Sentence examples for using a counting process from inspiring English sources
Cox proportional hazards regression modelling for repeated events were performed using a counting process approach to assess hazards of bicycle crash injury associated with residing in Auckland.
Using a counting process model (based on a Poisson process) [ 56], the rate of event occurrence for each patient will be modeled as a function of time, and available covariates.
Cox proportional hazards regression modelling for repeated events was performed using a counting process approach to assess hazards of crash involvement associated with patterns of using conspicuity aids (latent classes), amount of bunch riding and region of residence.
The Andersen-Gill model uses a counting process approach which relates the intensity function of event recurrences to the covariates multiplicatively where all events contribute equally to the hazard function.
The pseudolikelihood function can be readily constructed using available statistical software by adopting a counting process to describe the event time (i.e., each subject's time to event process is described by a series of start and stop intervals) [ 22].
Let {N t), t ≥ 0} be a counting process.
Admission to an ETU was a binary time-dependent variable entered into the model by using the counting process method.
To analyze survival in relation to AOC we applied Cox proportional hazards regression models based on maximum partial likelihood estimation as implemented by PROC PHREG in SAS 9.2, using the "counting process" procedure [36].
We note these potential limitations, which we address using the counting process style of input, when evaluating our extended Cox model with these time-varying covariates.
However, they can be extended to account for time varying covariates (measured several times per individual) using the counting process reformulation by Andersen and Gill [ 37].
Using standard counting process notation, let N 0 j (t ) count the number of observed 0 → j transitions by time t, and Y0 t) indicate the number of individuals still in state 0 just prior to time t.
