In terms of type I error rate, Log rank test and Wald test give similar results. We can see that when the randomization ratio is 1:1 for an event size of 600, no inflation of types I error rate is observed. However when the randomization ratio is 1:2 for an event size of 600, the type I error rate is inflated to about 0.027. The inflation becomes smaller when the sample size increases. However ...

s for Seminar Series available at: http://www.mcgill.ca/epi-biostat-occh/seminars/biostatistics/ Professor Michael Schemper Section for Clinical Biometrics, Core Unit for Medical Statistics and Informatics, Medical University of Vienna, Vienna, Austria. The estimation of average hazard ratios by Cox regression. Tuesday, 27 January, 2009 4:00 pm 5:00 pm Purvis Hall, 1020 Pine Ave. West, Room 24

Statistical inference based on the right-censored data for proportional hazard (PH) model with missing covariates has received considerable attention, but interval-censored or current status data with missing covariates are not yet investigated. Our study is partly motivated by analysis of fracture data from a cross-sectional study, where the ocurrence time of fracture was interval-censored and...

The Box-Cox quantile regression model using the two stage method suggested by Chamberlain (1994) and Buchinsky (1995) provides a flexible and numerically attractive extension of linear quantile regression techniques. However, the objective function in stage two of the method may not exists. We suggest a simple modification of the estimator which is easy to implement. The modified estimator is s...

Persson, I. 2002. Essays on the Assumption of Proportional Hazards in Cox Regression. Acta Universitatis Upsaliensis. Comprehensive Summaries of Uppsala Dissertations from the Faculty of Social Sciences 110. 36 pp. Uppsala. ISBN 91-554-5208-6. This thesis consists of four papers about the assumption of proportional hazards for the Cox model in survival analysis. The first paper compares the haz...

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 ...

BACKGROUND Aspirin has been considered to be beneficial in preventing cardiovascular diseases and cancer. Several pharmaco-epidemiology cohort studies have shown protective effects of aspirin on diseases using various statistical methods, with the Cox regression model being the most commonly used approach. However, there are some inherent limitations to the conventional Cox regression approach ...

In this paper, a global goodness-of-fit test statistic for a Cox regression model, which has an approximate chi-squared distribution when the model has been correctly specified, is proposed. Our goodness-of-fit statistic is global and has power to detect if interactions or higher order powers of covariates in the model are needed. The proposed statistic is similar to the Hosmer and Lemeshow (19...

The Cox regression model is a cornerstone of modern survival analysis and is widely used in many other fields as well. But the Cox models with time-change covariates are not easy to understand or visualize. We therefore offer a simple and easy-to-understand interpretation of the (arbitrary) baseline hazard and time-change covariate. This interpretation also provides a way to simulate variables ...

We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functional process, measured at baseline. The fundamental idea is to combine penalized signal regression with methods developed for mixed effects proportional hazards models. The model is fit by maximizing the penalized partial likelihood, with smoothing parameters estimated by a likelihood-based criter...