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Alex Luedtke
Researcher at University of Washington
Publications - 95
Citations - 2089
Alex Luedtke is an academic researcher from University of Washington. The author has contributed to research in topics: Estimator & Randomized controlled trial. The author has an hindex of 16, co-authored 86 publications receiving 1379 citations. Previous affiliations of Alex Luedtke include Fred Hutchinson Cancer Research Center & Brown University.
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Journal ArticleDOI
Effect of Dengue Serostatus on Dengue Vaccine Safety and Efficacy
Saranya Sridhar,Alex Luedtke,Edith Langevin,Ming Zhu,Matthew Bonaparte,Tifany Machabert,Stephen Savarino,Betzana Zambrano,Annick Moureau,Alena Khromava,Zoe Moodie,Ted Westling,Cesar Mascareñas,Carina Frago,Margarita Cortés,Danaya Chansinghakul,Fernando Noriega,Alain Bouckenooghe,Josh Chen,Su-Peing Ng,Peter B. Gilbert,Sanjay Gurunathan,Carlos A. DiazGranados +22 more
TL;DR: CYD‐TDV protected against severe VCD and hospitalization for VCD for 5 years in persons who had exposure to dengue before vaccination, and there was evidence of a higher risk of these outcomes in vaccinated people who had not been exposed to d Dengue.
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Statistical inference for the mean outcome under a possibly non-unique optimal treatment strategy
TL;DR: An approach to obtain root-n rate confidence intervals for the optimal value even when the parameter is not pathwise differentiable is described, and conditions under which the estimator is RAL and asymptotically efficient when the mean outcome is path Wise differentiable are provided.
Journal ArticleDOI
Super-Learning of an Optimal Dynamic Treatment Rule.
TL;DR: This work proposes data adaptive estimators of this optimal dynamic two time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment, where the candidate rules are restricted to depend only on a user-supplied subset of the baseline and intermediate covariates.
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Statistical inference for the mean outcome under a possibly non-unique optimal treatment strategy
TL;DR: In this paper, the authors consider the problem of estimating the mean outcome under an individualized treatment strategy defined as the treatment rule that maximizes the population mean outcome, where the candidate treatment rules are restricted to depend on baseline covariates.
Journal ArticleDOI
Suicide prediction models: a critical review of recent research with recommendations for the way forward
Ronald C. Kessler,Robert M. Bossarte,Alex Luedtke,Alex Luedtke,Alan M. Zaslavsky,José R. Zubizarreta +5 more
TL;DR: It is argued that the only way to resolve uncertainty is to link future efforts to develop or evaluate suicide prediction tools with concrete questions about specific clinical decisions aimed at reducing suicides and to evaluate the clinical value of these tools in terms of net benefit rather than sensitivity or positive predictive value.