I ran this code to get the confidence intervals for the 4 different groups in my dataset. However for group 1, it seems that the upper and lower confidence intervals are not being computed.
Valve.size valvemedian lowerci upperci
<fct> <dbl> <dbl> <dbl>
1 1 5760 -Inf Inf
2 2 7150 6100 8090
3 3 9210 8320 10400
4 4 10450 9520 13700
This is the code that I used to get to the result before - it worked for the other groups except the first one:
library(DescTools)
barplot2 <- barplot %>%
dplyr::group_by(Valve.size) %>%
dplyr::summarise(valvemedian = MedianCI(DAP, na.rm = TRUE)[1],
lowerci = MedianCI(DAP, na.rm = TRUE)[2],
upperci = MedianCI(DAP, na.rm = TRUE)[3])
Based on some quick experiments, it looks like the default method for DescTools::MedianCI ("exact") returns (-Inf, Inf) as the confidence intervals whenever there are 5 or fewer observations in the vector. In contrast, method = "boot" appears to return non-infinite confidence intervals down to n=2 (n=1 gives an error).
If you do switch to using method = "boot" you should call set.seed(...) (with the integer value of your choice) to make sure the results are reproducible.
It would be possible to dig further into the code and figure out why (the procedure starts (for 95% confidence intervals) by computing the critical value for a binomial test with probability = 0.5: qbinom(0.025, size = n, prob = 0.5, lower.tail = TRUE) &mdash which comes out to 0 for n=5 and 1 for n=6, that's probably where the trouble starts ...) What looks like a description of the rationale for the exact method (which may be more technical than you want) is in an answer to this CrossValidated question.