formatters.RdFunctions to format various types of outputs.
fmtp(p, digits=4, pname="", equal=FALSE, sep=FALSE, add0=FALSE, quote=FALSE)
fmtx(x, digits=4, flag="", quote=FALSE, ...)
fmtt(val, tname, df, df1, df2, pval, digits=4,
pname="p-val", format=1, sep=TRUE, quote=FALSE, call=FALSE, ...)Arguments for fmtp:
vector of p-values to be formatted.
integer to specify the number of decimal places to which the values should be rounded. For fmmt, can be a vector of length 2, to specify the number of digits for the test statistic and the p-value, respectively.
string to add as a prefix to the p-value (e.g., something like "p-val" or just "p").
logical to specify whether an equal symbol should be shown before the p-value (when it is larger than the rounding cutoff).
logical to specify whether a space should be added between pname, the equal/lesser symbol, and the p-value.
logical to specify whether a 0 should be shown before the decimal point when the p-value is below the rounding cutoff.
logical to specify whether formatted strings should be quoted when printed.
Arguments specific for fmtx:
vector of numeric values to be formatted.
a character string giving a format modifier as defined for formatC.
Arguments specific for fmtt:
test statistic value to be formatted.
character string for the name of the test statistic.
optional value for the degrees of freedom of the test statistic.
optional value for the numerator degrees of freedom of the test statistic.
optional value for the denominator degrees of freedom of the test statistic.
the p-value corresponding to the test statistic.
either 1 or 2 to denote whether the degrees of freedom should be given before the test statistic (in parentheses) or after the test statistic.
logical to specify whether the formatted test result should be returned as a call or not.
other arguments.
The fmtp function takes one or multiple p-values as input and rounds them to the chosen number of digits. For p-values that are smaller than 10^(-digits) (e.g., 0.0001 for digits=4), the value is shown to fall below this bound (e.g., <.0001).
The fmtx function takes one or multiple numeric values as input and rounds them to the chosen number of digits, without using scientific notation and without dropping trailing zeros (using formatC).
The fmtt function takes a single test statistic value as input (and, if applicable, its degrees of freedom via argument df or its numerator and denominator degrees of freedom via arguments df1 and df2) and the corresponding p-value and formats it for printing. Two different formats are available (chosen via the format argument), one giving the degrees of freedom before the test statistic (in parentheses) and one after the test statistic.
A character vector with the formatted values. By default (i.e., when quote=FALSE), formatted strings are not quoted when printed.
The option in fmtt to return the formatted test result as a call can be useful when adding the output to a plot with text and one would like to use plotmath formatting for tname.
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. https://doi.org/10.18637/jss.v036.i03
# examples for fmtp()
fmtp(c(.0002, .00008), quote=TRUE, digits=4)
#> [1] "0.0002" "<.0001"
fmtp(c(.0002, .00008), quote=TRUE, digits=4, equal=TRUE)
#> [1] "=0.0002" "<.0001"
fmtp(c(.0002, .00008), quote=TRUE, digits=4, equal=TRUE, sep=TRUE)
#> [1] "= 0.0002" "< .0001"
fmtp(c(.0002, .00008), quote=TRUE, digits=4, equal=TRUE, sep=TRUE, add0=TRUE)
#> [1] "= 0.0002" "< 0.0001"
# examples for fmtx()
fmtx(c(1.0002, 2.00008, 3.00004), digits=4)
#> [1] 1.0002 2.0001 3.0000
fmtx(c(-1, 1), digits=4)
#> [1] -1.0000 1.0000
fmtx(c(-1, 1), digits=4, flag=" ")
#> [1] -1.0000 1.0000
# examples for fmtt()
fmtt(2.45, "z", pval=0.01429, digits=2)
#> [1] z = 2.45, p-val = 0.01
fmtt(3.45, "z", pval=0.00056, digits=2)
#> [1] z = 3.45, p-val < .01
fmtt(2.45, "t", df=23, pval=0.02232, digits=2)
#> [1] t(df = 23) = 2.45, p-val = 0.02
fmtt(3.45, "t", df=23, pval=0.00218, digits=2)
#> [1] t(df = 23) = 3.45, p-val < .01
fmtt(3.45, "t", df=23, pval=0.00218, digits=2, format=2)
#> [1] t = 3.45, df = 23, p-val < .01
fmtt(46.23, "Q", df=29, pval=0.0226, digits=2)
#> [1] Q(df = 29) = 46.23, p-val = 0.02
fmtt(46.23, "Q", df=29, pval=0.0226, digits=2, format=2)
#> [1] Q = 46.23, df = 29, p-val = 0.02
fmtt(8.75, "F", df1=2, df2=35, pval=0.00083, digits=c(2,3))
#> [1] F(df1 = 2, df2 = 35) = 8.75, p-val < .001
fmtt(8.75, "F", df1=2, df2=35, pval=0.00083, digits=c(2,3), format=2, pname="p")
#> [1] F = 8.75, df1 = 2, df2 = 35, p < .001
fmtt(8.75, "F", df1=2, df2=35, pval=0.00083, digits=c(2,3), format=2, pname="p", sep=FALSE)
#> [1] F=8.75, df1=2, df2=35, p<.001