What panel count data is | The response | No time-varying covariates: one row per examination | Time-varying covariates: counting process rows | Which form, in one line | The formula | There is no intercept | Row order does not matter | Recipes for common layouts | Cumulative counts | Data held in the older panelEM layout | Examinations and covariate histories in separate tables | One row per subject, several visit columns | What the data must satisfy | What gets dropped | Missing values | What the package does with your rows | Checking before you fit | See also

The data and the model | Getting data into shape | Converting data held in the older layout | Fitting | Which standard errors | What happens when the Poisson assumption fails | The baseline and predicted means | Tidy output | The means model | Computation | References

The landscape | What is actually different | The rate model | Monotonicity | Covariates between examinations | Variance without the Poisson assumption | Seeing the data first | How long they take | Which standard errors are available | Timings | Why the rate model flattens | Caveats | Which to use | Reference

The landscape | What is actually different | The rate model | Monotonicity | Covariates between examinations | Variance without the Poisson assumption | Seeing the data first | How long they take | Which standard errors are available | Timings | Why the rate model flattens | Caveats | Which to use | Reference

What panel count data is | The response | No time-varying covariates: one row per examination | Time-varying covariates: counting process rows | Which form, in one line | The formula | There is no intercept | Row order does not matter | Recipes for common layouts | Cumulative counts | Data held in the older panelEM layout | Examinations and covariate histories in separate tables | One row per subject, several visit columns | What the data must satisfy | What gets dropped | Missing values | What the package does with your rows | Checking before you fit | See also

The data and the model | Getting data into shape | Converting data held in the older layout | Fitting | Which standard errors | What happens when the Poisson assumption fails | The baseline and predicted means | Tidy output | The means model | Computation | References