dot-partit_bvnorm: Computing summary statistics from a selection approach

In claycantrell/PartInvShinyUI: Multidimensional Classification Accuracy Analysis Framework

Computing summary statistics from a selection approach

Description

.partit_bvnorm returns a table of selection accuracy indices

Usage

.partit_bvnorm(
  cut1,
  cut2,
  mean1 = 0,
  sd1 = 1,
  mean2 = 0,
  sd2 = 1,
  cor12 = 0,
  cov12 = cor12 * sd1 * sd2
)

Arguments

cut1	Cut score based on the latent score
cut2	Cut score based on the observed score
mean1	Mean of first normal distribution (on x-axis).
sd1	Standard deviation of first normal distribution.
mean2	Mean of second normal distribution (on y-axis).
sd2	Standard deviation of second normal distribution.
cor12	Correlation in the bivariate normal.
cov12	Covariance in the bivariate normal. If not input, compute the covariance using the correlation and the standard deviations.

Value

A table of selection accuracy indices

Examples

## Not run: 
.partit_bvnorm(cut1 = 2, cut2 = 2, mean1 = 0, sd1 = 1, 
               mean2 = 1.53, sd2 = 0.89, cov12 = 0.80)

## End(Not run)

claycantrell/PartInvShinyUI documentation built on March 29, 2022, 9:49 a.m.