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In this exercise you will learn to take the variables from either:

• an existing SPSS Windows (.sav) file
• an Epi-Info .rec file

   ...and to calculate z-score values using Epi-Nut. Then you will learn how to merge the new z-score information back in the existing file for analysis.

From an existing SPSS Windows (.sav) file

1. Open the SEAsia.sav file which contains some data. Identify the variables for child age, child sex, child weight (kgs), and child height (cms).
2. Highlight the variables you want and copy them. Open a new data file and paste these variables into this new file.
3. Save the new file (SEAsia2) as a .dbfIII file in the Epi6 subdirectory of your computer.
4. Go to Import in Epi-Info under Programs, and select .dbf file as import file type, type SEAsia2.dbf and then process. It will produce the SEAsia2.rec file for you.

5. Creating anthropometric variables using the Epi-Nut program.

• After you have imported the SEAsia2.rec file, you will go to the Epi-Nut processor, which is under Programs in the Epi-Info system.

• Go to Indices and Add to file. There, type in the name of the .rec file you will use.
• Use the mouse to click on the arrows to select the variable names in your data set for Age, Sex, Weight, and Height.
• Next use the mouse to select only whz, waz, and haz. All nine indices are selected (X) by the default but usually you only use the Z-scores. The space bar can also be used to remove the default selections, moving the cursor with the arrow buttons.
• Then click on Process. The computer will give you a status report when finished.
• Go back to Analysis and 'read' the updated SEAsia2.rec file you created. View the file by pressing the F4 key.

6. Go to Export in the Program menu. Export the SEAsia2.rec file with anthropometric variables in it as a dbase III file. You can export it to the SPSS subdirectory. Open the exported file in SPSS Windows and save it as SEAsia2.sav. You can overwrite the previous file since this one has the newest information in it.
7. To merge the files in SPSS-Windows open the larger file. Under the Data menu, select Merge and then select Add new variables.
8. It will then go to the open file selection and you choose the file larger existing SPSS file named SEAsia.sav. Now you select Match cases on key variables in sorted files and select the unique identification variable (there is not one in this particular file, but usually it is ID or caseid) . Move it to the Key Variables box. Then select out all variables except the waz, whz, and haz variables to the Excluded Variables box and process.
9. You should now have the anthropometric variables added to the SEAsia.sav data set. Make sure to save it.

1. To open Epi-Info: From windows, click on the MS-DOS prompt. Then change to the Epi6 subdirectory. When you see c:\Epi6> then type Epi6 again and press return.
2. Open the kenya1.rec file in Analysis by typing read kenya1 and pressing return. Look for the variable names for child age (in months), sex, weight (in kgs) and height (in cms). Also look for the unique identifier like ID number or Case ID. Each child record should have a number which identifies that particular child so when you merge the files together again there is no problem matching the new anthropometric variables to the correct child.
3. Next you will write a program that will create a small .rec file that contains only the unique identifier and child sex, age, weight, and height variables.This is done because the Epi-Nut processor cannot easily handle large data sets. This way we only have the information necessary for calculating these anthropometric indices. These programs are written in the EPED word processor.

TAKE A LOOK at the program you will write in EPED.

    4.  Creating the kensm1.rec by running the kenya1.pgm:

• After saving the program file and exiting EPED, exit Epi-Info by pressing F10. You should be at the DOS prompt C:\Epi6>.
• Type analysis run kenya1.pgm and press return.
• When it has finished running, press the F10 key again to get back to the C:\Epi6> prompt.
• Then type Epi6 (return) and go to Analysis.
• Open the new kensm1.rec file and press F4 to see the file structure.

    5.   Creating anthropometric variables using the Epi-Nut program.

• After you have created the small .rec file, you will go to the Epi-Nut processor, which is under Programs in the Epi-Info system.

• Go to Indices and Add to file. There, type in the name of the .rec file you will use. In this instance it will be the kensm1.rec file created from the program.
• Use the mouse to click on the arrows to select the variable names in your data set for Age, Sex, Weight, and Height.
• Next use the mouse to select only whz, waz, and haz. All nine indices are selected (X) by the default but usually you only use the Z-scores. The space bar can also be used to remove the default selections, moving the cursor with the arrow buttons.
• Then click on Process. The computer will give you a status report when finished.
• Go back to Analysis and 'read' the kensm1.rec. View the updated file by pressing the F4 key.

    6.   Merging two files - anthropometric variables with the original file.

Go EPED - you will write a new program to merge the kensm1.rec with the kenya1.rec. In doing this remember that you are matching the data for each record with the unique identifier (caseid) and are actually creating a third .rec file with all variables.

TAKE A LOOK at the program you will write in EPED.

1. Viewing complete data set with anthropometric variables:

• Go to Analysis and type read kenya2
• Press F3 to see a variable list and look for the waz, whz, and haz variables.
• Press F4 to see the file structure.

2. Exporting the new kenya2.rec for analysis in SPSS Windows:

• Under Programs, go to Export.
• Type kenya2 and select dbaseIII as the file type to export.
• It will automatically name it kenya2.dbf and will export it to the C:\epi6 subdirectory.
• Open SPSS Windows and open the Kenya2.dbf file - it will be found in the Epi6 sub-directory.
• After the data is opened in the Data Editor, go to File and Save As and save it in the SPSS sub-directory as a .sav file.

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