The data were also analyzed using a survival analysis.
Patients dying as a result of postoperative complications (within 30 days) were excluded from the survival analysis.
The survival analysis relied on comparisons with historical control subjects rather than an actual control group.
Multicollinearity may represent a serious issue in survival analysis.
Censoring is a form of missing data problem which is common in survival analysis.
In survival analysis, this would be done by splitting each study subject into several observations, one for each area of residence.
The log-logistic distribution provides one parametric model for survival analysis.
"A survival analysis of student mobility and retention in Indiana."
Thus, there are two ways in performing a cause-specific survival analysis:
In traditional overall survival analysis the cause of death is irrelevant to the analysis.
