Round and format p-values. Can also mark significant p-values with stars.
p_round(x, ..., digits = 3)
p_format(
x,
...,
new.col = FALSE,
digits = 2,
accuracy = 1e-04,
decimal.mark = ".",
leading.zero = TRUE,
trailing.zero = FALSE,
add.p = FALSE,
space = FALSE
)
p_mark_significant(
x,
...,
new.col = FALSE,
cutpoints = c(0, 1e-04, 0.001, 0.01, 0.05, 1),
symbols = c("****", "***", "**", "*", "")
)
p_detect(data, type = c("all", "p", "p.adj"))
p_names()
p_adj_names()a numeric vector of p-values or a data frame containing a p value
column. If data frame, the p-value column(s) will be automatically detected.
Known p-value column names can be obtained using the functions
p_names() and p_adj_names()
column names to manipulate in the case where x is a data
frame. P value columns are automatically detected if not specified.
the number of significant digits to be used.
logical, used only when x is a data frame. If TRUE, add
a new column to hold the results. The new column name is created by adding,
to the p column, the suffix "format" (for p_format()), "signif" (for
p_mak_significant()).
number to round to, that is the threshold value above wich the function will replace the pvalue by "<0.0xxx".
the character to be used to indicate the numeric decimal point.
logical. If FALSE, remove the leading zero.
logical. If FALSE (default), remove the training extra zero.
logical value. If TRUE, add "p=" before the value.
logical. If TRUE (default) use space as separator between different elements and symbols.
numeric vector used for intervals
character vector, one shorter than cutpoints, used as significance symbols.
a data frame
the type of p-value to detect. Can be one of c("all", "p", "p.adj").
a vector or a data frame containing the rounded/formatted p-values.
p_round(): round p-values
p_format(): format p-values. Add a symbol "<" for small p-values.
p_mark_significant(): mark p-values with significance levels
p_detect(): detects and returns p-value column names in a data frame.
p_names(): returns known p-value column names
p_adj_names(): returns known adjust p-value column names
# Round and format a vector of p-values
# ::::::::::::::::::::::::::::::::::::::::::::
# Format
p <- c(0.5678, 0.127, 0.045, 0.011, 0.009, 0.00002, NA)
p_format(p)
#> [1] "0.568" "0.127" "0.045" "0.011" "0.009" "<0.0001" "NA"
# Specify the accuracy
p_format(p, accuracy = 0.01)
#> [1] "0.568" "0.127" "0.045" "0.011" "<0.01" "<0.01" "NA"
# Add p and remove the leading zero
p_format(p, add.p = TRUE, leading.zero = FALSE)
#> [1] "p=.568" "p=.127" "p=.045" "p=.011" "p=.009" "p<.0001" "p=NA"
# Remove space before and after "=" or "<".
p_format(p, add.p = TRUE, leading.zero = FALSE, space = FALSE)
#> [1] "p=.568" "p=.127" "p=.045" "p=.011" "p=.009" "p<.0001" "p=NA"
# Mark significant p-values
# ::::::::::::::::::::::::::::::::::::::::::::
p_mark_significant(p)
#> [1] "0.5678" "0.127" "0.045*" "0.011*" "0.009**" "2e-05****"
#> [7] "NA"
# Round, the mark significant
p %>% p_round(digits = 2) %>% p_mark_significant()
#> [1] "0.57" "0.13" "0.04*" "0.01**" "0.009**" "2e-05****"
#> [7] "NA"
# Format, then mark significant
p %>% p_format(digits = 2) %>% p_mark_significant()
#> [1] "0.568" "0.127" "0.045*" "0.011*" "0.009**"
#> [6] "<0.0001****" "NA"
# Perform stat test, format p and mark significant
# ::::::::::::::::::::::::::::::::::::::::::::
ToothGrowth %>%
group_by(dose) %>%
t_test(len ~ supp) %>%
p_format(digits = 2, leading.zero = FALSE) %>%
p_mark_significant()
#> # A tibble: 3 × 9
#> dose .y. group1 group2 n1 n2 statistic df p
#> * <dbl> <chr> <chr> <chr> <int> <int> <dbl> <dbl> <chr>
#> 1 0.5 len OJ VC 10 10 3.17 15.0 .0064**
#> 2 1 len OJ VC 10 10 4.03 15.4 .001***
#> 3 2 len OJ VC 10 10 -0.0461 14.0 .964