Survival Analysis Software

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BMDP for Survival Analysis

BMDP is recognized by leading statisticians and clinical researchers as one of the best statistical software packages for Survival Analysis. For many years, BMDP has been trusted by leading professionals to provide clear and accurate statistical analysis of research data.

 BMDP’s Survival Analysis programs, 1L &2L, are renowned for their ability to easily handle complex data and to accurately calculate and test survivor functions, Cox proportional hazards model and the log-linear (accelerated failure time) model.

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BMDP Survival Analysis program 1L carries out two major functions:

1. It provides estimates of the survival functions
2. It compares survival functions across different subgroups

Major Features include

• Life Table and Kaplan-Meier estimates of survival distribution
• Survival curves for all or subsets of patients
• Tests for equality of survival curves between groups, including Mantel-Cox, Tarone-Ware, Breslow and Peto-Prentice tests.
• Plots of cumulative survival function, hazard function
• Stratified Analysis
• Brookmeyer-Crowley confidence interval for median survival time
• Special features to handle more unusual analyses types.

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BMDP Survival Analysis Program 2L analyzes survival data for which the time-to-response is influenced by other measured variables. BMDP 2L provides 2 methods of analysis:

1. Cox Proportional Hazards Model
2. Accelerated Failure Time also known as the Log-Linear Model

Major Features Include:

• Cox proportional hazard models with built-in risk functions
• Accelerated failure time models (exponential, Weibull, log-logistic, log normal distributions)
• Optional stepwise variable selections based on two methods
• Competing risk analysis
• User specified time-dependent covariates
• Plots of cumulative survival function, log cumulative hazard function
• Stratified Analysis
• Hypothesis tests for joint significance of subsets of regression co-efficients
• Diagnostic plots (Cox-Snell residuals, standardized residuals Vs. each covariate, log of survival function Vs. time)

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