Порівняння методів

	Зважування оберненою ймовірністю для панельних даних	Зважування за оберненою ймовірністю лікування (IPW / IPTW)
Галузь	Причинно-наслідковий висновок	Причинно-наслідковий висновок
Родина	Regression model	Regression model
Рік появи	2000	2000
Автор методу	Robins, Hernan & Brumback	Robins, Hernán & Brumback
Тип	Reweighting / causal inference	Causal inference weighting estimator
Основоположне джерело	Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560.	Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560.
Інші назви	panel IPW, longitudinal IPW, time-varying IPW, panel IPTW	IPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
Пов'язані	5	5
Підсумок	Panel Data Inverse Probability Weighting (panel IPW) estimates the causal effect of a time-varying treatment by reweighting observed units to create a pseudo-population in which treatment is independent of measured confounders at each time point. It extends the cross-sectional IPW framework to longitudinal settings where treatment status and confounders both evolve across multiple periods.	Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.