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The Heckman selection model is one of the most well-renounced econometric models in the analysis of data with sample selection. This model is designed to rectify sample selection biases based on the assumption of bivariate normal error…

Methodology · Statistics 2025-11-26 Heeju Lim , Jose Alejandro Ordonez , Victor H. Lachos , Antonio Punzo

Many proposals have emerged as alternatives to the Heckman selection model, mainly to address the non-robustness of its normal assumption. The 2001 Medical Expenditure Panel Survey data is often used to illustrate this non-robustness of the…

Methodology · Statistics 2021-04-02 Fernando de S. Bastos , Wagner Barreto-Souza , Marc G. Genton

Two-phase sampling designs are frequently employed in epidemiological studies and large-scale health surveys. In such designs, certain variables are exclusively collected within a second-phase random subsample of the initial first-phase…

Methodology · Statistics 2024-03-25 Lingxiao Wang

The sample selection bias problem arises when a variable of interest is correlated with a latent variable, and involves situations in which the response variable had part of its observations censored. Heckman (1976) proposed a sample…

Methodology · Statistics 2022-06-22 Helton Saulo , Roberto Vila , Shayane S. Cordeiro

In a clinical trial of a treatment for alcoholism, a common response variable of interest is the number of alcoholic drinks consumed by each subject each day, or an ordinal version of this response, with levels corresponding to abstinence,…

Applications · Statistics 2010-10-08 Kenneth E. Shirley , Dylan S. Small , Kevin G. Lynch , Stephen A. Maisto , David W. Oslin

Selection bias is a common concern in epidemiologic studies. In the literature, selection bias is often viewed as a missing data problem. Popular approaches to adjust for bias due to missing data, such as inverse probability weighting, rely…

The Heckman selection model is widely used in econometric analysis and other social sciences to address sample selection bias in data modeling. A common assumption in Heckman selection models is that the error terms follow an independent…

Methodology · Statistics 2026-02-09 Heeju Lim , Victor E. Lachos , Victor H. Lachos

Under missing-not-at-random (MNAR) sample selection bias, the performance of a prediction model is often degraded. This paper focuses on one classic instance of MNAR sample selection bias where a subset of samples have non-randomly missing…

Machine Learning · Computer Science 2024-04-23 Huy Mai , Xintao Wu

Heckman selection model is perhaps the most popular econometric model in the analysis of data with sample selection. The analyses of this model are based on the normality assumption for the error terms, however, in some applications, the…

Methodology · Statistics 2020-06-16 Victor H. Lachos Davila , Marcos O. Prates , Dipak K. Dey

We develop a distribution regression model with a censored selection rule, offering a semi-parametric generalization of the Heckman selection model. Our approach applies to the entire distribution, extending beyond the mean or median,…

Econometrics · Economics 2025-05-19 Ivan Fernandez-Val , Seoyun Hong

Prior to clinical applications, it is critical that risk prediction models are evaluated in independent studies that did not contribute to model development. While prospective cohort studies provide a natural setting for model validation,…

Methodology · Statistics 2017-10-13 Parichoy Pal Choudhury , Anil K. Chaturvedi , Nilanjan Chatterjee

Surveys are commonly used to facilitate research in epidemiology, health, and the social and behavioral sciences. Often, these surveys are not simple random samples, and respondents are given weights reflecting their probability of…

Methodology · Statistics 2024-08-20 Adway S. Wadekar , Jerome P. Reiter

This paper studies multiparty learning, aiming to learn a model using the private data of different participants. Model reuse is a promising solution for multiparty learning, assuming that a local model has been trained for each party.…

Machine Learning · Computer Science 2023-05-24 Anke Tang , Yong Luo , Han Hu , Fengxiang He , Kehua Su , Bo Du , Yixin Chen , Dacheng Tao

Aims: A common objective of epidemiological surveys is to provide population-level estimates of health indicators. Survey results tend to be biased under selective non-participation. One approach to bias reduction is to collect information…

The two-sample problem, which consists in testing whether independent samples on $\mathbb{R}^d$ are drawn from the same (unknown) distribution, finds applications in many areas. Its study in high-dimension is the subject of much attention,…

Statistics Theory · Mathematics 2023-02-09 Stephan Clémençon , Myrto Limnios , Nicolas Vayatis

This paper addresses the critical issue of sample selection bias in cross-country comparisons based on international assessments such as the Programme for International Student Assessment (PISA). Although PISA is widely used to benchmark…

Econometrics · Economics 2025-10-08 Onil Boussim

The aim of this study is to look at predicting whether a person will complete a drug and alcohol rehabilitation program and the number of times a person attends. The study is based on demographic data obtained from Substance Abuse and…

Machine Learning · Computer Science 2024-04-25 Karen Roberts-Licklider , Theodore Trafalis

Rich meta-epidemiological data sets have been collected to explore associations between intervention effect estimates and study-level characteristics. Welton et al. proposed models for the analysis of meta-epidemiological data, but these…

Applications · Statistics 2017-11-28 Kirsty Rhodes , David Mawdsley , Rebecca Turner , Hayley Jones , Jelena Savovic , Julian Higgins

We consider planning longitudinal covariate measurements in follow-up studies where covariates are time-varying. We assume that the entire cohort cannot be selected for longitudinal measurements due to financial limitations and study how a…

Methodology · Statistics 2024-07-03 Jaakko Reinikainen , Juha Karvanen

Heckman selection model is the most popular econometric model in analysis of data with sample selection. However, selection models with Normal errors cannot accommodate heavy tails in the error distribution. Recently, Marchenko and Genton…

Computation · Statistics 2014-01-08 Peng Ding
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