dicho.meanci.zvar: variance of z converted from dichotomizing/extreme group...

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

variance of z converted from dichotomizing/extreme group design mean and ci

Description

compute the variance of z from t-statistics derived from dichotomizing/extreme group design mean and ci
see pustejovsky, 2014. psychological methods.

Usage

dicho.meanci.zvar(
  m1,
  m2,
  cil1,
  ciu1,
  cil2,
  ciu2,
  n1,
  n2,
  k,
  p1,
  p2,
  type = c("vd.ce", "vd.eg")
)

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)
type	select one from below, please read pustejovsky, 2014. psychological methods.for recommendations there are situations where the "controlled experiment" formulas are recommended even for stats derived from dichotomize/extreme group designs so please refer to his paper "vd.ce" compute variance of d using the controlled experiment formulas "vd.eg" compute variance of d using the extreme group formulas

Examples

dicho.meanci.zvar(5, 3, 3, 6, 1, 4, 30, 31, 0, .33, .33, "vd.eg")

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