After controlling for patient and hospital factors, M-M bearings were associated with a higher risk of periprosthetic joint infection (hazard ratio, 3.03; confidence interval, 1.02 9.09) when compared with C-C bearings.
After adjusting for patient and hospital factors, M-M bearings were associated with a higher risk of periprosthetic joint infection (hazard ratio, 3.03; confidence interval, 1.02 9.09) when compared with C-C bearings (0.59% versus 0.32%, respectively).
The results are then used to construct the joint wind snow hazard level contours corresponding to different annual exceedance probabilities.
This paper presents an approach to statistically characterize the joint wind snow hazard for use in performance-based design.
The following two paragraphs discuss the joint transition hazards approach J and the separate transition hazards approach S. Approach J models transitions 1 →3 and 2 →3 jointly.
From their own experiences, many do not consider the occasional joint a great hazard.
Using a joint proportional mixed hazard rate model, we simultaneously estimate two durations.
For disaster officials, scenarios are often perceived just in descriptive terms, sometimes relate to one reference event type only (e.g. flood, earthquake, windstorm or eruption) and rarely consider the possibility of joint or cascaded hazard exposures and the associated uncertainties, physical, scientific and logistical.
We use survey and register data of 809 long-term sick-listed workers to estimate a joint proportional mixed hazard rate model with two durations, i.e. the competing risk duration until returning to work (in an accommodated job with the current employer, in a non-accommodated job with the current employer, or in a job with a new employer) and the duration of the subsequent employment.
The joint model produces hazard ratios that are substantially higher than the time-to-first-event model especially for the risk factors of smoking and diabetes.
