No standard error output in quantile regression using R

Question

I am running a quantile regression (as my residuals in linear regression were not normally distributed) for a study on the association of mediterranean diet and inflammatory markers. As I was building the model I got outputs for beta coefficients and standard error plus p-values, and confidence intervals. However, once I stratified for low and high levels of exercise, there was no longer an output for standard error. Any ideas?enter image description here

I used to coding:summary(model_CRP_quantile_14) [then on next line] summary(model_CRP_quantile_14, se = "rank") which I used for the earlier models and got out puts with se and then conf ints. If I just run the first line by itself I also get coefficient and cons ints only - NO standard error??? — Murphy
– Murphy, Commented Jul 9, 2021 at 8:58
You don't need to pipe into filter, there is an argument rq(..., subset = exercise_level == "low"). — Rui Barradas
– Rui Barradas, Commented Jul 9, 2021 at 9:07

user2974951 · Accepted Answer · 2021-07-09 09:02:54Z

1

By default rq does not returns standard errors, but rather the confidence interval by inverting a rank test. If you want standard errors you have to specify another method for se, such as se="boot".

Note: the whole point of quantile regression is to move away from means and SD, so this may not be the most adequate estimate for your problem.

answered Jul 9, 2021 at 9:02

user2974951

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