finasteride

<ul>
<li><code>center</code>: Center ID</li>
<li><code>n1</code>: Number of observations in finasteride group</li>
<li><code>m1</code>: Mean of the change of Boyarsky score from baseline in finasteride group</li>
<li><code>s1</code>: SD of the change of Boyarsky score from baseline in finasteride group</li>
<li><code>n0</code>: Number of observations in placebo group</li>
<li><code>m0</code>: Mean of the change of Boyarsky score from baseline in placebo group</li>
<li><code>s0</code>: SD of the change of Boyarsky score from baseline in placebo group</li>
</ul>

datasets

Computational tools for outlier detection and influence diagnostics in meta-analysis (Noma et al. (2025) <doi:10.1101/2025.09.18.25336125>). Bootstrap distributions of influence statistics are computed, and explicit thresholds for identifying outliers are provided. These methods can also be applied to the analysis of influential centers or regions in multicenter or multiregional clinical trials (Aoki, Noma and Gosho (2021) <doi:10.1080/24709360.2021.1921944>, Nakamura and Noma (2021) <doi:10.5691/jjb.41.117>).

Hisashi Noma

boutliers

Outlier Detection and Influence Diagnostics for Meta-Analysis

Kazushi Maruo

Masahiko Gosho

finasteride function

A data frame with 29 rows and 7 variables

finasteride: A multicenter clinical trial data assessing the treatment effect of finasteride for benign prostatic hyperplasia

Description

Usage

Arguments

Format

References