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An example of a Kaplan–Meier plot for two conditions associated with patient survival. The Kaplan–Meier estimator, [1] [2] also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime data.
Survival models can be viewed as consisting of two parts: the underlying baseline hazard function, often denoted (), describing how the risk of event per time unit changes over time at baseline levels of covariates; and the effect parameters, describing how the hazard varies in response to explanatory covariates. A typical medical example would ...
An alternative to building a single survival tree is to build many survival trees, where each tree is constructed using a sample of the data, and average the trees to predict survival. [7] This is the method underlying the survival random forest models. Survival random forest analysis is available in the R package "randomForestSRC". [10]
The logrank test statistic compares estimates of the hazard functions of the two groups at each observed event time. It is constructed by computing the observed and expected number of events in one of the groups at each observed event time and then adding these to obtain an overall summary across all-time points where there is an event.
IBM SPSS Modeler is a data mining and text analytics software application from IBM. It is used to build predictive models and conduct other analytic tasks. It has a visual interface which allows users to leverage statistical and data mining algorithms without programming.
The original SPSS manual (Nie, Bent & Hull, 1970) [11] has been described as one of "sociology's most influential books" for allowing ordinary researchers to do their own statistical analysis. [12] In addition to statistical analysis, data management (case selection, file reshaping and creating derived data) and data documentation (a metadata ...
SigmaStat can compare effects among groups, conduct survival analysis, analyze rates and proportions, perform regression and correlation analysis and calculate power and sample size. The program uses a wizard based interface which asks the user questions about the project and its data.
Epi Info has been in development for over 20 years. The first version, Epi Info 1, was originally developed by Jeff Dean while he was in high school. [3] [4] It was an MS-DOS batch file on 5.25" floppy disks and released in 1985. [5]
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