Event status: The event status variable is coded this way:

Equal to 1 if the event was known to occur during the observation period (uncensored)

Equal to 0 if the event didn’t occur during the observation period (censored)

Time-to-event: In participants who experienced the event during the observation period, this is

the time from the start of observation to the occurrence of the event. In participants who did not

experience the event during the observation period, this is the time from the start of observation to

the last time the participant was observed. We describe time-to-event data in more detail in

Chapter 21.

And as with all regression methods, you designate one or more variables as the predictors. The rules

for representing the predictor variables are the same as described in Chapter 18:

For continuous numerical variables, choose units of a convenient magnitude.

For categorical predictors, carefully consider how you recode the data, especially in terms of

selecting a reference group. Consider a five-level age group variable. Would you want to model it

as an ordinal categorical variable, assuming a linear relationship with the outcome? Or would you

prefer using indicator variables, allowing each level to have its own slope relative to the reference

level? Flip to Chapter 8 for more on recoding categorical variables.

You may not be sure which variables in your data to include as predictors in the regression. We

provide advice on model-building in Chapter 17.

After you assemble and properly code the data, you execute the regression in statistical software using

a similar approach as you use when doing ordinary least-squares or logistic regression. You need to

specify the variables in the regression model:

1. Specify the two outcome variables.

The event status variable

The time-to-event variable

2. Specify the predictor variables.

Make sure you are careful when you include categorical predictors, especially indicator variables.

All the predictors you introduce should make sense together in the model.

Most software also lets you specify calculations you want to see on the output. You should

always request at least the following:

Coefficients table, including HRs and their confidence intervals

Tests of whether the hazard proportionality assumption is valid

You may also want to request the following output: