Cox proportional hazards
Set up, run, and review this analysis in Lifescio.
Supported analysis
Enter time, an event indicator (1 event, 0 censored) and numeric covariates. Cox regression estimates log hazard ratios without choosing a baseline survival distribution; the implementation uses Efron handling of tied events.
Supported scope: Observations must be independent, covariate coding appropriate and censoring noninformative conditional on the model. Time-varying covariates, recurrent events and clustered survival are outside this workflow. A nonsignificant diagnostic does not prove proportional hazards.
Prepare data and configure the analysis
Use one row per person: strictly positive follow-up Time, Event coded 1 for the event or 0 for right censoring, then numeric covariates. Treatment and age are example columns; all columns after event are used in their supplied order. Encode categorical predictors deliberately, with a reference category, and omit a redundant intercept column.
Use a consistent time unit. This interface fits a standard Cox model with baseline covariates; it does not provide start/stop records, delayed entry, clustering, or time-dependent effects. Significance level sets confidence limits and the diagnostic flag threshold.
Input reference (2 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 | — | Independent right-censored observations; event is 0 or 1. All columns after event are numeric covariates. Columns in order: Time; Event; Treatment; Age. |
| 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
Cox regression lists Covariate 1, Covariate 2, and so on in input order. SE refers to the log-hazard coefficient; Lower HR and Upper HR are on the hazard-ratio scale. Match those generic labels to your retained input column definitions.
Proportional-hazards check contains rank-time diagnostic tests. The plotted survival is Survival at centered covariates, not a treatment-specific adjusted pair of curves. Diagnostics also report concordance and observed events. A warning should be reviewed before using the constant hazard ratio.
Troubleshooting and common mistakes
A rank-deficiency error often means a constant covariate, duplicated column, or all dummy categories were included. A convergence problem can arise from sparse events, separation, or highly correlated predictors. Check event coding and data support before simplifying a scientifically chosen model.
A proportional-hazards flag is not repaired by increasing alpha. If a time-varying effect is required, use a workflow that supports it; this form does not fit one. Do not interpret the centered-covariate curve as a patient-specific prediction.
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.