Survival Analysis

  • Life Tables and Distributions
    Creates Life Tables for censored data, and fits common distributions for survival or lifetime data.

 Specifying survival times: There are three ways to specify survival times. You can select one (continuous dependent) variable with survival times (e.g., number of weeks surviving), you can select two (continuous dependent) variables with start and stop times for each observation (the analysis will be performed on the differences between the two values, i.e., on the elapsed times), or you can select six (continuous dependent) variables containing dates. Specifically, these variables should contain the month (1 to 12), day (1 to 31), and year when the particular observation began (e.g., when a patient was admitted to the hospital), and the month, day, and year when the observation was terminated (due to death/failure or censoring, e.g., when a patient was dismissed from the hospital). While processing the data, Survival Analysis will compute the number of days that elapsed between dates and perform the analysis on this measure. Note that if the value of the year is less than 100, Statistica will automatically assume that the year refers to the 20th century; for example, the year 88 would be converted into 1988 (and 3 would be converted to 1903; make sure to enter 2003 explicitly into the year column to reference that year).
  • Kaplan-Meier Product-Limit Method
    Creates Kaplan-Meier product limit estimator. Specifying survival times: There are three ways to specify survival times. You can select one (continuous dependent) variable with survival times (e.g., number of weeks surviving), you can select two (continuous dependent) variables with start and stop times for each observation (the analysis will be performed on the differences between the two values, i.e., on the elapsed times), or you can select six (continuous dependent) variables containing dates. Specifically, these variables should contain the month (1 to 12), day (1 to 31), and year when the particular observation began (e.g., when the patient was admitted to the hospital), and the month, day, and year when the observation was terminated (due to death/failure or censoring, e.g., when a patient was dismissed from the hospital). While processing the data, Survival Analysis will compute the number of days that elapsed between dates, and perform the analysis on this measure. Note that if the value of the year is less than 100, Statistica will automatically assume that the year refers to the 20th century; for example, the year 88 would be converted into 1988 (and 3 would be converted to 1903; make sure to enter 2003 explicitly into the year column to reference that year).
  • Comparing Survival in Two Groups
    Computes various nonparametric tests for comparing the survival times in two groups. If more than two groups are specified in the categorical predictor variable, the first two groups are selected for the comparisons. Specifying survival times: There are three ways to specify survival times. You can select one (continuous dependent) variable with survival times (e.g., number of weeks surviving), you can select two (continuous dependent) variables with start and stop times for each observation (the analysis will be performed on the differences between the two values, i.e., on the elapsed times), or you can select six (continuous dependent) variables containing dates. Specifically, these variables should contain the month (1 to 12), day (1 to 31), and year when the particular observation began (e.g., when the patient was admitted to the hospital), and the month, day, and year when the observation was terminated (due to death/failure or censoring, e.g., when a patient was dismissed from the hospital). While processing the data, Survival Analysis will compute the number of days that elapsed between dates, and perform the analysis on this measure. Note that if the value of the year is less than 100, STATISTICA will automatically assume that the year refers to the 20th century; for example, the year 88 would be converted into 1988 (and 3 would be converted to 1903; make sure to enter 2003 explicitly into the year column to reference that year).
  • Comparing Survival in Multiple Groups
    Creates nonparametric test for comparing the survival times in multiple groups. Specifying survival times: There are three ways to specify survival times. You can select one (continuous dependent) variable with survival times (e.g., number of weeks surviving), you can select two (continuous dependent) variables with start and stop times for each observation (the analysis will be performed on the differences between the two values, i.e., on the elapsed times), or you can select six (continuous dependent) variables containing dates. Specifically, these variables should contain the month (1 to 12), day (1 to 31), and year when the particular observation began (e.g., when the patient was admitted to the hospital), and the month, day, and year when the observation was terminated (due to death/failure or censoring, e.g., when a patient was dismissed from the hospital). While processing the data, Survival Analysis will compute the number of days that elapsed between dates, and perform the analysis on this measure. Note that if the value of the year is less than 100, STATISTICA will automatically assume that the year refers to the 20th century; for example, the year 88 would be converted into 1988 (and 3 would be converted to 1903; make sure to enter 2003 explicitly into the year column to reference that year).
  • Regression Models
    Fit various regression models, including Cox proportional hazard, normal, and log-normal, to censored data (e.g., survival data). Specifying survival times: There are three ways to specify survival times. You can select one (continuous dependent) variable with survival times (e.g., number of weeks surviving), you can select two (continuous dependent) variables with start and stop times for each observation (the analysis will be performed on the differences between the two values, i.e., on the elapsed times), or you can select six (continuous dependent) variables containing dates. Specifically, these variables should contain the month (1 to 12), day (1 to 31), and year when the particular observation began (e.g., when the patient was admitted to the hospital), and the month, day, and year when the observation was terminated (due to death/failure or censoring, e.g., when a patient was dismissed from the hospital). While processing the data, Survival Analysis will compute the number of days that elapsed between dates, and perform the analysis on this measure. Note that if the value of the year is less than 100, Statistica will automatically assume that the year refers to the 20th century; for example, the year 88 would be converted into 1988 (and 3 would be converted to 1903; make sure to enter 2003 explicitly into the year column to reference that year).