survival analysis

A large part of the course will be concerned with survival analysis.

Survival analysis is another name for time to event analysis.

Such cases are included in incidence rates, but excluded from survival analysis.

We approach this challenge by using techniques based on survival analysis which can handle such changes to the size and structure of the population.

Survival analysis predicts when the client leaves assistance and does not return.

Survival analysis attempts to answer questions such as: what is the proportion of a population which will survive past a certain time?

The data were also analyzed using a survival analysis.

One method for predicting the long-term outcome of training is survival analysis.

Information regarding certain key variables is required to undertake survival analyses.

Correcting for confounding in survival analysis: the tree- growing approach.

In traditional overall survival analysis the cause of death is irrelevant to the analysis.

Survival analysis was used to compare recidivism over a maximum of 80 months for the two groups.

I have published papers in distribution theory, sample size determination and survival analysis.

Annual mortality rates are estimated using both survival analysis and a Bayesian approach.

Three methods were used for the survival analysis.

For the time course presentations, survival analyses are recommended.

Multicollinearity may represent a serious issue in survival analysis.

These results vary somewhat from those obtained by the survival analysis, but the general orders of magnitude are the same.

Nonparametrical survival analysis as a statistical tool in agricultural decision making.

Survival analysis suggested that subjects were most vulnerable to recidivism in the 60 days after release.

Censoring is a form of missing data problem which is common in survival analysis.

Patients dying as a result of postoperative complications (within 30 days) were excluded from the survival analysis.

Applied survival analysis : regression modeling of time to event data.

The log-logistic distribution provides one parametric model for survival analysis.

The concept is used in cancer survival analyses.