estimate_singleThresh_WOLS

Implements the formula \( c_i = \mu + \sigma * \Phi^{-1}(1 - p_i^{obs}) \)
in a weighted least-squares sense, with weights = \(n_i\).

Provides likelihood-based and hierarchical estimation methods
for thresholded (binomial-probit) data. Supports fixed-mean and random-mean
models with maximum likelihood estimation (MLE), generalized linear mixed model
(GLMM), and Bayesian Markov chain Monte Carlo (MCMC) implementations.
For methodological background, see Albert and Chib (1993)
<doi:10.1080/01621459.1993.10476321> and McCulloch (1994)
<doi:10.2307/2297959>.

Zhaoze Liu

bin2norm

Hierarchical Probit Estimation for Dichotomized Data

estimate_singleThresh_WOLS function

<dl><dt>n_i</dt>
<dd>numeric vector</dd>
<dt>c_i</dt>
<dd>numeric vector</dd>
<dt>p_i_obs</dt>
<dd>numeric vector</dd></dl>

Arguments

Weighted OLS (Initial value in Single Threshold per Study MLE) — estimate_singleThresh_WOLS

<dl>

<dt>n_i</dt>
<dd>numeric vector</dd>


<dt>c_i</dt>
<dd>numeric vector</dd>


<dt>p_i_obs</dt>
<dd>numeric vector</dd>

</dl>

estimate_singleThresh_WOLS: Weighted OLS (Initial value in Single Threshold per Study MLE)

Description

Usage

Value

Arguments