RESEARCHDESIGNANDMETHODSdUsing claims data from a nationwide statutory health insurance fund (Gmünder ErsatzKasse), we assessed all deaths in a cohort of 5,757 patients with a first stroke between 2005 and 2007 (69.3% male, mean age 68.1 years, 32.2% with diabetes) up to 2009. By use of Cox regression, we estimated time-dependent hazard ratios (HRs) to compare patients with and without diabetes...

Objective: The objective of this project was to valuate impact of a standardized order set on quality and financial performance. Methods: We conducted an observational study to examine order set use by hospital, discharge month, severity of illness and risk of mortality for pneumonia patients between March 2006 and September 2007. We also assessed impact on in-hospital mortality and 30-day read...

BACKGROUND Most randomized controlled trials with a time-to-event outcome are designed and analysed under the proportional hazards assumption, with a target hazard ratio for the treatment effect in mind. However, the hazards may be non-proportional. We address how to design a trial under such conditions, and how to analyse the results. METHODS We propose to extend the usual approach, a logran...

The objective of hazards (lifetime) analysis is to advance and promote statistical science in the various applied fields that deal with lifetime (survival) data including: actuarial science and reliability engineering. The lifetime data analysis provides special techniques that are required to compare the risks for failure. Bayesian semi-parametric methods have been applied to survival analysis...

Background: Aspirin reduces risk of colorectal neoplasia in randomized trials and epidemiological studies and inhibits tumor growth and metastases in animal models. However, the influence of aspirin on survival after diagnosis of colorectal cancer is unknown. Methods: Among 1288 participants diagnosed with Stage I, II, or III colorectal cancer enrolled in two cohorts, we used Cox proportional h...

This paper explores how mortality is related to such socio-economic factors as education, occupation, skill level and income for the years 1992-1997 using an extensive sample of the Danish population. We employ a competing risks proportional hazard model to allow for different causes of death. This method is important as some factors have unequal (and sometimes opposite) influence on the cause-...

In this paper the effect of age, educational level, occupational group and regional labour market conditions on the probability of leaving the state of unemployment is estimated. We use a proportional hazard model based on aggregate data on incomplete spells of unemployment for males in the Netherlands. Effects of omitted variables and time dependence are studied in combination with a non-const...

Survival analysis is widely used in mechanical research, engineering and many other fields. This paper introduces the properties and modeling methods for survival data, then fits a Cox Proportional Hazards Model for stock data in the Shanghai Security Market. Introduction By September 17th, the Shanghai stock exchange’s benchmark index had plunged 64% since the start of the year, reaching a 52-...

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

In this paper, we present a Bayesian analysis for the Weibull proportional hazard (PH) model used in step-stress accelerated life testings. The key mathematical and graphical difference between the Weibull cumulative exposure (CE) model and the PH model is illustrated. Compared with the CE model, the PH model provides more flexibility in fitting step-stress testing data and has the attractive m...