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Multiple Indicator Cluster Surveys Data Processing Workshop

Multiple Indicator Cluster Surveys Data Processing Workshop. Creating Analysis Files: Description of Preparation Steps. Secondary Data Processing Flow. Export Data from CSPRO. Import Data into SPSS. Recode Variables. Add Sample Weights, Wealth Index and GPS Data. Run Tables.

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Multiple Indicator Cluster Surveys Data Processing Workshop

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  1. Multiple Indicator Cluster SurveysData Processing Workshop Creating Analysis Files: Description of Preparation Steps MICS4 Data Processing Workshop

  2. Secondary Data Processing Flow Export Data from CSPRO Import Data into SPSS Recode Variables Add Sample Weights, Wealth Index and GPS Data Run Tables MICS4 Data Processing Workshop

  3. Exporting ‘clean data’ from CSPRO to SPSS • By using CSPRO dictionary and final data file, we create ASCII rectangular data files (*.dat) and corresponding syntax files (*.sps) to read the data into SPSS • All located in ‘c:\mics4\spss’ directory • c:\mics4\spss\myhh.sps • c:\mics4\spss\myhh.dat • … MICS4 Data Processing Workshop

  4. Rectangular data files [*.dat] • myhh.dat - [Household] • myhl.dat – [Household members] • mywm.dat – [Women] • mych.dat – [Children] • mytn.dat – [Mosquito nets] • Only if ‘ITN’ module’ is included • myfg.dat – [FGM] • Only if ‘FGM’ module’ is included • mybh.dat – [Births to women 15-49] • Only if ‘Birth History’ module is included • mymn.dat – [Men] • Only if ‘Men’ questionnaire is included MICS4 Data Processing Workshop

  5. Rectangular data files [*.dat] • HOUSEHOLD QUESTIONNAIRE • myhh.dat - [Household] • myhl.dat – [Household Members] • mytn.dat – [Mosquito nets] • INDIVIDUAL WOMEN QUESTIONNAIRE • mywm.dat – [Women age 15-49] • myfg.dat – [Female genital cutting. women age 15-49] • mybh.dat – [Births to interview. women age 15-49] • UNDER-5 QUESTIONNAIRE • mych.dat – [Children] • INDIVIDUAL MEN QUESTIONNAIRE • mymn.dat – [Men age 15-59] MICS4 Data Processing Workshop

  6. Rectangular data files [*.dat] • Rows are ‘cases’ • Household – all (interviewed or not) • Members - living in interviewed households • Women – all (interviewed or not) • Children – all (interviewed or not) • Nets – mosquito nets in interviewed household • Only if ‘ITN’ module’ is included • Daughters – daughters under 15 years of age of interviewed women age 15-49 • Only if ‘FGM’ module’ is included • Births – births to interviewed women age 15-49 • Only if ‘Birth History’ module is included • Men – all (interviewed or not) • Only if ‘Men’ questionnaire is included • Columns are ‘variables’ • Cluster, Household number, Line number, Interviewer number, etc.

  7. Screenshot • Sample ASCII data file

  8. Syntax files (to read rectangular data files) • myhh.sps • myhl.sps • mywm.sps • mych.sps • mytn.sps • Only if ‘ITN’ module is included • myfg.sps • Only if ‘FGM’ module is included • mybh.sps • Only if ‘Birth History’ module is included • mymn.sps • Only if ‘Men’ questionnaire is included • Includes the location information (columns) of variables in rectangular data file as well as variable labels and value labels MICS4 Data Processing Workshop

  9. Screenshot • Sample Syntax file

  10. Importing Data to SPSS • Executing syntax files created by CSPRO • In SPSS, run all my*.sps files (one by one) • The my*.sps files will import the data into SPSS and create SPSS-format data files (system files - *.sav), with variable labels, value labels etc. • At the end of each run, save your work in data files as hh.sav, hl.sav, wm.sav, ch.sav[tn.sav, fg.sav, bh.sav, mn.sav] MICS4 Data Processing Workshop

  11. Saving the Data File • It is helpful to have the syntax file automatically save the data file that it creates • To do so, add the following line to the end of the syntax file: save outfile = 'hh.sav'. MICS4 Data Processing Workshop

  12. Screenshot • SPSS Data Editor – Data View • Household

  13. Screenshot • SPSS Data Editor – Variable View • Household

  14. Run frequency distributions • Open SPSS and run frequency distributions for all of the variables in all 7 files • Detect any unexpected codes or inconsistencies, and if necessary, return to CSPro and make corrections.

  15. Next Steps • Recoding variables • Creating new variables by recoding existing variables • Adding variables to different levels • Mother’s education • Father’s education MICS4 Data Processing Workshop

  16. Customize make*.sps • Customize the make*.sps syntax files, in accordance with the contents of your questionnaires • Take out any variables and associated syntax which are not included in your questionnaire, or modify the variables according to your response categories

  17. Run make.sps • Run make.sps to recode all additional variables needed for the tabulations • make.sps is provided as a batch file which calls and runs each of the make*.sps files in turn • All *.sav variables will be replaced! • Backup before you proceed to this stage

  18. Next Steps • Adding sample weights • Sample weights are added from weights spreadsheet MICS4 Data Processing Workshop

  19. Calculate weights • Obtain distribution of interview results by the unit based on which you intend to calculate unique sample weights: - using the weights_table.sps syntax file, if calculation at cluster level - using the weights_table_alt.sps syntax file, if calculation at stratum level, e.g. regions and area

  20. Calculate weights cont. • Calculate final sample weights • using weights.xls, if calculations are carried out at the cluster level • weights_alt.xls, if calculations are carried out at stratum level

  21. Calculate weights cont. • Once calculations in weights.xls or weights_alt.xls have been completed, save the “Output” workbook • c:\mics4\weights\weights.xls

  22. Append sample weights • Append sample weights to the exported SPSS files hh.sav, hl.sav, wm.sav, ch.sav (tn.sav, fg.sav, bh.sav and mm.sav if relevant modules included), by using the SPSS weights_merge.sps or weights_merge_alt.sps syntax file • Need customization if ITN, Birth History modules or Men questionnaire included

  23. Next Steps • Adding wealth index • Wealth index calculated then added to files MICS4 Data Processing Workshop

  24. Customize wealth.sps • Customize the wealth.sps syntax file that calculates wealth index values, together with the survey coordinator/technical manager, according to the items included in your questionnaire

  25. Run and append wealth • Run the customized SPSS syntax wealth.sps to calculate and append wealth index values to all of the exported data files

  26. Next Steps • Adding GPS data • Geographic location data added to files MICS4 Data Processing Workshop

  27. Next Steps • Tabulation • Tables are generated from the *.sav files MICS4 Data Processing Workshop

  28. Customize each syntax • Customize all tabulation syntax files in accordance with the contents of your survey • Delete the syntax files which are used to obtain tables on topics which are not included in your survey

  29. Run all_tables.sps • Once all tabulation syntax files are customized and free of errors, customize all_tables.sps • all_tables.sps calls and runs all tabulation syntax files, and produces an output which includes all tables • If any of the tabulation syntax files have errors, the program will stop and you will have to correct the tabulation syntax file. Then re-run all_tables.sps

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