Suppose that having established a marginal total effect of a point exposure on a time-to-event outcome, an investigator wishes to decompose this effect into its direct and indirect pathways, also known as natural direct and indirect effects, mediated by a variable known to occur after the exposure and prior to the outcome. This paper proposes a theory of estimation of natural direct and indirec...

One can fruitfully approach survival problems without covariates in an actuarial way. In narrow time bins, the number of people at risk is counted together with the number of events. The relationship between time and probability of an event can then be estimated with a parametric or semi-parametric model. The number of events observed in each bin is described using a Poisson distribution with t...

This paper analyzes the impact of childbearing history on later-life mortality for ever-married men and women using high-quality historical longitudinal microlevel data for southern Sweden. The main advantage of using historical data is that it makes it possible to investigate the experience of many birth cohorts with medium to high fertility, thereby facilitating estimation of the effects of t...

According to the article[2], we present a new method for post-selection inference for l1(lasso)penalized likelihood models, including generalized regression models. Our approach generalizes the post-selection framework presented in Lee et al. (2013)[1]. The method provides P-values and confidence intervals that are asymptotically valid, conditional on the inherent selection done by the lasso. W...

Model. The primary exposure variable was a time­varying covariate that indicated whether a beneficiary had expe­ rienced an interruption of Medicaid coverage in the prior month. Confounders adjusted for in the model included demographic characteristics, type of Medicaid coverage (ie, Temporary Assistance to Needy Families [TANF], Supple­ mental Security Income [SSI], or other), non­Medicaid for...

In this paper we consider nonlinear models with an arbitrary number of covariates for which the information additionally depends on the value of the linear predictor. We establish the general result that for many optimality criteria the support points of an optimal design lie on the edges of the design region, if this design region is a polyhedron. Based on this result we show that under certai...

Currently, for a variety of mechatronic systems and components, sufficient failure behaviour data are not available. Endurance tests at customer-specific operating conditions provide manufacturers with specific failure time data. However, they are timeconsuming and expensive. Findings gained through experiments are valid only for the applied test conditions and loads. On the other hand, develop...

1. (a) Partial likelihood estimates of the coefficients in the proportional hazards model using , are shown below with standard errors. Those results suggest that, after adjusting for effects of the other variables in the model, patient-donor age interaction ( ), low risk for acute myelotic leukemia ( ) and the FAB morphology score ( ) have significant associations with disease free survival. 1...

First hitting time models are a technique of modeling a stochastic process as it approaches or avoids a boundary, also known as a threshold. The process itself may be unobservable, making this a difficult problem. Regression techniques, however, can be employed to model the data as it compares to the threshold, creating a class of first hitting time models called threshold regression models. Su...

In this article, we show the general relation between standardization methods and marginal structural models. Standardization has been recognized as a method to control confounding and to estimate causal parameters of interest. Because standardization requires stratification by confounders, the sparse-data problem will occur when stratified by many confounders and one then might have an unstabl...