Quote from Eric Grant on 04/17/2025, 9:41 am

Datab Part 2: Creating a person-year table.

This tutorial uses the study introduced in Part 1 to create a simple person-year table based on a subjects’ “year in”, “year out”, and “case status”. We create 5-year age categories and accumulate person-years and case counts into each stratum.

The mp4 file is the 10 minute tutorial.

The graphics file (.pdf) is attached. The script and logs are below:

DATAB Script:

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

!

! DATAB tutorial 2

! Create a cross-tabulated dataset based on the “How DATAB Works” tutorial

!     See: https://hirosoft.com/forum/topic/tutorial-datab-part-1/

! Output files: tutorial_2_tab.bsf (binary file)

!                   tutorial_2_tab.csv @

!

!

! HIROSOFT INTERNATIONAL LLC

! August 2024

!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

! DATAB is a program to take individual records (persons) and

! count their accumulated person-years into categories

! that we define

!

! In this example, we will count person years and events to create rates

! The data that we will used is based on Slide 8 of the accompanying

! online tutorial. See: https://hirosoft.com/forum/topic/tutorial-datab-part-1/

!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

!

! To use DATAB, we define variables

! We then define categories to stratify the data in the variables

! Finally, we input the data. DATAB will then accumulate person years

! and count events into each of the categories that we defined.

!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

! On the graphic in the accompanying tutorial, we see that there are

! 6 individuals in the study. Their age is the primary time category

! The study design starts at age 50 and ends at age 80.

! All person-time prior to age 50 or after age 80 is censored

!

! The input data includes the following variables

! ID: An arbitrary ID value, here we use 1-6

! Age_in: A participant’s age when they come under surveillance

! Age_out: A particpant’s age when they left the study

! Case: If they had the event at the time they left, this value is 1, else 0

!

! We begin by telling Epicure that we are starting a new project (i.e. clears

! the memory) and also that this is a DATAB session. The DATAB module will

! read individual records and create a stratified person-year table and event

! counts. Each command in Epicure is terminated with the ampersand “@”

new datab @

! We start by defining the variables that we will use

! using the NAMES command. Note, these are just variable names (placeholders)

! at this time. We will define categories using these variables, finally,

! we will input the data for these variable names

NAMES id age_in age_out case @

! now we define other information that DATAB needs

! Let’s start with a 5-year age categories from

! age 50 to age 80 (like the graphic). We use the

! DURATION command for ages that are not based on

! birth years and calendar date (we’ll see an example

! based on calendar dates in the next tutorial).

DURATION age_cat

50 (5) 80

@

! Next we tell DATAB which variable is the entry age

ENTRY age_in @

! Exit age:

EXIT age_out @

! Tell DATAB which variable indicates an Event

EVENT case @

! This is sufficient information for DATAB to compute

! person-years in 5-year time intervals and count events

! in each strata

!

! We are now ready to input the data using the INPUT

! command. Usually, we will read the data from a file but for

! this example, the data will be input directly from

! this script. Remember the variables are defined as:

!

! ID: An arbitrary ID value, here we use 1-6

! Age_in: A participant’s age when they come under surveillance

! Age_out: A particpant’s age when they left the study

! Case: If they had the event at the time they left, this value is 1, else 0

!

! We will not retype the variable names, simply the data separated by spaces.

! there are 4 variables. Each number will be put into the next variable, when the

! end of the list is found, it will repeat (the linefeeds are there for clarity).

INPUT < @

1 52 76 1

2 58 80 0

3 50 64 0

4 50 68 1

5 50 63 0

6 56 78 1

@

! At this point, the person-year table has been created

! Three variables were created based on our definitions

! PYR: person year in the strata

! age_cat: The age stratification we defined (5-year categories; age 50-80)

! case: a count of the number of cases in each strata

!

! another variable was created by DATAB “AT_RISK”

sum case @

sum pyr @

sum pyr by age_cat @

tran rate = case/pyr @

mean rate by age_cat @

!! Save the data to a CSV file

DATA TO tutorial_2_tab.csv @

!! Save the data to a binary “BSF” file

save; as tutorial_2_tab @

Log file:

[

Epicure/DATAB Version 2.00.04 (Oct 2023)

Gambarimashoo!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

!

! DATAB tutorial 2

! Create a cross-tabulated dataset based on the “How DATAB Works” tutorial

!     See: https://hirosoft.com/forum/topic/tutorial-datab-part-1/

! Output files: tutorial_2_tab.bsf (binary file)

!                   tutorial_2_tab.csv @

!

!

! HIROSOFT INTERNATIONAL LLC

! August 2024

!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

! DATAB is a program to take individual records (persons) and

! count their accumulated person-years into categories

! that we define

!

