Complete the following steps to specify the columns of data that you want to analyze.
- In Start
Time, specify the entry time for each observation. The column must be numeric and the same length as the column in End Time. The start times should be less than the end times. If the start time is equal to the end time, Minitab removes the entire row from the analysis.
- In End Time, enter the observed time for each observation. This value is either the time until the event of interest, the censoring time, or the time that the value of a predictor changes. The column must be numeric.
- In Censoring column (optional), enter a column that contains two distinct values. One value indicates a censored observation. The other value indicates the event of interest. A response time is censored if the subject does not experience the event of interest before the study ends, or if the subject leaves the study before they experience the event. You can specify which value indicates a censored observation in Censoring
value. By default, the lowest numeric value or the lowest ASCII value for text columns is the censoring value.
- In Continuous
predictors, enter the columns of numeric data that may explain or predict changes in the response. The predictors are also called X variables.
- In Categorical predictors, enter the categorical classifications or group assignments, such as a type of treatment, that may explain or predict changes in the response. The predictors are also called X variables.
- In Stratification variables
(optional), enter a column to fit a stratified model. Each unique combination of values in the columns that you specify defines a stratum. A stratified model estimates a baseline hazard rate for each strata but uses the same estimates for the effects of the predictors. You can have up to two stratification variables.
The data must be in the counting process form, which means that multiple rows represent each patient. Each row describes a time interval when the values of all the variables are constant. Time-dependent predictors change between rows. The intervals begin just after the start time and include the end time.
For example, the following table contains the data for the patient with an ID of 1. The observed values of Risk Category and Disease Stage are the same in every row because those predictors are fixed. Because a normal platelet count can change during the study, each patient requires a new row of data whenever this predictor changes. The first row shows that the patient did not have a normal platelet count in the interval of the first 13 days after the transplant. The second row shows that the patient had a normal platelet count from after day 13 until the end of the study on day 2,081.
| ID |
Risk Category |
Start Time |
End Time |
Disease Free |
Normal Platelets |
Disease Stage |
|---|
| 1 |
1 |
0 |
13 |
Yes |
No |
Normal |
| 1 |
1 |
13 |
2081 |
Yes |
Yes |
Normal |
