steroid

The standardized mean difference \(y_i\) and standard errors \(se_i\) for seven randomised studies on the use of topical steroids in treatment of chronic rhinosinusitis with nasal polyps.

datasets

A Bayesian data modeling scheme that performs four interconnected tasks: (i) characterizes the uncertainty of the elicited parametric prior; (ii) provides exploratory diagnostic for checking prior-data conflict; (iii) computes the final statistical prior density estimate; and (iv) executes macro- and micro-inference. Primary reference is Mukhopadhyay, S. and Fletcher, D. 2018 paper "Generalized Empirical Bayes via Frequentist Goodness of Fit" (<https://www.nature.com/articles/s41598-018-28130-5 >).

Doug Fletcher

BayesGOF

Bayesian Modeling via Frequentist Goodness-of-Fit

steroid function

A data frame of \((y_i, se_i)\) for \(i = 1,...,7\).<dl class="dl-horizontal">
 <dt><code>y</code></dt><dd>standard mean difference of clinical trials for topical steroids found in the \(i^{th}\) study</dd>
 <dt><code>se</code></dt><dd>standard error of the standard mean difference for the \(i^{th}\) study</dd>
 </dl>

Format

Nasal Steroid Data — steroid

A data frame of \((y_i, se_i)\) for \(i = 1,...,7\).<dl class='dl-horizontal'>
 <dt><code>y</code></dt><dd>standard mean difference of clinical trials for topical steroids found in the \(i^{th}\) study</dd>
 <dt><code>se</code></dt><dd>standard error of the standard mean difference for the \(i^{th}\) study</dd>
 </dl>

steroid: Nasal Steroid Data

Description

Usage

Arguments

Format