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

   ...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.
  1. Creating anthropometric variables using the Epi-Nut program.
  1. 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.
  2. To merge the files in SPSS-Windows open the larger file. Under the Data menu, select Merge and then select Add new variables.
  3. 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.
  4. You should now have the anthropometric variables added to the SEAsia.sav data set. Make sure to save it.

From Epi-Info .rec file

  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:

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

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

 

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