Researchers have developed a new framework for addressing selection bias in statistical studies using amortized Bayesian inference. This method embeds the selection mechanism directly into a generative simulator, allowing for debiased estimates without requiring tractable likelihoods. The approach also includes diagnostics to detect bias and assess posterior calibration, demonstrating its effectiveness across various applications where traditional methods fail. AI
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RANK_REASON Academic paper introducing a new statistical inference method.
