Get full P value in R when it's less than 2.225074e-308 (.Machine&double.xmin)
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
edited Dec 4 '18 at 20:27
massisenergy
577218
asked Nov 21 '18 at 14:31
Caragh
255
add a comment |
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
edited Dec 4 '18 at 20:27
massisenergy
577218
asked Nov 21 '18 at 14:31
Caragh
255
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 '18 at 16:46
1
I'm jealous this is a problem I never have... :)
– Ian Wesley
Nov 21 '18 at 17:10
add a comment |
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
edited Dec 4 '18 at 20:27
massisenergy
577218
asked Nov 21 '18 at 14:31
Caragh
255
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
edited Dec 4 '18 at 20:27
massisenergy
577218
asked Nov 21 '18 at 14:31
Caragh
255
edited Dec 4 '18 at 20:27
massisenergy
577218
asked Nov 21 '18 at 14:31
Caragh
255
edited Dec 4 '18 at 20:27
massisenergy
577218
edited Dec 4 '18 at 20:27
massisenergy
577218
edited Dec 4 '18 at 20:27
massisenergy
577218
577218
asked Nov 21 '18 at 14:31
Caragh
255
asked Nov 21 '18 at 14:31
Caragh
255
asked Nov 21 '18 at 14:31
Caragh
255
255
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 '18 at 16:46
1
I'm jealous this is a problem I never have... :)
– Ian Wesley
Nov 21 '18 at 17:10
add a comment |
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 '18 at 16:46
1
I'm jealous this is a problem I never have... :)
– Ian Wesley
Nov 21 '18 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 '18 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 '18 at 16:46
1
1
I'm jealous this is a problem I never have... :)
– Ian Wesley
Nov 21 '18 at 17:10
I'm jealous this is a problem I never have... :)
– Ian Wesley
Nov 21 '18 at 17:10
add a comment |
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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 '18 at 16:46
1
I'm jealous this is a problem I never have... :)
– Ian Wesley
Nov 21 '18 at 17:10