! In this example, we will count person years and events to create rates

! The data that we will used is based on Slide 8 of the accompanying

! online tutorial. See: https://hirosoft.com/forum/topic/tutorial-datab-part-1/

!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

!

! To use DATAB, we define variables

! We then define categories to stratify the data in the variables

! Finally, we input the data. DATAB will then accumulate person years

! and count events into each of the categories that we defined.

!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

! On the graphic in the accompanying tutorial, we see that there are

! 6 individuals in the study. Their age is the primary time category

! The study design starts at age 50 and ends at age 80.

! All person-time prior to age 50 or after age 80 is censored

!

! The input data includes the following variables

! ID: An arbitrary ID value, here we use 1-6

! Age_in: A participant’s age when they come under surveillance

! Age_out: A particpant’s age when they left the study

! Case: If they had the event at the time they left, this value is 1, else 0

!

! We begin by telling Epicure that we are starting a new project (i.e. clears

! the memory) and also that this is a DATAB session. The DATAB module will

! read individual records and create a stratified person-year table and event

! counts. Each command in Epicure is terminated with the ampersand “@”

new datab @

! We start by defining the variables that we will use

! using the NAMES command. Note, these are just variable names (placeholders)

! at this time. We will define categories using these variables, finally,

! we will input the data for these variable names

NAMES id age_in age_out case @

! now we define other information that DATAB needs

! Let’s start with a 5-year age categories from

! age 50 to age 80 (like the graphic). We use the

! DURATION command for ages that are not based on

! birth years and calendar date (we’ll see an example

! based on calendar dates in the next tutorial).

DURATION age_cat

50 (5) 80

@

! Next we tell DATAB which variable is the entry age

ENTRY age_in @

! Exit age:

EXIT age_out @

! Tell DATAB which variable indicates an Event

EVENT case @

! This is sufficient information for DATAB to compute

! person-years in 5-year time intervals and count events

! in each strata

!

! We are now ready to input the data using the INPUT

! command. Usually, we will read the data from a file but for

! this example, the data will be input directly from

! this script. Remember the variables are defined as:

!

! ID: An arbitrary ID value, here we use 1-6

! Age_in: A participant’s age when they come under surveillance

! Age_out: A particpant’s age when they left the study

! Case: If they had the event at the time they left, this value is 1, else 0

!

! We will not retype the variable names, simply the data separated by spaces.

! there are 4 variables. Each number will be put into the next variable, when the

! end of the list is found, it will repeat (the linefeeds are there for clarity).

INPUT < @

Description of table:

    Variable             Category          Lower             Upper

Number     Name      Number     Name       Bound             Bound

    1      age_cat

                        1      50 – 55  [  50.00             55.00 )

                        2      55 – 60  [  55.00             60.00 )

                        3      60 – 65  [  60.00             65.00 )

                        4      65 – 70  [  65.00             70.00 )

                        5      70 – 75  [  70.00             75.00 )

                        6      75 – 80  [  75.00             80.00 )

           Summary Variables

    1) AT_RISK     2) PYR         3) case

             The potential number of cells is 6

Records read    —         6   Records used                    —         6

This table contains data in 6 with 6 variables

! At this point, the person-year table has been created

! Three variables were created based on our definitions

! PYR: person year in the strata

! age_cat: The age stratification we defined (5-year categories; age 50-80)

! case: a count of the number of cases in each strata

!

! another variable was created by DATAB “AT_RISK”

sum case @

           Summary for case

                Sum         Count      Minimum      Maximum

                  3             6            0            2

sum pyr @

           Summary for PYR

                Sum         Count      Minimum      Maximum

                113             6            9           27

sum pyr by age_cat @

           Summary for PYR

age_cat           Sum         Count      Minimum      Maximum

    1            18             1           18           18

    2            26             1           26           26

    3            27             1           27           27

    4            18             1           18           18

    5            15             1           15           15

    6             9             1            9            9

tran rate = case/pyr @

mean rate by age_cat @

           Summary for rate

age_cat          Mean      Std. Dev.        Count      Minimum      Maximum

    1             0             0             1            0            0

    2             0             0             1            0            0

    3             0             0             1            0            0

    4     0.0555556             0             1     0.055556     0.055556

    5             0             0             1            0            0

    6      0.222222             0             1      0.22222      0.22222

!! Save the data to a CSV file

DATA TO tutorial_2_tab.csv @

6 records written to tutorial_2_tab.csv

!! Save the data to a binary “BSF” file

save; as tutorial_2_tab @

6 records written to tutorial_2_tab.BSF

]