🚀 Introducing riptw: Revolutionize Your IPTW Analysis in R!
🔍 What is IPTW?
Inverse Probability of Treatment Weighting (IPTW) is a pivotal statistical method for estimating causal effects where randomized trials aren't feasible. It's a game-changer in fields ranging from oncology to broader scientific research, aiming to balance covariates and eliminate confounding biases in observational studies.
📦 Why riptw?
- Minimize Confounding: Attain clearer causal inference by equilibrating covariates.
- Versatility: Applicable in diverse settings and compatible with various analyses.
- Bias Mitigation: Ideal for studies with non-random treatment allocations.
- Enhanced Comparability: Bolsters the validity of treatment-control assessments.
🛠 Installation Made Easy!
Get started with just a few lines of code. Dependencies? Worry not! riptw takes care of them during installation.
📈 Your Results: Insightful & Comprehensive
riptw returns an object with:
- Data: Enhanced with propensity scores, iptw, and standardised weights.
- Unadjusted/Adjusted: Covariate stratification tables, pre and post IPTW.
- Plots: Visualize the impact of IPTW in balancing covariate effects.
🧑💻 Advanced Usage
Customize your analysis further with features like Restricted Cubic Spline transformation and much more!
Ready to transform your R data analysis with riptw? Check out our GitHub repository for more details and examples: https://github.com/cccnrc/riptw
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