Parametric survival & extrapolation
Set up, run, and review this analysis in Lifescio.
Supported analysis
The app fits exponential, Weibull, lognormal and log-logistic candidates to right-censored observations. It compares fit statistics and uses the distribution you select for extrapolation to the requested horizon.
Supported scope: The workflow fits marginal distributions without covariates. Independent censoring and a suitable distribution are required. Reported intervals condition on the selected model and exclude uncertainty about which distribution is correct.
Prepare data and configure the analysis
Supply exactly two columns: positive follow-up Time and binary Event. Remove covariate columns explicitly; this workflow is unadjusted. Select Extrapolation distribution, set the horizon in the same time units as the observations, and choose significance level.
The engine attempts exponential, Weibull, lognormal, and loglogistic fits for comparison, while your selected distribution determines the detailed curve table. It does not automatically replace your choice with the model having the smallest information criterion.
Input reference (4 fields)
Enter your data and prespecified choices. Ranges include both limits. For table fields, use cell editing, Paste data, or Import CSV / TSV. Review whether the first imported row contains headings and map the source columns before applying the import. Empty numeric cells are not treated as zero. Open file is for an exported Lifescio analysis JSON file, not a spreadsheet.
| Input | Format | Allowed range | Guidance |
|---|---|---|---|
| Survival observations | Table | — | Columns in order: Time; Event. |
| Extrapolation distribution | Selection | — | Choices: exponential, weibull, lognormal, loglogistic. |
| Extrapolation horizon | Number | 0.1–10000 | — |
| Significance level | Number | 0.001–0.2 | — |
Run and review
- Give the analysis a descriptive name and review every example value. Record units, data preparation, and planning assumptions in Reproducibility & notes. For simulations, record the seed and replication or sampling settings.
- Choose Run analysis. Resolve input errors before interpreting output. In the connected app, a run uses a saved input revision; local preview runs need the page to stay open.
- Review Diagnostics for method limitations, warnings, and available numerical checks. A completed run means computation finished; it does not establish that the assumptions fit your study.
- Use the Result table selector to inspect each output. Editing inputs does not recalculate existing results: an earlier-input notice means you need to run again to obtain matching results.
Understand the outputs
Read Candidate model fit for log likelihood, AIC, and BIC, then Fitted parameters for the selected family. Parameters have family-specific meanings and should not be compared as if they were the same quantity across distributions.
Selected survival curve contains pointwise bounds and a Range label distinguishing extrapolation beyond the maximum observed follow-up. The comparison plot includes successfully fitted candidates. The displayed timeline reaches at least the largest observed time even if you enter a shorter horizon.
Troubleshooting and common mistakes
Extra columns, nonpositive times, invalid event codes, or no observed events prevent fitting. If the selected distribution fails to converge, inspect data quality and whether the distribution is estimable; selecting another family changes the model and must be recorded.
An attractive AIC does not validate a long extrapolation. If candidate tails diverge, preserve separate scientifically plausible scenarios and compare them. The current output does not include distribution-selection uncertainty in its confidence bounds.
After correcting inputs, run again and check that the results belong to the new input snapshot. Increasing simulation draws improves numerical precision only; it does not repair invalid data or an unsuitable model.
Save, compare, and export
In the connected app, Save analysis retains the inputs in your account. Run history lets you inspect earlier runs, each with the input revision it used. In local preview, Save analysis downloads an input file instead; download results before leaving the page.
Use Result + inputs for a JSON archive containing the completed result and its inputs, Download CSV for the selected result table, PDF report for a report, and a chart's SVG button for its figure. Table displays round to three decimals; CSV and JSON exports retain calculation precision. Use those values when assessing a result near a decision boundary.
To reopen an archive, select the matching analysis method and choose Open file. Imported inputs start a new draft; a result archive can also display its retained result. It does not attach itself to an existing account analysis or recompute the result. Save or run the imported draft when you want a new account record.