# Correlation_and_Agreement_Analysis

**Repository Path**: Yulv-git/Correlation_and_Agreement_Analysis

## Basic Information

- **Project Name**: Correlation_and_Agreement_Analysis
- **Description**: Statistical analysis for correlation (Pearson Correlation) and agreement (Bland-Altman Agreement). Assessing correlation and agreement between two methods of measurement.
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2022-04-23
- **Last Updated**: 2022-06-06

## Categories & Tags

**Categories**: Uncategorized

**Tags**: Pearson-Correlation, Bland-Altman-Agreement, Python, matlab-r, Julia

## README

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 * @Author: Shuangchi He / Yulv
 * @Email: yulvchi@qq.com
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 * @Motto: Entities should not be multiplied unnecessarily.
 * @LastEditors: Shuangchi He
 * @LastEditTime: 2022-04-11 12:19:03
 * @FilePath: /Correlation_and_Agreement_Analysis/README.md
 * @Description: repo. https://github.com/Yulv-git/Correlation_and_Agreement_Analysis
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<h1><center> Statistical Analysis for Correlation and Agreement </h1></center>

    Assessing correlation and agreement between two methods of measurement.

---

- [1. Using](#1-using)
  - [1.1. Python](#11-python)
  - [1.2. Matlab](#12-matlab)
  - [1.3. R](#13-r)
  - [1.4. Julia](#14-julia)
- [2. Correlation](#2-correlation)
- [3. Agreement](#3-agreement)

---

# 1. Using

## 1.1. Python

``` bash
python ./Python/Correlation_Agreement.py \
    --M_predict 0.125 0.95 0.55 0.60 0.78 0.46 0.88 0.50 0.93 0.35 0.975 0.725 0.285 0.166 0.666 0.888 0.233 \
    --M_GT 0.127 0.97 0.53 0.57 0.72 0.49 0.91 0.52 0.90 0.37 0.982 0.718 0.277 0.175 0.666 0.88 0.2333
```

## 1.2. Matlab

``` bash
cd ./Matlab
plot_Pearson_Correlation_Bland_Altman_Agreement([0.125, 0.95, 0.55, 0.60, 0.78, 0.46, 0.88, 0.50, 0.93, 0.35, 0.975, 0.725, 0.285, 0.166, 0.666, 0.888, 0.233], [0.127, 0.97, 0.53, 0.57, 0.72, 0.49, 0.91, 0.52, 0.90, 0.37, 0.982, 0.718, 0.277, 0.175, 0.666, 0.88, 0.2333])
```

## 1.3. R

``` bash
Rscript ./R/Correlation_Agreement.R
```

## 1.4. Julia

``` bash
julia ./Julia/Correlation_Agreement.jl
```

# 2. Correlation

The correlation (Pearson Correlation) test can be used to statistically test the degree of correlation between the measured values of the same object through two measurement methods.

![Measurement_Pearson_Correlation](./Python/Measurement_Pearson_Correlation.png)

Measurement_predict and Measurement_GT have a high correlation (Pearson correlation coefficient of 0.9966).

# 3. Agreement

Agreement (Bland-Altman Agreement) test is a measure of the mean and variance of the measurement values of the same object by two measurement methods.

![Measurement_Bland-Altman_Agreement](./Python/Measurement_Bland-Altman_Agreement.png)

Assuming that the difference between Measurement_predict and Measurement_GT conforms to a normal distribution, the difference between the two measurement methods is distributed within a confidence interval of 0.00145 ± 0.04668 (mm) with 95% confidence. That is, it can be considered that the two measurement methods, Measurement_predict and Measurement_GT, have good Agreement.

---

<font size=4><b><big> Contributing </b></big></font>

If you find any errors, or have any suggestions, please feel free to please feel free to pull requests.