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We Need Subject Matter Expertise to Choose and Identify Causal Estimands: Comment on "Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event"

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Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

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Many research questions concern treatment effects on outcomes that can recur several times in the same individual. For example, medical researchers are interested in treatment effects on hospitalizations in heart failure patients and sports injuries in ath ...

SPRINGER2023

We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...

EPFL2022

Statistical limits of high-dimensional inference problems

Clément Dominique Luneau

This thesis focuses on two kinds of statistical inference problems in signal processing and data science. The first problem is the estimation of a structured informative tensor from the observation of a noisy tensor in which it is buried. The structure com ...

EPFL2021

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This paper reports the results of an international benchmark exercise on the measurement of fibre bed compaction behaviour. The aim was to identify aspects of the test method critical to obtain reliable results and to arrive at a recommended test procedure ...

2021

DBnorm as an R package for the comparison and selection of appropriate statistical methods for batch effect correction in metabolomic studies

Nicolas Jean Philippe Guex, Murielle Bochud, Cristian Carmeli, Aurélien Thomas, Tiziana Caputo

As a powerful phenotyping technology, metabolomics provides new opportunities in biomarker discovery through metabolome-wide association studies (MWAS) and the identification of metabolites having a regulatory effect in various biological processes. While ...

2021

A causal framework for classical statistical estimands in failure-time settings with competing events

Mats Julius Stensrud

In failure-time settings, a competing event is any event that makes it impossible for the event of interest to occur. For example, cardiovascular disease death is a competing event for prostate cancer death because an individual cannot die of prostate canc ...

2020

Statistical methods for inference on spatial extremes of large datasets are yet to be developed. Motivated by standard dimension reduction techniques used in spatial statistics, we propose an approach based on empirical basis functions to explore and model ...

SPRINGER2019

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Meteorological conditions, gas-phase precursors, and aerosol acidity (pH) can influence the formation of secondary inorganic aerosols (SIA) in fine particulate matter (PM2.5). Most works related to the influence of pH and gas-phase precursors on SIA have b ...

Elsevier B.V.2019

The participants in randomized trials and other studies used for causal inference are often not representative of the populations seen by clinical decision-makers. To account for differences between populations, researchers may consider standardizing resul ...

2019