dicho.meanci.r: means and ci from dichotomizing/extreme group design to r

In phoebehlam/michaela: convert statistical metrics for meta-analytic purpose

means and ci from dichotomizing/extreme group design to r

Description

means and ci from dichotomizing/extreme group design to correlation coefficient
see pustejovsky, 2014. psychological methods.
returns extreme group r (referred to as r (subscript eg) in pustejovsky paper)

Usage

dicho.meanci.r(
  m1,
  m2,
  cil1,
  ciu1,
  cil2,
  ciu2,
  n1,
  n2,
  k,
  p1,
  p2,
  result = c("sediff", "cil", "ciu")
)

Arguments

m1	mean of group 1
m2	mean of group 2
cil1	lower bound of 95 confidence interval for group 1 mean
ciu1	upper bound of 95 confidence interval for group 1 mean
cil2	lower bound of 95 confidence interval for group 2 mean
ciu2	upper bound of 95 confidence interval for group 2 mean
n1	cell size of group 1
n2	cell size of group 2
k	number of predictors
p1	cutoff percentile for group 1 (sample-based, please see other formulas for population-based in pustejovsky, 2014)
p2	cutoff percentile for group 2 (sample-based, please see other formulas for population-based in pustejovsky, 2014)
result	choose one: "cil" estimates se from lower bound of ci "ciu" estimates se from upper bound of ci "sediff" computes the difference in estimated se computed from upper vs. lower bound ci

Examples

dicho.meanci.r(5, 3, 3, 6, 1, 4, 30, 31, 0, .33, .33)

phoebehlam/michaela documentation built on Oct. 23, 2024, 4:10 p.m.