Metadata-Version: 2.4
Name: scia
Version: 1.3.2
Summary: A Comprehensive most updated Python package for Single Case Design Analysis
Home-page: https://github.com/Ahsankhodami/scia
Author: Mohammad Ahsan Khodami
Author-email: Mohammad Ahsan Khodami <ahsan.khodami@gmail.com>
Project-URL: Homepage, https://github.com/Ahsankhodami/scia
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: scipy
Requires-Dist: openpyxl
Requires-Dist: scikit-learn
Requires-Dist: statsmodels
Dynamic: author
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python

# scia

scia is a robust Python package dedicated to single-case data analysis. Designed for researchers and practitioners working with single-case experimental designs.

**scia** provides a comprehensive suite of statistical methods to analyze, interpret, and report data effectively. The package includes functionality to create and preprocess single-case data frames, fill in missing values, filter data, and compute key non-overlap and effect size metrics. Advanced methods for evaluating treatment effects and trends are available through functions such as autocorr for autocorrelation analysis and bayesplm for Bayesian piecewise linear regression. Additional tools like pnd, pem, pet, nap, pand, ird, tau_u, and corrected_tau offer further analytical capabilities to support rigorous, data-driven decision making.

-Documentation is on going and reading, please be patient with it.

For full documentation, please visit our [Documentation](https://ahsankhodami.github.io/scia/rci.html) 🚀📚
