Choose the Cox proportional hazards regression model if the values in your dependent variable are duration observations. The advantage of the semi-parametric Cox proportional hazards model over fully parametric models such as the exponential or Weibull models is that it makes no assumptions about the shape of the baseline hazard. The model only requires the proportional hazards assumption that ...

Methods We evaluated 153 patients (28males) diagnosed younger than 20 years old, managed during 1980 through 2013 (median 7.0 years of duration). Good or poor outcome (persistence or recurrence) was analyzed in 126 patients followed for at least 12 months. Predictors for recurrence were analyzed among 108 pediatric PTC patients. Adult PTC patients (n = 3093) were finally included in Cox proport...

Purpose – Most current condition-based maintenance (CBM) systems using proportional hazards model (PHM) assume that enough historical data are available. However, in many practical cases, it is usually costly to collect much historical data prior to real practice (model implementation). This paper aims to focus on the necessity and benefits of updating a PHM with new samples generated in the pr...

We introduce the R package CPHshape, which computes the effect parameters and the nonparametric maximum likelihood estimator of a shape constrained baseline hazard in the Cox proportional hazards model. The functionality of the package is illustrated using reproducible examples which are based on simulated data.

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...