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MICS Data Processing Workshop

MICS Data Processing Workshop

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MICS Data Processing Workshop

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  1. MICS Data Processing Workshop Adding the Wealth Index and GPS Data

  2. Secondary Data Processing Flow Export Data from CSPRO Import Data into SPSS Recode Variables Add the Wealth Index and GPS Data Run Tables

  3. Sampling • The probability of selecting a household for MICS interviews was not equal across all of Popstan • In North region • 28 households were selected per 10,000 • In West Region • 5 households were selected per 10,000 • Overall • 10 households were selected per 10,000

  4. Sample Weights • Sample weights are used to adjust the sample to produce accurate estimates for the whole country • Sample weights are the inverse of the relative probabilities of selection • For example, the weights for North and West region • North region 10/28 = 0.36 • West region 10/5 = 2 • Weights should always be used when tabulating

  5. Sample Weights Objects • WEIGHTS.XLS • spreadsheet that calculates weights • WEIGHTS_TABLE.SPS • SPSS program that provides input data for spreadsheet • WEIGHTS.SPS • SPSS program that defines structure of spreadsheet’s output • WEIGHTS_MERGE.SPS • SPSS program that merges weights onto the MICS data files

  6. Steps in Adding Weights 1. Update weights.xls to have one row per strata/cluster 2. Add sampling information to weights.xls 3. Adapt strata definitions in weights_table.sps 4. Execute weights_table.sps program 5. Copy resulting table’s contents into “Calculations” sheet of weights.xls 6. Save “Output” sheet of weights.xls as weights.csv in directory c:\mics\weights 7. Execute weights_merge.sps program

  7. Step 1: Updating weights.xls • Spreadsheet has one row per cluster • Adjust the number of rows in “Calculations” to reflect the number of clusters in your survey • Do so by copying and pasting internal rows • Check that the totals cells have the correct ranges • Adjust the number of rows in “Output” • Check that data in “Output” is correct

  8. Step 2: Adding Sampling Info • Open weights.xls • Complete the “stratum sampling fraction” column • Complete the “cluster sampling fraction” column • Enter 1 if your weights don’t vary by cluster within a stratum • Otherwise enter the cluster sampling fraction

  9. Step 3: Defining Strata • Your survey has sampling strata. Examples: • all combinations of area (HH6) and region (HH7) • region • Lines 3-10 of weights_table.sps define the standard survey’s strata • Updates these statements to reflect the definition of strata in your country

  10. Step 4: Executing weights_table.sps • Open weights_table.sps in SPSS • Select Run--->all • Check output for error messages • Examine output table

  11. Step 5: Copying Output • Double-click inside the table to open it • Select the household results • Paste them in the “Calculations” sheet of weights.xls • Repeat for the women and children results • Save weights.xls

  12. Step 6: Saving the Output Sheet • Click on the “output” tab in the weights.xls spreadsheet • Select File ---> Save As • Navigate to the directory c:\mics\weights • Change the “save as type:” to “CSV (Comma delimited)(*.csv)” • file name should automatically change to weights.csv • Click the save button

  13. Step 7: Merging Weights into SPSS • Open weights_merge.sps in SPSS • Select Run ---> all • Check output for error messages • Open each data file—HH, HL, WM and CH — and check that weights were correctly added

  14. Useful Merging Commands get file = ‘filename.sav’. sort cases by varlist. save outfile = ‘filename.sav’ [/keep varlist] [/drop varlist] [/rename = (BI1 = BR1) (BI2 = BR2)]. erase file = ‘filename.sav’.

  15. MATCH FILES Command match files /file = * /file = ‘filename.sav’ /by varlist. match files /file = * /table = ‘filename.sav’ /by varlist.

  16. WEIGHTS_MERGE.SPS Source Files: c:\mics\spss\weights.sav Destination Files: hh.sav, hl.sav, wm.sav, ch.sav Match By: HH1 Variables Added: xxweight where xx is HH, WM or CH

  17. The Wealth Index • The MICS wealth index is an attempt to measure the socio-economic status of households • The analysis section of this process will be done at the 3rd workshop • The goal today is to discuss the programs and how they work

  18. Wealth Index Programs • There are two program related to the wealth index • WEALTH.SPS • This program calculates the wealth index • WEALTH_MERGE.SPS • This program adds the wealth index to the SPSS data files

  19. WEALTH.SPS • Calculates a wealth index using factor analysis • Inputs: • dichotomous variables related to household/individual assets • Outputs: • wlthscor - a wealth index score for each household • wlthind5 - a wealth quintile for each household

  20. A Recoding Example • Code below creates variable with value 1 if household owns a car, value 0 otherwise compute car = 0. if (hc10e = 1) car = 1. variable label car 'Household member owns: car/truck'. value label car 0 'No' 1 'Yes'.

  21. The Rest of the Program • The factor statement • creates wealth index score • The compute statement • generates household member weights • The rank statement • creates wealth quintiles • The save outfile statement • saves wealth variables in wealth.sav file

  22. WEALTH_MERGE.SPS Source Files: c:\mics\spss\wealth.sav Destination Files: hh.sav, hl.sav, wm.sav, ch.sav Match By: HH1, HH2 Variables Added: wlthscor, wlthind5

  23. GPS Readings • Some countries will take GPS readings during their MICS survey • These readings allow researchers to merge diverse data sets using a cluster’s location • Data sets that can be linked to the MICS data • Climate data • Agricultural data

  24. The GPS Form

  25. GPS Programs • GPS.DIC • CSPRO dictionary • GPSENTRY.ENT • CSPRO data entry application • GPS.SPS • SPSS version of GPS.DIC • GPS_MERGE.SPS • reads in GPS data and merges it onto SPSS data files

  26. GPS_MERGE.SPS Source Files: c:\mics\spss\gps.dat Destination Files: hh.sav, hl.sav, wm.sav, ch.sav Match By: HH1 Variables Added: all variables on GPS form