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Missing Confounding Data in Marginal Structural Models: A Comparison of Inverse Probability Weighting and Multiple Imputation

Moodie, Erica; Delaney, Joseph; Lefebvre, Geneviève; … - In: International Journal of Biostatistics 4 (2008) 1, pp. 1106-1106

Standard statistical analyses of observational data often exclude valuable information from individuals with incomplete measurements. This may lead to biased estimates of the treatment effect and loss of precision. The issue of missing data for inverse probability of treatment weighted...

Persistent link: https://www.econbiz.de/10005246592

Revisiting the omitted variables argument: Substantive vs. statistical adequacy

Spanos, Aris - In: Journal of Economic Methodology 13 (2006) 2, pp. 179-218

the confounding problem is one of substantive inadequacy in so far as the potential error concerns subject-matter, not … addressing the confounding problem. The paper reframes the omitted variables question into a hypothesis testing problem … effectively with assessing the problem of confounding raised by the omitted variables argument. The assessment of the confouding …

Persistent link: https://www.econbiz.de/10005282282

Health Selection and the Effect of Smoking on Mortality

Adda, Jérôme; Lechene, Valerie - Institute for the Study of Labor (IZA) - 2011

We show that individuals who are in poorer health, independently from smoking, are more likely to start smoking and to smoke more cigarettes than those with better non-smoking health. We present evidence of selection, relying on extensive data on morbidity and mortality. We show that health...

Persistent link: https://www.econbiz.de/10009395437

Orthogonal blocking of regular and nonregular strength-3 designs

SARTONO, Bagus; GOOS, Peter; SCHOEN, Eric D. - Faculteit Toegepaste Economische Wetenschappen, … - 2012

There is currently no general approach to orthogonally block two-level and multi-level orthogonal arrays and mixed-level orthogonal arrays. In this article, we present a mixed integer linear programming approach that seeks an optimal blocking arrangement for any type of regular and nonregular...

Persistent link: https://www.econbiz.de/10010710028

Implementing double-robust estimators of causal effects

Emsley, Richard; Lunt, Mark; Pickles, Andrew; Dunn, GraHam - In: Stata Journal 8 (2008) 3, pp. 334-353

eﬀects such as confounding by allowing for diﬀerent forms of model misspecification; a double-robust estimator also can offer …

Persistent link: https://www.econbiz.de/10005568789

Estimating causal effects with optimization-based methods : a review and empirical comparison

Cousineau, Martin; Verter, Vedat; Murphy, Susan A.; … - In: European journal of operational research : EJOR 304 (2023) 2, pp. 367-380

Persistent link: https://www.econbiz.de/10013534525

Formal covariate benchmarking to bound omitted variable bias

Basu, Deepankar - 2023

Covariate benchmarking is an important part of sensitivity analysis about omitted variable bias and can be used to bound the strength of the unobserved confounder using information and judgments about observed covariates. It is common to carry out formal covariate benchmarking after...

Persistent link: https://www.econbiz.de/10014430784

Health selection and the effect of smoking on mortality

Adda, Jérôme; Lechene, Valérie - In: The Scandinavian journal of economics 115 (2013) 3, pp. 902-931

Persistent link: https://www.econbiz.de/10009778313

Integer programming approaches to find row-column arrangements of two-level orthogonal experimental designs

Nha Vo-Thanh; Goos, Peter; Schoen, Eric D. - 2016

Persistent link: https://www.econbiz.de/10011729923

Symmetry breaking in mixed integer linear programming formulations for blocking two-level orthogonal experimental designs

Nha Vo-Thanh; Jans, Raf; Schoen, Eric D.; Goos, Peter - In: Computers & operations research : and their … 97 (2018), pp. 96-110

Persistent link: https://www.econbiz.de/10011872896