gen_binomial_anticoef

Generates Binomial Anticipated Coefficients
Solves the logistic function
log(p / (1-p)) = beta0 + beta1 * x
such that p = lowprob when x = -1, and p = highprob when x = +1.
Equivalently, solves this set of equations for beta0 and beta1:
log(lowprob / (1 - lowprob)) = beta0 - beta1
log(highprob / (1 - highprob)) = beta0 + beta1

internal

Generates and evaluates D, I, A, Alias, E, T, and G optimal designs. Supports generation and evaluation of blocked and split/split-split/.../N-split plot designs. Includes parametric and Monte Carlo power evaluation functions, and supports calculating power for censored responses. Provides a framework to evaluate power using functions provided in other packages or written by the user. Includes a Shiny graphical user interface that displays the underlying code used to create and evaluate the design to improve ease-of-use and make analyses more reproducible. For details, see Morgan-Wall et al. (2021) <doi:10.18637/jss.v099.i01>.

Tyler Morgan-Wall

skpr

Design of Experiments Suite: Generate and Evaluate Optimal
Designs

George Khoury

gen_binomial_anticoef function

<dl><dt>anticoef</dt>
<dd>Anticipated coefficients</dd>
<dt>lowprob</dt>
<dd>Default 0.50. The base probability</dd>
<dt>highprob</dt>
<dd>Default 0.80. The high probability</dd></dl>

Arguments

Generates Binomial Anticipated Coefficients — gen_binomial_anticoef

<dl>

<dt>anticoef</dt>
<dd>Anticipated coefficients</dd>


<dt>lowprob</dt>
<dd>Default 0.50. The base probability</dd>


<dt>highprob</dt>
<dd>Default 0.80. The high probability</dd>

</dl>

gen_binomial_anticoef: Generates Binomial Anticipated Coefficients

Description

Usage

Value

Arguments