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The Survival Analysis tool implements common methods of survival analysis. Survival Models model the time until occurrence of an event (e.g. lapse of life insurance policy). Survival Models are unique in that they feature censoring; a test or trial may end before such an event occurs (e.g. a policy-holder may pass away before the policy can lapse).
This tool is not automatically installed with Alteryx Designer. To use this tool, download it from the Alteryx Analytics Gallery.
This tool can be used for two purposes (determined based on configuration settings):
Model Name: Each model needs to be given a name so it can later be identified. Model names must start with a letter and may contain letters, numbers, and the special characters period (".") and underscore ("_"). No other special characters are allowed, and R is case sensitive.
Kaplan-Meier Estimate: This option will find the survival curve of a dataset with an option to group by one variable.
Graph resolution: Select the resolution of the graph in dots per inch: 1x (96 dpi); 2x (192 dpi); or 3x (288 dpi). Lower resolution creates a smaller file and is best for viewing on a monitor. Higher resolution creates a larger file with better print quality.
O output: Consists of a table of the serialized model with model name and the size of the object. The availability of various models will depend on the choice of "Analysis Type" under "Analysis Options".
The Cox PH model can be accessed directly from the second element of the output of the O output. If that model is 'model', the Surv and KMest objects can be accessed by 'model$surv' and 'model$KMest', respectively.
R output: Consists of the report snippets generated by the Survival Analysis tool, depending on the choice of "Analysis Type" under "Analysis Options".
D output: For Summary Analysis and Grouping Analysis (in which case an extra field is added specifying group), this constructs the Kaplan-Meier estimate for the survival curves. For factor analysis, it is not provided.
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