Calculates a confidence interval for a standardized mean difference effect size

Calculates a confidence interval for a g_mlm object, using either a central t distribution (for a symmetric interval) or a non-central t distribution (for an asymmetric interval).

CI_g(g, cover = 0.95, bound = 35, symmetric = TRUE)

Arguments

g

an estimated effect size object of class g_mlm.

cover

confidence level.

bound

numerical tolerance for non-centrality parameter in qt.

symmetric

If TRUE (the default), use a symmetric confidence interval. If FALSE, use a non-central t approximation to obtain an asymmetric confidence interval.

Value

A vector of lower and upper confidence bounds.

Examples

library(nlme)
data(Bryant2016, package = "lmeInfo")
Bryant2016_RML1 <- lme(fixed = outcome ~ treatment,
                       random = ~ 1 | school/case,
                       correlation = corAR1(0, ~ session | school/case),
                       data = Bryant2016)
Bryant2016_g1 <- g_mlm(Bryant2016_RML1, p_const = c(0,1), r_const = c(1,1,0,1),
                       infotype = "expected")
CI_g(Bryant2016_g1, symmetric = TRUE)
#> [1] 0.2180582 0.7085558
CI_g(Bryant2016_g1, symmetric = FALSE)
#> [1] 0.2521980 0.7037762