Results 11 to 20 of about 269 (169)
A fundamental measure of treatment effect heterogeneity
Journal of Causal Inference, 2021 The stratum-specific treatment effect function is a random variable giving the average treatment effect (ATE) for a randomly drawn stratum of potential confounders a clinician may use to assign treatment.
Levy Jonathan +3 more
doaj +1 more source
Identification of causal intervention effects under contagion
Journal of Causal Inference, 2021 Defining and identifying causal intervention effects for transmissible infectious disease outcomes is challenging because a treatment – such as a vaccine – given to one individual may affect the infection outcomes of others. Epidemiologists have proposed
Cai Xiaoxuan +2 more
doaj +1 more source
Statistics of Extremes under Random Censoring [PDF]
, 2006 AMS classifications: 62G05; 62G20; 62G32 ...
John H. J. Einmahl +5 more
core +2 more sources
Trimmed means for functional data [PDF]
, 2001 Data depth, functional data, trimmed means estimates, 62G07, 62G05,
Fraiman, Ricardo +3 more
core +1 more source
Bootstrap variance estimation for Nadaraya quantile estimator [PDF]
, 2009 Nadaraya quantile estimator, Order-calibration, Smoothed bootstrap, 62G05, 62G09, 62G30,
Cheung, KY +5 more
core +1 more source
Large deviations for exchangeable observations with applications
International Journal of Mathematics and Mathematical Sciences, Volume 2004, Issue 55, Page 2947-2958, 2004., 2004 We first prove some large deviation results for a mixture of i.i.d. random variables. Compared with most of the known results in the literature, our results are built on relaxing some restrictive conditions that may not be easy to be checked in certain typical cases.
Jinwen Chen
wiley +1 more source
Empirical likelihood for quantile regression models with response data missing at random
Open Mathematics, 2017 This paper studies quantile linear regression models with response data missing at random. A quantile empirical-likelihood-based method is proposed firstly to study a quantile linear regression model with response data missing at random.
Luo S., Pang Shuxia
doaj +1 more source
International Journal of Stochastic Analysis, Volume 15, Issue 3, Page 207-219, 2002., 2002 In this paper we are concerned with the heteroscedastic regression model yi = xiβ + g(ti) + σiei, 1 ≤ i ≤ n under correlated errors ei, where it is assumed that σi2=f(ui), the design points (xi, ti, ui) are known and nonrandom, and g and f are unknown functions. The interest lies in the slope parameter β.
Han-Ying Liang, Bing-Yi Jing
wiley +1 more source
Minimally capturing heterogeneous complier effect of endogenous treatment for any outcome variable
Journal of Causal Inference, 2023 When a binary treatment DD is possibly endogenous, a binary instrument δ\delta is often used to identify the “effect on compliers.” If covariates XX affect both DD and an outcome YY, XX should be controlled to identify the “XX-conditional complier ...
Lee Goeun +2 more
doaj +1 more source
Nonparametric density estimators based on nonstationary absolutely regular random sequences
International Journal of Stochastic Analysis, Volume 9, Issue 3, Page 233-254, 1996., 1995 In this paper, the central limit theorems for the density estimator and for the integrated square error are proved for the case when the underlying sequence of random variables is nonstationary. Applications to Markov processes and ARMA processes are provided.
Michel Harel, Madan L. Puri
wiley +1 more source