We propose a new causal parameter, which is a natural extension of existing approaches to causal inference such as marginal structural models. Modelling approaches are proposed for the difference between a treatment-specific counterfactual population distribution and the actual population distribution of an outcome in the target population of interest. Relevant parameters describe the effect of...

This paper develops methods for evaluating marginal policy changes. We characterize how the effects of marginal policy changes depend on the direction of the policy change, and show that marginal policy effects are fundamentally easier to identify and to estimate than conventional treatment parameters. We develop the connection between marginal policy effects and the average effect of treatment...

using a choice experiment survey, the marginal willingness to pay (wtp) among iranian households to avoid power outages is estimated. the results indicate that households prefer lower price of alternatives and the low duration and frequency of outages, and the factors of outage day, outage time and warning in advance of outage are important to households' preferences. moreover, the conditi...

to evaluate the influence of core thickness and fabrication stages on the marginal accuracy of ips e.max press crowns.twenty ips e.max press crowns, 1.5mm thick, were fabricated on metal dies. the crowns had two different core thicknesses, 0.8mm for group a and 1mm for group b, ten for each group. marginal gap was measured after each stage of core fabrication, veneering and glaze firing. the sp...

BACKGROUND Insomnia symptoms are associated with type 2 diabetes incidence but are also associated with a range of potential time-varying covariates which may confound and/or mediate associations. We aimed to assess whether cumulative exposure to insomnia symptoms has a causal effect on type 2 diabetes incidence. METHODS A prospective cohort study in the West of Scotland, following respondent...

Multi-marker methods for genetic association analysis can be performed for common and low frequency SNPs to improve power. Regression models are an intuitive way to formulate multi-marker tests. In previous studies we evaluated regression-based multi-marker tests for common SNPs, and through identification of bins consisting of correlated SNPs, developed a multi-bin linear combination (MLC) tes...

BACKGROUND Clustered data with binary outcomes are often analysed using random intercepts models or generalised estimating equations (GEE) resulting in cluster-specific or 'population-average' inference, respectively. METHODS When a random effects model is fitted to clustered data, predictions may be produced for a member of an existing cluster by using estimates of the fixed effects (regress...