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...

In this article, we illustrate the command distrate, which calcu- lates age-standardized rates with efficient interval estimation by using formulas developed by Tiwari, Clegg, and Zou (2006, Statistical Methods in Medical Re- search 15: 547–569) as a modification of the method proposed by Fay...

Marginal structural models (MSM) provide a powerful tool for estimating the causal effect of a treatment. These models, introduced by Robins (e.g. Robins (2000a), Robins (2000b), van der Laan and Robins (2002)), model the marginal distributions of treatment-specific counterfactual outcomes,...

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...

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...