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Progression Models for Repeated Measures

PMRM 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

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# ⚠️ IMPORTANT: This package has been superseded

**This repository is no longer under active development.**  
The functionality has been **fully replaced by the newer, more efficient, and actively maintained package `pmrm`.**

👉 **Please use `pmrm` instead of `PMRM` for all new work.**

## 📦 New package: pmrm ✅

- **GitHub:** https://github.com/openpharma/pmrm  
- **CRAN:** Available on CRAN under the name **`pmrm`**

### Installation

Install the released version directly from CRAN:

```r
install.packages("pmrm")
````

# Progression Models for Repeated Measures

This repository contains code for fitting some of the models described in

Raket, Lars Lau. "Progression models for repeated measures: Estimating novel treatment effects in progressive diseases." (2022).

The models enable time-quantifications of treatment effects in clinical trials (e.g. 20% slowing of time-progression or 6 months delay of progression after 2 years of treatment).

Example 1
--------------------
In the example below, a treatment effect resulting in 20% slowing of time-progression of disease was simulated. The results of the MMRM, Proportional decline PMRM, Time-PMRM and Proportional slowing Time-PMRM are shown. Only small differences can be observed between the different models and the Proportional slowing Time-PMRM model had the lowest AIC.

![](https://raw.githubusercontent.com/larslau/PMRM/main/img/ill1.png)

Example 2
--------------------
In the example below, a treatment effect resulting in accelerated slowing of time-progression of disease was simulated. The results of the MMRM and Time-PMRM can both model this treatment effect, while the constraints of the Proportional decline PMRM and Proportional slowing Time-PMRM does not fully allow modeling of this treatment effect and thus finds the closest alternative.

![](https://raw.githubusercontent.com/larslau/PMRM/main/img/ill2.png)

PMRM

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