[en] Survival Analysis Tool

[en] The Survival Analysis tool implements common methods of survival analysis. Survival Models model the time until the occurrence of an event (for example, the lapse of a 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).

重要

[en] This tool is not automatically installed with Alteryx Designer or the R tools. To use this tool, download it from the Alteryx Community Gallery.

[en] This tool can be used for two purposes (determined based on configuration settings):

[en] To gain insight into the "survival function" of a dataset (i.e. to estimate a distribution of survival times across a population).
[en] To determine whether particular factors influence the survival function of a population (e.g. to compare survival functions across groups).

[en] Configure the Tool

[en] Use the Required Parameters tab to set the controls for the model generation.

[en] 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.
[en] Input Type: Select one of the following (depending on the data in the data stream).
- [en] Data contains durations: The data includes a field representing durations.
  - [en] Select duration variable: Select the field representing durations.
- [en] Data contains start and stop times: The data includes a field representing start times and a field representing stop times.
  - [en] Select start time/ left censor variable: Select the field representing start times.
  - [en] Select end time/ right censor variable: Select the field representing end times.
[en] Censoring:
- [en] Data is left-censored: The data includes a field representing 0/1 censoring of the start of the record's life.
  - [en] Select left-censoring variable: Select a 0/1 variable, where 0 represents censoring, and 1 indicates that a record's life began at the start time or at 0 (if "Data contains durations" was specified earlier).
- [en] Data is right-censored: The data includes a field representing 0/1 truncation of the end of the record's life.
  - [en] Select right-censoring variable: Select a 0/1 variable, where 0 represents censoring and 1 indicates that a record's life ended at the end time or at the duration (if "Data contains durations" was specified earlier).

[en] Use the Analysis Options tab to better define how analysis is calculated.

[en] Kaplan-Meier Estimate: This option will find the survival curve of a dataset with an option to group by one variable.
- [en] Choose field to group by: This option allows for the comparison of survival curves of different groups.
  - [en] Select grouping variable: Select the field corresponding to the grouping variable.
- [en] Use confidence interval: This option will display upper and lower bounds for the plotting of the KM estimate as well as in its table.
  - [en] Input Confidence Level: Enter the confidence level at which to compute upper and lower bounds for KM estimate.
- [en] Cox Proportional Hazards: Use to see the impact and significance of covariates affecting the survival curve.
  - [en] Select predictor variables: At least one must be selected.
  - [en] Method for tie handling: The method by which to deal with tied times.**
  - [en] Include case weights: This option allows for the selection of a field containing weights for each record.
    [en] Select Field Specifying Weights: Select the field containing case weights.

[en] Use the Graphics Options tab to set the controls for the graphical output.

[en] Plot size: Select inches or centimeters for the size of the graph.
[en] 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.

[en] View the Output

[en] Connect a Browse tool to each output anchor to view results.

[en] O anchor: 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".

[en] Summary Analysis - Surv object, Kaplan-Meier estimate object
[en] Grouping Analysis - Surv object, Kaplan-Meier estimate object, Cox Proportional Hazards object
[en] Factor Analysis - Surv object, Cox Proportional Hazards object

[en] 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.

[en] R anchor: Consists of the report snippets generated by the Survival Analysis tool, depending on the choice of "Analysis Type" under "Analysis Options".

[en] Summary Analysis - Summary statistics and a graph of the survival function.
[en] Grouping Analysis - Summary statistics; observed vs expected results for each group; group comparison test results for similarity of groups for Logrank, Likelihood Ratio, and Wald tests; a graph comparing the survival curves of different groups; and distinct survival curves and cumulative hazard curves for each group.
[en] Factor Analysis - Summary statistics; factor analysis test results for impact of predictive variables for Logrank, Likelihood Ratio, and Wald tests; and a summary of the Cox Proportional Hazards Model detailing the impact of the predictors.

[en] D anchor: 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.

[en] _{*https://en.wikipedia.org/wiki/Survival_analysis **https://stat.ethz.ch/R-manual/R-devel/library/survival/html/coxph.html}