Metadata-Version: 2.1
Name: reliability-stability-calc
Version: 0.0.4
Summary: Calculation for relibability and stability three data sets
Home-page: https://github.com/nimh-mbdu/data-reliability-stability
Author: Lily Eisner
Author-email: lillian.eisner@gmail.com
License: UNKNOWN
Description: # Reliability Stability
        
        ## Description
        
        reliability-stability is a simple python package, which takes a csv or other pandas compatable data file and gives the reliability and stability of three columns for test-retest reliability and stability. 
        
        [![nimh-mbdu](https://circleci.com/gh/nimh-mbdu/data-reliability-stability.svg?style=shield)](https://app.circleci.com/pipelines/github/nimh-mbdu/data-reliability-stability)
        
        The reliability and stability calculations, as well as an assumption test, are based on the 1969 paper from Heise, D. R. ['Separating Reliability and Stability in Test-Retest Correlation'](https://doi.org/10.2307/2092790).
        
        ## Installation
        
        pip install reliability stability:
        
        ```
        >>> pip install reliability-stability-calc
        ```
        
        ## Usage
        
        reliability stability is a python package with fuctions defined to: 
        1. calculate correlation between two data columns (calc_correlation)
        2. calculate the test-retest reliability between three data columns (calc_reliability)
        3. calculate the test-retest stability between three data columns (calc_stability)
        4. perform an assumption test with a fourth column (assumption_test)
        5. implement a bootstap test to test assumptions (bootstrap_assumption_test)
        
        Refer to the [documentation](https://github.com/nimh-mbdu/data-reliability-stability/wiki) for more examples and narrative guides.
        
        ## Citations
        
        Heise, D. R. (1969). Separating reliability and stability in test-retest correlation. American Sociological Review, 34(1), 93–101. https://doi.org/10.2307/2092790
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Classifier: Operating System :: POSIX
Description-Content-Type: text/markdown
