Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

probitInverse

Probit-Inverse of Group-Level Normal Distribution

Description

Transform latent group-level normal distribution (latent-trait MPT) into mean and SD on probability scale.

Usage

probitInverse(mu, sigma, fittedModel = NULL)

Arguments

mu

latent-probit mean of normal distribution
sigma

latent-probit SD of normal distribution
fittedModel

optional: fitted traitMPT model. If provided, the bivariate inverse-probit transform is applied to all MCMC samples (and mu and sigma are ignored).

Value

implied mean and SD on probability scale

Examples

####### compare bivariate vs. univariate transformation
probitInverse(mu=.8, sigma=c(.25,.5,.75,1))
pnorm(.8)

# full distribution
prob <- pnorm(rnorm(10000, .8, .7))
hist(prob, 80, col="gray", xlim=0:1)

## Not run: 
# transformation for fitted model
mean_sd <- probitInverse(fittedModel=fit)
summarizeMCMC(mean_sd)

## End(Not run)
TreeBUGS

Hierarchical Multinomial Processing Tree Modeling

v1.4.7
GPL-3
Authors
Daniel W. Heck [aut, cre] (<https://orcid.org/0000-0002-6302-9252>), Nina R. Arnold [aut, dtc], Denis Arnold [aut], Alexander Ly [ctb], Marius Barth [ctb] (<https://orcid.org/0000-0002-3421-6665>)
Initial release
2021-01-08

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.