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Assumption-lean inference for generalised linear model parameters

Assumption-lean inference for generalised linear model parameters

15 June 2020
S. Vansteelandt
O. Dukes
    CML
ArXivPDFHTML

Papers citing "Assumption-lean inference for generalised linear model parameters"

16 / 16 papers shown
Title
Debiasing Synthetic Data Generated by Deep Generative Models
Debiasing Synthetic Data Generated by Deep Generative Models
A. Decruyenaere
Heidelinde Dehaene
Paloma Rabaey
Christiaan Polet
Johan Decruyenaere
Thomas Demeester
S. Vansteelandt
AI4CE
31
0
0
06 Nov 2024
Assumption-Lean Post-Integrated Inference with Negative Control Outcomes
Assumption-Lean Post-Integrated Inference with Negative Control Outcomes
Jin-Hong Du
Kathryn Roeder
Larry Wasserman
39
1
0
07 Oct 2024
Non-parametric efficient estimation of marginal structural models with
  multi-valued time-varying treatments
Non-parametric efficient estimation of marginal structural models with multi-valued time-varying treatments
Axel Martin
Michele Santacatterina
Iván Díaz
26
1
0
27 Sep 2024
Substitute adjustment via recovery of latent variables
Substitute adjustment via recovery of latent variables
Jeffrey Adams
Niels Richard Hansen
CML
24
1
0
01 Mar 2024
On the role of parametrization in models with a misspecified nuisance
  component
On the role of parametrization in models with a misspecified nuisance component
Heather Battey
Nancy Reid
18
0
0
08 Feb 2024
Optimally weighted average derivative effects
Optimally weighted average derivative effects
Oliver Hines
Karla Diaz-Ordaz
S. Vansteelandt
CML
26
2
0
10 Aug 2023
Sandwich Boosting for Accurate Estimation in Partially Linear Models for
  Grouped Data
Sandwich Boosting for Accurate Estimation in Partially Linear Models for Grouped Data
Elliot H. Young
Rajen Dinesh Shah
24
1
0
21 Jul 2023
Efficient and Multiply Robust Risk Estimation under General Forms of
  Dataset Shift
Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shift
Hongxiang Qiu
E. T. Tchetgen
Yan Sun
OOD
15
7
0
28 Jun 2023
Semiparametric posterior corrections
Semiparametric posterior corrections
Andrew Yiu
Edwin Fong
Chris Holmes
Judith Rousseau
41
3
0
09 Jun 2023
Using Imperfect Surrogates for Downstream Inference: Design-based
  Supervised Learning for Social Science Applications of Large Language Models
Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models
Naoki Egami
Musashi Jacobs-Harukawa
Brandon M Stewart
Hanying Wei
24
15
0
07 Jun 2023
Semiparametric efficient estimation of genetic relatedness with machine
  learning methods
Semiparametric efficient estimation of genetic relatedness with machine learning methods
Xu Guo
Yiyuan Qian
Hongwei Shi
Weichao Yang
Niwen Zhou
19
0
0
04 Apr 2023
Nonparametric Estimation of Conditional Incremental Effects
Nonparametric Estimation of Conditional Incremental Effects
Alec McClean
Zach Branson
Edward H. Kennedy
CML
20
8
0
07 Dec 2022
Combinatorial Causal Bandits
Combinatorial Causal Bandits
Shi Feng
Wei Chen
CML
19
13
0
04 Jun 2022
Parameterising the effect of a continuous exposure using average
  derivative effects
Parameterising the effect of a continuous exposure using average derivative effects
Oliver Hines
Karla Diaz-Ordaz
S. Vansteelandt
14
10
0
27 Sep 2021
Demystifying statistical learning based on efficient influence functions
Demystifying statistical learning based on efficient influence functions
Oliver Hines
O. Dukes
Karla Diaz-Ordaz
S. Vansteelandt
TDI
19
110
0
01 Jul 2021
Estimating heterogeneous treatment effects with right-censored data via
  causal survival forests
Estimating heterogeneous treatment effects with right-censored data via causal survival forests
Yifan Cui
Michael R. Kosorok
Erik Sverdrup
Stefan Wager
Ruoqing Zhu
CML
22
67
0
27 Jan 2020
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