Percentile Confidence Intervals
pcci(thetahatstar, thetahat, theta = NULL, alpha = c(0.001, 0.01, 0.05))
| thetahatstar | Numeric vector. Sampling distribution of thetahat. |
|---|---|
| thetahat | Numeric. Parameter estimate. |
| theta | Numeric. Parameter. Optional argument. |
| alpha | Numeric vector.
Alpha level.
By default |
Other confidence intervals functions:
bcaci(),
bcci(),
evalci(),
len(),
shape(),
theta_hit(),
zero_hit()
Ivan Jacob Agaloos Pesigan
B <- 5000 data <- jeksterslabRdatarepo::thirst thetahat <- fit.ols(data, minimal = TRUE) n <- nrow(data) muthetahat <- colMeans(data) Sigmathetahat <- cov(data) thetahatstar <- pb.mvn( muthetahat = muthetahat, Sigmathetahat = Sigmathetahat, n = n, B = 5000, par = FALSE ) pcci( thetahatstar = thetahatstar, thetahat = thetahat, theta = 0.15 # assuming that the true indirect effect is 0.15 )#> est se reps ci_0.05 ci_0.5 #> 0.15271850 0.07667234 5000.00000000 -0.04208255 0.00347748 #> ci_2.5 ci_97.5 ci_99.5 ci_99.95 zero_hit_99.9 #> 0.03021895 0.32412894 0.39528490 0.47205583 1.00000000 #> zero_hit_99 zero_hit_95 len_99.9 len_99 len_95 #> 0.00000000 0.00000000 0.51413837 0.39180742 0.29390998 #> shape_99.9 shape_99 shape_95 theta_hit_99.9 theta_hit_99 #> 1.63929987 1.62533336 1.39927409 1.00000000 1.00000000 #> theta_hit_95 theta_miss_99.9 theta_miss_99 theta_miss_95 theta #> 1.00000000 0.00000000 0.00000000 0.00000000 0.15000000