trial_data

Generated with logistic regression model:
 $$logit(P(Y_{ij} = 1 | gender_i, age_{i1}, age_{i2})) = 3*gender_i +3*age_{i1} +3*age_{i2}$$
The data frame can be used to run GLM clinical trial example in Huang, Tong, Yang (2023)

datasets

In the context of paid research studies and clinical trials, budget considerations and patient sampling from available populations are subject to inherent constraints. We introduce the 'CDsampling' package, which integrates optimal design theories within the framework of constrained sampling. This package offers the possibility to find both D-optimal approximate and exact allocations for samplings with or without constraints. Additionally, it provides functions to find constrained uniform sampling as a robust sampling strategy with limited model information. Our package offers functions for the computation of the Fisher information matrix under generalized linear models (including regular linear regression model) and multinomial logistic models.To demonstrate the applications, we also provide a simulated dataset and a real dataset embedded in the package. Yifei Huang, Liping Tong, and Jie Yang (2025)<doi:10.5705/ss.202022.0414>.

Yifei Huang

CDsampling

Constrained Sampling in Paid Research Studies

Liping Tong

Jie Yang

trial_data function

A data frame with 500 rows and 6 variables:<dl>
 <dt>gender</dt>
<dd>gender of the patients</dd> <dt>age_1</dt>
<dd>1 or 0, whether or not the patient belongs to 18-25 age group</dd> <dt>age_2</dt>
<dd>1 or 0, whether or not the patient belongs to 26-64 age group</dd> <dt>label</dt>
<dd>stratification group in terms of gender and age, 1 to 6</dd> <dt>Y</dt>
<dd>treatment effective or not, Y=1 means treatment is effective to the patient</dd> <dt>ID</dt>
<dd>patient ID, 1-500</dd>
</dl>

Format

Generated clinical trial data with binary response — trial_data

A data frame with 500 rows and 6 variables:<dl>
 <dt>gender</dt>
<dd>gender of the patients</dd>

 <dt>age_1</dt>
<dd>1 or 0, whether or not the patient belongs to 18-25 age group</dd>

 <dt>age_2</dt>
<dd>1 or 0, whether or not the patient belongs to 26-64 age group</dd>

 <dt>label</dt>
<dd>stratification group in terms of gender and age, 1 to 6</dd>

 <dt>Y</dt>
<dd>treatment effective or not, Y=1 means treatment is effective to the patient</dd>

 <dt>ID</dt>
<dd>patient ID, 1-500</dd>


</dl>

trial_data: Generated clinical trial data with binary response

Description

Usage

Arguments

Format

Examples