comparative-effectiveness

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ehsanx / TMLEworkshop
Targeted maximum likelihood estimation (TMLE) enables the integration of machine learning approaches in comparative effectiveness studies. It is a doubly robust method, making use of both the outcome model and propensity score model to generate an unbiased estimate as long as at least one of the models is correctly specified.
tmle machine-learning double robust r workshop-materials g-computation propensity-score comparative-effectiveness ipw inverse-probability-weights code reproducible reproducible-research implementation steps epidemiology statistical-inference medicine conference-workshop
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smartdata-analysis-and-statistics / comparative-effectiveness
Example code for the handbook "Comparative effectiveness and personalized medicine using real-world data"
meta-analysis prediction real-world comparative-effectiveness imputation imputation-methods prediction-model real-world-data real-world-evidence
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ehsanx / TMLEworkshop