Assessing methods for dealing with treatment switching in randomised controlled trials: a simulation study by Latimer Nicholas, Lambert Paul C, Morden James P, Abrams Keith R, Wailoo Allan J

“…These included simple methods which are commonly used in medical literature and may be subject to selection bias if patients switching are not typical of the population as a whole. …”
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On safe post-selection for Bell tests with ideal detectors: Causal diagram approach by Pawel Blasiak, Ewa Borsuk, Marcin Markiewicz

“…This is because conditioning on the outcomes is a source of non-causal correlations, known as a $\textit{selection bias}$, rising doubts whether the conclusion concerns the actual causal process or maybe it is just an effect of processing the data. …”
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A tailored use of the mahalanobis distance matching for causal effects estimation: A simulation study by Lateef Amusa, Delia North, Temesgen Zewotir

“…Selection bias is a fundamental reason why the estimation of treatment effects in observational studies is not as straightforward as in well-designed experiments. …”
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Evaluating the Impact of Large-Scale Agricultural Investments on Household Food Security Using an Endogenous Switching Regression Model by Wegayehu Fitawek, Sheryl L. Hendriks

“…An endogenous switching regression model was adopted to control for a possible selection bias due to unobserved factors. It was found that households with members employed by large-scale agricultural investment companies were more likely larger households headed by younger migrant males holding smaller plots and fewer livestock than non-engaged households. …”
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Near-Optimal A-B Testing by Bhat, Nikhil, Farias, Vivek F, Moallemi, Ciamac C, Sinha, Deeksha

“…In a set of numerical experiments, we demonstrate that our method simultaneously offers better statistical efficiency and less selection bias than state-of-the-art competing biased coin designs.…”
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Implementation of the trial emulation approach in medical research: a scoping review by Giulio Scola, Anca Chis Ster, Daniel Bean, Nilesh Pareek, Richard Emsley, Sabine Landau

“…Different statistical methods were used to address confounding at baseline and selection bias, predominantly conditioning on the confounders (N = 18/49, 37%) and inverse probability of censoring weighting (N = 7/20, 35%) respectively. …”
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Response rates and selection problems, with emphasis on mental health variables and DNA sampling, in large population-based, cross-sectional and longitudinal studies of adolescents... by Lien Lars, Green Kristian, Sagatun Åse, Bjertness Espen, Søgaard Anne, Selmer Randi

“…<p>Abstract</p> <p>Background</p> <p>Selection bias is a threat to the internal validity of epidemiological studies. …”
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Essays in corporate finance and financial institutions by Kolasinski, Adam

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The simulation analysis on the accuracy and efficiency of MIT transaction index by Park, Jungsoo, S. M. Massachusetts Institute of Technology

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A critical appraisal of epidemiological studies comes from basic knowledge: a reader's guide to assess potential for biases by van Duijn Cornelia M, D'Ugo Domenico, Persiani Roberto, La Torre Giuseppe, Boccia Stefania, Ricciardi Gualtiero

“…This review focuses on the concepts of confounding, selection bias and information bias, utilising explanatory examples and simple rules to recognise and, when possible, to correct for them. …”
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The impact of adopting artificial cattle insemination technology by smallholder farmers on their wellbeing: The case of Yem Special District, Ethiopia by Abebe Eshetu Lemma, Mulate Chanie Yitbarek, Endalkachew Kabtamu Mekonen

“…The sensitivity analysis shows that the estimated impact was insensitive to unobserved selection bias.…”
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Assessing the joint effect of population stratification and sample selection in studies of gene-gene (environment) interactions by Cheng KF, Lee JY

“…If the conservative p-value is smaller than the significance level, we can safely claim that the association test is significant regardless of the presence of PS or not, or if there is any selection bias. We also identify conditions for the null bias. …”
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Bias due to sample selection in propensity score matching for a supportive housing program evaluation in New York City. by Sungwoo Lim, Sue M Marcus, Tejinder P Singh, Tiffany G Harris, Amber Levanon Seligson

“…The purpose of the study was to assess potential selection bias using one-to-one greedy matching versus optimal full matching as part of an evaluation of supportive housing in New York City (NYC). …”
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An Empirical Study of Univariate and Genetic Algorithm-Based Feature Selection in Binary Classification with Microarray Data by Michael Lecocke, Kenneth Hess

“…We also find that the univariate approach had higher optimism bias and lower selection bias compared to both GA approaches.…”
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The need for a clinical case definition in test-negative design studies estimating vaccine effectiveness by Sheena G. Sullivan, Arseniy Khvorov, Xiaotong Huang, Can Wang, Kylie E. C. Ainslie, Joshua Nealon, Bingyi Yang, Benjamin J. Cowling, Tim K. Tsang

“…We provide an html tool for researchers to explore site-specific sources of selection bias in their own studies. We recommend all groups consider the potential for selection bias in their vaccine effectiveness studies, particularly when using administrative data.…”
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Adoption and income effects of new agricultural technology on family farms in China. by Fang Wu

“…After controlling for the selection bias, the adoption of new agricultural technologies has a positive and significant impact on family farms' income. …”
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Does Land Transfer Improve Farmers’ Quality of Life? Evidence from Rural China by Qiang He, Xin Deng, Chuan Li, Fangxia Kong, Yanbin Qi

“…As land transfer may be a self-selection behaviour, it may be subject to selection bias such that traditional measurement methods are unable to effectively estimate its quantitative impact. …”
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Exploring causality from observational data: An example assessing whether religiosity promotes cooperation by Daniel Major-Smith

“…Causal inference from observational data is notoriously difficult, and relies upon many unverifiable assumptions, including no confounding or selection bias. Here, we demonstrate how to apply a range of sensitivity analyses to examine whether a causal interpretation from observational data may be justified. …”
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Adoption and income effects of new agricultural technology on family farms in China by Fang Wu

“…After controlling for the selection bias, the adoption of new agricultural technologies has a positive and significant impact on family farms’ income. …”
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Walkable neighborhoods and obesity: Evaluating effects with a propensity score approach by Lori Kowaleski-Jones, Cathleen Zick, Ken R. Smith, Barbara Brown, Heidi Hanson, Jessie Fan

“…Keywords: Obesity, Neighborhood walkability, Propensity score matching, Non-random selection bias, Built environment…”
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