Advanced Cox Model Diagnostics Calculator

Check proportional hazards, residual patterns, and influential observations fast. Compare risk scores across subjects confidently. Make survival diagnostics clearer for decisions, audits, and reporting.

Calculator inputs

Use the responsive grid below. It shows three columns on large screens, two on small screens, and one on mobile.

Uploaded data overrides the textarea below.
Required columns: id, time, event. Optional covariates: x1, x2, x3, x4, x5. Event must be 0 or 1.
Reset to example

Example data table

This example is already loaded into the textarea.

ID Time Event x1 x2 x3 x4 x5
S013.210.810.401
S025.10-0.20-0.510
S032.411.110.911
S046.80-0.70-0.100
S054.010.311.210

Formula used

Linear predictor
ηi = Σ(βj × xij)
Hazard ratio
HRi = exp(ηi)
Breslow baseline increment
ΔH0(tk) = dk / Σl∈Rk exp(ηl)
Cumulative hazard and survival
H0(ti) = Σ ΔH0(tk) for tk ≤ ti
H(ti|xi) = H0(ti) × exp(ηi)
S(ti|xi) = exp(-H(ti|xi))
Martingale residual
Mi = δi - H(ti|xi)
Deviance residual
Di = sign(Mi) × √[-2 × (Mi + δi ln(δi - Mi))]
Cox-Snell residual
rCS,i = H(ti|xi)
Schoenfeld residual for events
rSch,i = xi - weighted mean of the risk set at event time

This tool uses supplied coefficients and a Breslow baseline estimate from the entered dataset. The PH correlation is a fast screening proxy.

How to use this calculator

  1. Enter covariate names and the fitted Cox coefficients.
  2. Paste CSV data or upload a CSV file.
  3. Keep event coded as 1 for event, 0 for censored.
  4. Use x1 through x5 to match the coefficients above.
  5. Submit the form to generate subject-level diagnostics.
  6. Review c-index, residuals, PH trend proxies, and outliers.
  7. Use the CSV or PDF buttons to export results.

Frequently asked questions

1. What does this calculator actually diagnose?

It checks risk scores, Breslow baseline hazard, predicted survival, martingale residuals, deviance residuals, Cox-Snell residuals, influence magnitude, and a fast proportional-hazards drift proxy from Schoenfeld residual patterns.

2. Do I need raw survival data?

Yes. You need at least an ID, observed time, event flag, and the matching covariate values. The calculator uses those rows to build risk sets and estimate the cumulative baseline hazard.

3. What does a large martingale residual mean?

Large positive or negative martingale residuals can suggest poor local fit, omitted nonlinearity, or unusual observations. They are especially useful when checking whether a covariate effect may need transformation.

4. How should I read deviance residuals?

Deviance residuals symmetrize martingale residuals. Values far from zero can flag outliers or observations the model fits poorly. Many analysts start reviewing cases with absolute values greater than about two.

5. Is the proportional hazards check a formal statistical test?

No. The correlation shown here is a fast screening proxy based on event times and Schoenfeld residuals. Use a full formal PH test when you need publication-grade inference.

6. What does the c-index show?

Harrell’s c-index measures how well the model ranks earlier events above later observations. Higher values indicate better discrimination, while values near 0.5 suggest weak ranking performance.

7. Can I use fewer than five covariates?

Yes. Leave unused coefficients at zero and keep missing x columns empty or omitted. The calculator treats missing x2 to x5 columns as zeros.

8. Why do exported results matter?

Exports make it easier to document model reviews, share screening findings, attach evidence to reports, and continue residual analysis in spreadsheets or audit packages.

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Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.