Assuming a prior Standard (two-parameter) Beta Distribution, returns the expected mean of the distribution under the assumption that the observed value is the most likely value of the distribution.

Package providing a number of functions for working with Two- and
Four-parameter Beta and closely related distributions (i.e., the Gamma-
Binomial-, and Beta-Binomial distributions).
Includes, among other things:
- d/p/q/r functions for Four-Parameter Beta distributions and Generalized
"Binomial" (continuous) distributions, and d/p/r- functions for Beta-
Binomial distributions.
- Moment generating functions for Binomial distributions, Beta-Binomial
distributions, and observed value distributions.
- Functions for estimating classification accuracy and consistency,
making use of the Classical Test-Theory based 'Livingston and Lewis' (L&L)
and 'Hanson and Brennan' approaches.
A shiny app is available, providing a GUI for the L&L approach when used
for binary classifications. For url to the app, see documentation for the
LL.CA() function.
Livingston and Lewis (1995) <doi:10.1111/j.1745-3984.1995.tb00462.x>.
Lord (1965) <doi:10.1007/BF02289490>.
Hanson (1991) <https://files.eric.ed.gov/fulltext/ED344945.pdf>.

Haakon Haakstad

betafunctions

Functions for Working with Two- And Four-Parameter Beta
Probability Distributions and Psychometric Analysis of
Classifications

MLM function

<dl><dt>alpha</dt>
<dd>Observed alpha value for fitted Standard Beta PDD.</dd>
<dt>beta</dt>
<dd>Observed beta value for fitted Standard Beta PDD.</dd>
<dt>x</dt>
<dd>Observed proportion-correct outcome.</dd>
<dt>n</dt>
<dd>Test-length.</dd></dl>

Arguments

Most Likely Mean of the Standard Beta PDD, Given that the Observation is Considered the Most Likely Observation of the Standard Beta PDD (i.e., the mode). — MLM

<dl>

<dt>alpha</dt>
<dd>Observed alpha value for fitted Standard Beta PDD.</dd>


<dt>beta</dt>
<dd>Observed beta value for fitted Standard Beta PDD.</dd>


<dt>x</dt>
<dd>Observed proportion-correct outcome.</dd>


<dt>n</dt>
<dd>Test-length.</dd>

</dl>

Most Likely Mean of the Standard Beta PDD, Given that the Observation is Considered the Most Likely Observation of the Standard Beta PDD (i.e., the mode).

MLM: Most Likely Mean of the Standard Beta PDD, Given that the Observation is Considered the Most Likely Observation of the Standard Beta PDD (i.e., the mode).

Description

Usage

Value

Arguments

Examples