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Univariable Cox Proportional Hazards Screening Engine

Source: R/cbe_cox_single.R
cox_single.Rd

Fits a univariable Cox proportional hazards model, validates the proportional hazards assumption, formats coefficients with explicit reference levels, generates plain-language clinical interpretations, and gathers model fit metrics.

Usage

cox_single(data, outcome = "outcome", feature, conf_level = 0.95, ...)

Arguments

data

A data frame containing survival data and the candidate feature.

outcome

Character string naming the Surv object or outcome column in data (e.g., "outcome" or "Surv(survival_time, status)").

feature

Character string naming the candidate predictor column in data.

conf_level

Numeric confidence level (default: 0.95).

...

Additional arguments passed to survival::coxph (e.g., weights, ties).

Value

An object of class cbe_cox containing:

  • model: The fitted survival::coxph object.

  • zph: The survival::cox.zph proportional hazards test object.

  • zph_table: Formatted assumption test table.

  • zph_violated: Logical indicating whether the assumption was violated (p < 0.05).

  • zph_text: Automated sentence summarizing the assumption test.

  • table: Clean coefficient table with explicit reference level rows for factors.

  • interpretation: Plain-language automated interpretation of the hazard ratio(s).

  • glance: One-row data frame of model goodness-of-fit metrics.

  • feature: Feature name string.

  • var_label: Human-readable variable label.

  • is_numeric: Logical flag indicating whether predictor is continuous/numeric.

See also

[cox_multi()], [cox_check()], [km_single()], [cbe_cox_table()], [plot_cox_forest()], [plot_cox_survival()], [plot_cox_marginal()]