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P value significant digits
i found a point which actually is not a issue. i found that when i use "t_test" function to calculate p Value, it always give only 3 significant digits . in some case, more digits would help. could this be optimized? Thanks!
Hi @LeiHanAVLH
Can you post a reprex (reproducible example)? Meanwhile, you can try to increase the number of significant digits manually with options(pillar.sigfig = x)
as shown below.
The issue might also be the p-values themselves if they don't contain any further digits (see below as well).
library(tidyverse)
library(rstatix)
example_test <- PlantGrowth %>%
t_test(weight ~ group)
# The output contains 3 significant digits in all columns
example_test
#> # A tibble: 3 x 10
#> .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
#> * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 weight ctrl trt1 10 10 1.19 16.5 0.25 0.25 ns
#> 2 weight ctrl trt2 10 10 -2.13 16.8 0.048 0.096 ns
#> 3 weight trt1 trt2 10 10 -3.01 14.1 0.009 0.028 *
# This behaviour can be changed like so
options(pillar.sigfig = 4)
example_test
#> # A tibble: 3 x 10
#> .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
#> * <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 weight ctrl trt1 10 10 1.191 16.52 0.25 0.25 ns
#> 2 weight ctrl trt2 10 10 -2.134 16.79 0.048 0.096 ns
#> 3 weight trt1 trt2 10 10 -3.010 14.10 0.009 0.028 *
# Notice that the p-column seems not to bee affected by this option but this is
# the result of the p-values themselves. They don't have any further digits.
example_test %>%
pull(p)
#> [1] 0.250 0.048 0.009
Created on 2021-10-06 by the reprex package (v2.0.1)