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pro vyhledávání: '"Gabriel, Erin"'
When the target of inference is a real-valued function of probability parameters in the k-sample multinomial problem, variance estimation may be challenging. In small samples, methods like the nonparametric bootstrap or delta method may perform poorl
Externí odkaz:
http://arxiv.org/abs/2406.19141
In instrumental variable (IV) settings, such as in imperfect randomized trials and observational studies with Mendelian randomization, one may encounter a continuous exposure, the causal effect of which is not of true interest. Instead, scientific in
Externí odkaz:
http://arxiv.org/abs/2401.17735
Autor:
Gabriel, Erin E, Sachs, Michael C, Waernbaum, Ingeborg, Goetghebeur, Els, Blanche, Paul F, Vansteelandt, Stijn, Sjölander, Arvid, Scheike, Thomas
Recently, it has become common for applied works to combine commonly used survival analysis modeling methods, such as the multivariable Cox model and propensity score weighting, with the intention of forming a doubly robust estimator of an exposure e
Externí odkaz:
http://arxiv.org/abs/2310.16207
Autor:
Gabriel, Erin E, Sachs, Michael C, Martinussen, Torben, Waernbaum, Ingeborg, Goetghebeur, Els, Vansteelandt, Stijn, Sjölander, Arvid
There are now many options for doubly robust estimation; however, there is a concerning trend in the applied literature to believe that the combination of a propensity score and an adjusted outcome model automatically results in a doubly robust estim
Externí odkaz:
http://arxiv.org/abs/2309.05531
The probability of benefit is a valuable and important measure of treatment effect, which has advantages over the average treatment effect. Particularly for an ordinal outcome, it has a better interpretation and can make apparent different aspects of
Externí odkaz:
http://arxiv.org/abs/2305.10555
Strong untestable assumptions are almost universal in causal point estimation. In particular settings, bounds can be derived to narrow the possible range of a causal effect. Symbolic bounds apply to all settings that can be depicted using the same di
Externí odkaz:
http://arxiv.org/abs/2209.03657
Trial level surrogates are useful tools for improving the speed and cost effectiveness of trials, but surrogates that have not been properly evaluated can cause misleading results. The evaluation procedure is often contextual and depends on the type
Externí odkaz:
http://arxiv.org/abs/2208.09869
In randomized trials, once the total effect of the intervention has been estimated, it is often of interest to explore mechanistic effects through mediators along the causal pathway between the randomized treatment and the outcome. In the setting wit
Externí odkaz:
http://arxiv.org/abs/2112.13632
Nonignorable missingness and noncompliance can occur even in well-designed randomized experiments making the intervention effect that the experiment was designed to estimate nonidentifiable. Nonparametric causal bounds provide a way to narrow the ran
Externí odkaz:
http://arxiv.org/abs/2010.05220
A causal query will commonly not be identifiable from observed data, in which case no estimator of the query can be contrived without further assumptions or measured variables, regardless of the amount or precision of the measurements of observed var
Externí odkaz:
http://arxiv.org/abs/2003.10702