Before you model | What to decide | Fit and summarize | Visual check — posterior forest plot | Visual check — MLE vs Bayes | Why this is insightful | Credible intervals and criteria | Convergence (optional deep dive) | tidybayes posterior draws | Survival prediction

Before you model | Why this is insightful | What to decide | Fit and summarize | Visual check — baseline overlay | Gamma information stability | Basis functions

Before you model | Why this is insightful | What to decide | Fit and summarize | Visual check — survival overlay | When to use which family

Before you model | Why this is insightful | What to decide | Fit and summarize | Specifying the Bernstein degree | The spbp object | Visual check — KM (step) vs Bernstein survival (smooth) | Visual check — forest plot | Printing | Next steps

Before you model | Fit and summarize | Visual check — forest plot | Visual check — model comparison | Why this is insightful | What to decide | Degrees of freedom (visual) | Confidence intervals and variance | estimates(), se(), and extractAIC() | Null model

Before you model | Why this is insightful | What to decide | Fit and summarize | Visual check — martingale residuals | Visual check — Cox-Snell calibration | Visual check — deviance residuals | Compare with Cox (reference) | Gamma information stability | Bayesian fits

Before you model | Why this is insightful | What to decide | Fit and summarize | Prediction grid | predict() — tidy data frame | Visual check — KM vs model overlay | survfit() with tidy = TRUE | Bayesian fits | Interval types (MLE)

parsnip engines | workflows | Convenience constructor | Censored predictions from spbp fits | Bayesian: tidybayes

Before you model | What to decide | Fit and summarize | Visual check — posterior forest plot | Visual check — MLE vs Bayes | Why this is insightful | Credible intervals and criteria | Convergence (optional deep dive) | tidybayes posterior draws | Survival prediction

Before you model | Why this is insightful | What to decide | Fit and summarize | Visual check — survival overlay | When to use which family

Before you model | Why this is insightful | What to decide | Fit and summarize | Specifying the Bernstein degree | The spbp object | Visual check — KM (step) vs Bernstein survival (smooth) | Visual check — forest plot | Printing | Next steps

Before you model | Why this is insightful | What to decide | Fit and summarize | Prediction grid | predict() — tidy data frame | Visual check — KM vs model overlay | survfit() with tidy = TRUE | Bayesian fits | Interval types (MLE)

parsnip engines | workflows | Convenience constructor | Censored predictions from spbp fits | Bayesian: tidybayes

Before you model | Why this is insightful | What to decide | Fit and summarize | Visual check — baseline overlay | Gamma information stability | Basis functions

Before you model | Fit and summarize | Visual check — forest plot | Visual check — model comparison | Why this is insightful | What to decide | Degrees of freedom (visual) | Confidence intervals and variance | estimates(), se(), and extractAIC() | Null model

Before you model | Why this is insightful | What to decide | Fit and summarize | Visual check — martingale residuals | Visual check — Cox-Snell calibration | Visual check — deviance residuals | Compare with Cox (reference) | Gamma information stability | Bayesian fits