten around?



Any help would be greatly appreciated! Many thanks!






r p-value




r p-value






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asked Nov 21 at 14:31









Caragh

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  • Why do you need the exact value of such a low p-value? The only way to calculate it is to work on the logarithmic scale, which is supported by R's distribution functions. Likely one of these functions is used internally to calculate the p-value here.
    – Roland
    Nov 21 at 16:46










  • I'm jealous this is a problem I never have... :)
    – Ian Wesley
    Nov 21 at 17:10


















  • Why do you need the exact value of such a low p-value? The only way to calculate it is to work on the logarithmic scale, which is supported by R's distribution functions. Likely one of these functions is used internally to calculate the p-value here.
    – Roland
    Nov 21 at 16:46










  • I'm jealous this is a problem I never have... :)
    – Ian Wesley
    Nov 21 at 17:10
















Why do you need the exact value of such a low p-value? The only way to calculate it is to work on the logarithmic scale, which is supported by R's distribution functions. Likely one of these functions is used internally to calculate the p-value here.
– Roland
Nov 21 at 16:46




Why do you need the exact value of such a low p-value? The only way to calculate it is to work on the logarithmic scale, which is supported by R's distribution functions. Likely one of these functions is used internally to calculate the p-value here.
– Roland
Nov 21 at 16:46












I'm jealous this is a problem I never have... :)
– Ian Wesley
Nov 21 at 17:10




I'm jealous this is a problem I never have... :)
– Ian Wesley
Nov 21 at 17:10

















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