stats-calcs: Statistical calculations

In WhiteJP/jpw: Useful tidbits

Statistical calculations

Description

Various stastical calculations.

Usage

normalise(x, in_min = min(x, na.rm = TRUE), in_max = max(x, na.rm = TRUE))

scale_minmax(
  x,
  out_min,
  out_max,
  in_min = min(x, na.rm = TRUE),
  in_max = max(x, na.rm = TRUE)
)

max_z_given_n(n)

se(x, ...)

lm_r2(lm_mod, adjusted = FALSE)

mad(x, na.rm = TRUE)

log10(x)

sym_setdiff(a, b)

q1(x)

q3(pmf)

p_se(p_est, k)

Arguments

x	numeric vector
in_min	minimum possible value of input, defaults to min(x, na.rm = TRUE)
in_max	maximum possible value of input, defaults to max(x, na.rm = TRUE)
out_min	numeric scalar. Minimum value of scaled output.
out_max	numeric scalar. Maximum value of scaled output.
n	numeric scalar. sample size.
lm_mod	model output from stats::lm
adjusted	logical. Whether to return adjusted R (TRUE), or non-adjusted (FALSE). Defaults FALSE
p_est, k	estimated p value from Fisherian randomization inference from K iterations

Functions

• normalise(): normalise vector to scale [0, 1]

• scale_minmax(): normalise vector so that max = mx and min = mn

• max_z_given_n(): Find Maximum z score given sample size n

• se(): Calculate standard error of mean

• lm_r2(): get r squared from stats::lm()

• mad(): get median absolute deviation

• log10(): Log(x, base = 10) wrapper

• sym_setdiff(): symmetrical setdiff()

• q1(): quantile wrapper for Q1

• q3(): quantile wrapper for Q3

• p_se(): estimate standard error of estimate p value from Fisherian randomization inference

See Also

https://www.tandfonline.com/doi/abs/10.1080/00031305.1988.10475530

WhiteJP/jpw documentation built on April 17, 2025, 5:47 a.m.