ppact

The Pain Program of Active Coping and Training(PPACT) is a large-scale, mixed methods, cluster-randomized trial (CRT) to compare the effectiveness of an integrated, interdisciplinary
program versus usual care in treating patients with chronic pain on long-term opioid treatment (CP-LOT).
The primary outcome is the impact of pain (assessed using the PEGS)

datasets

Implements model-robust standardization for cluster-randomized trials (CRTs). Provides functions that standardize user-specified regression models to estimate marginal treatment effects. The targets include the cluster-average and individual-average treatment effects, with utilities for variance estimation and example simulation datasets. Methods are described in Li, Tong, Fang, Cheng, Kahan, and Wang (2025) <doi:10.1002/sim.70270>.

Changjun Li

MRStdCRT

Model-Robust Standardization in Cluster-Randomized Trials

Jiaqi Tong

Xi Fang

Chao Cheng

Bingkai Wang

Fan Li

ppact function

A data frame with primary outcome, cluster-level, individual level covariates:<dl>
 <dt>SID</dt>
<dd>Study ID</dd> <dt>CLUST</dt>
<dd>Cluster</dd> <dt>INTERVENTION</dt>
<dd>Study arm</dd> <dt>AGE</dt>
<dd>Patient age at randomization</dd> <dt>FEMALE</dt>
<dd>Participant gender</dd> <dt>comorbid</dt>
<dd>Diagnosis of 2 or more of the chronic medical conditions in 6 month prior to randomization</dd> <dt>Dep_OR_Anx</dt>
<dd>Anxiety and/or depression diagnosis in 6 months prior to randomization</dd> <dt>pain_count</dt>
<dd>Number of different pain types from which participants have diagnoses in 12 months prior to randomization</dd> <dt>BL_benzo_flag</dt>
<dd>Benzodiazepine dispensed in 6 months prior to randomization</dd> <dt>BL_avg_daily</dt>
<dd>Average morphine miligram equivalents dose per day in 6 month prior to randomization</dd> <dt>PEGS_bl</dt>
<dd>PEGS score at baseline</dd> <dt>satisfied_primary</dt>
<dd>Satisfaction with primary care services in prior 3 months</dd> <dt>PEGS</dt>
<dd>PEGS score</dd> <dt>n</dt>
<dd>cluster size</dd>
</dl>

Format

Example Dataset: PPACT — ppact

A data frame with primary outcome, cluster-level, individual level covariates:<dl>
 <dt>SID</dt>
<dd>Study ID</dd>

 <dt>CLUST</dt>
<dd>Cluster</dd>

 <dt>INTERVENTION</dt>
<dd>Study arm</dd>

 <dt>AGE</dt>
<dd>Patient age at randomization</dd>

 <dt>FEMALE</dt>
<dd>Participant gender</dd>

 <dt>comorbid</dt>
<dd>Diagnosis of 2 or more of the chronic medical conditions in 6 month prior to randomization</dd>

 <dt>Dep_OR_Anx</dt>
<dd>Anxiety and/or depression diagnosis in 6 months prior to randomization</dd>

 <dt>pain_count</dt>
<dd>Number of different pain types from which participants have diagnoses in 12 months prior to randomization</dd>

 <dt>BL_benzo_flag</dt>
<dd>Benzodiazepine dispensed in 6 months prior to randomization</dd>

 <dt>BL_avg_daily</dt>
<dd>Average morphine miligram equivalents dose per day in 6 month prior to randomization</dd>

 <dt>PEGS_bl</dt>
<dd>PEGS score at baseline</dd>

 <dt>satisfied_primary</dt>
<dd>Satisfaction with primary care services in prior 3 months</dd>

 <dt>PEGS</dt>
<dd>PEGS score</dd>

 <dt>n</dt>
<dd>cluster size</dd>


</dl>

ppact: Example Dataset: PPACT

Description

Usage

Arguments

Format