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Multiple Indicator Cluster Surveys Survey Design Workshop

Multiple Indicator Cluster Surveys Survey Design Workshop. Sampling Overview. Introduction. MICS is multi-national survey program Consistency and comparability between surveys is important MICS based on national stratified multi-stage sample

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Multiple Indicator Cluster Surveys Survey Design Workshop

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  1. Multiple Indicator Cluster SurveysSurvey Design Workshop Sampling Overview MICS4 Survey Design Workshop

  2. Introduction • MICS is multi-national survey program • Consistency and comparability between surveys is important • MICS based on national stratified multi-stage sample • Workshop session covers highlights of MICS sampling, including: • Identifying effective sampling frame and sample design • Determinants and calculation of sample size MICS4 Survey Design Workshop

  3. Importance of correct sampling procedures • Sample design will affect inferences of survey results • Coverage of frame and appropriate probability sampling are critical • Accuracy of survey results depends on both sampling and non-sampling errors MICS4 Survey Design Workshop

  4. Key concepts in proper sampling • Use accepted probability techniques at every stage of selection • Use of simple sampling methodology • Use the latest census as the sampling frame when available • Sampling in two stages • Use of clusters of moderate size • Use of an adequate sample size MICS4 Survey Design Workshop

  5. MICS4 prototype sample design • Manual presents different sampling options • All options involve two or three-stage cluster sampling • Primary sampling units (PSUs) – census enumeration areas • Listing in sample clusters or use of compact clusters • Sample households selected from listing • Option for each country depends on type of frame and availability of existing samples MICS4 Survey Design Workshop

  6. Sampling option 1 – use existing sample • Most cost-effective approach • Determine whether existing sample is appropriate • Probability sample • Known probabilities of selection at each stage • Nationally representative • Sufficient number of sample PSUs for MICS • Example – 2008 Mozambique MICS3 MICS4 Survey Design Workshop

  7. Sampling option 1 – continued • Determine when listing of households in sample EAs was conducted • Listing can be used if less than 1 year old • Generally select new sample of households from listing • Possible to use selected households from other survey • Consider response burden, analytical needs for both surveys • Conduct new listing in existing sample or subsample of EAs • Availability of master sampling frame in some countries MICS4 Survey Design Workshop

  8. Sampling option 2 – standard segment design • Based on standard segments of about 500 persons or 100 households • Effective procedure when some EAs are too large for listing • Three-stage sample design • Measure of size for each EA – calculated number of segments • EAs selected systematically with PPS • Larger sample EAs with 2 or more segments subdivided • One segment selected in each EA for listing, enumeration MICS4 Survey Design Workshop

  9. Sampling option 3 – modified segment design • Three-stage sample design • Small compact clusters with about 20-30 households • Measure of size of EAs – calculated number of compact clusters • EAs selected systematically with PPS • Mapping and segmentation in all sample EAs • One compact cluster selected in each sample EA for listing, enumeration MICS4 Survey Design Workshop

  10. Relationship of sampling with other aspects of survey planning • Survey budget – may determine maximum sample size • Sampling plan should also take into account required timing of MICS results • Estimate costs and time related to PSUs – transportation, listing • Costs related to sample households – cost of interviewing (days of enumeration) MICS4 Survey Design Workshop

  11. Sampling and fieldwork organization • Effective balance of number of sample PSUs and cluster size • Dispersion of sample affects transportation costs, travel time • Size of team of enumerators and supervisor • Interviewer workload MICS4 Survey Design Workshop

  12. Factors that affect sample size • Budget and resource constraints • Timing and logistical considerations • Select key indicators • Required level of precision • Need for sub-national estimates • Regions, provinces, urban/rural domains MICS4 Survey Design Workshop

  13. Selecting key indicators • Person variables (rates) • Important indicator that will yield the largest sample size • Estimated rates between 15 and 20% • Target population that comprises a small proportion of the total population • Children aged 12 to 23 months MICS4 Survey Design Workshop

  14. Sample size determinants – sampling parameters • Level of precision – standard error, coefficient of variation (CV) • Acceptable level of error - margin of error, relative margin of error • Level of confidence – 95% • Design effect (DEFF) – depends mostly on level of clustering in the sample • Average household size • Proportion of base population in total population • Adjustment for non-response MICS4 Survey Design Workshop

  15. Use of previous MICS or DHS results • Review sample design of previous survey • Examine sample size and allocation to geographic domains • Study level of precision for key indicators • Design effects • 95% confidence intervals • Results can be used to determine sample size and allocation for new MICS MICS4 Survey Design Workshop

  16. Formula for sample size calculation • Two similar spreadsheet templates for MICS4 • Entry cell for each sampling parameter • Formula for calculating required number of sample households • Presentation and discussion of spreadsheets MICS4 Survey Design Workshop

  17. Sample Size Formula where • n is the required sample size, expressed as number of households, for the KEY indicator • 4 is factor to achieve 95 percent level of confidence, • r is anticipated prevalence rate for key indicator, • 1.1 is factor to raise sample size by 10 percent for potential nonresponse, • deff is shortened symbol for design effect, • 0.12r is margin of error to be tolerated, defined as 12 percent of r (12 percent thus represents the relative margin of error), • p is proportion of total population that smallest group comprises, and • is average household size. MICS4 Survey Design Workshop

  18. Sample size reference table • Table 4.3 in Chapter 4 of MICS manual • Can be used for specific set of parameters: • Target population is 2.5% of total population • DEFF = 1.5 • Nonresponse rate is 10% • Relative margin of error is 12% • 95% level of confidence MICS4 Survey Design Workshop

  19. Sample Size (Households) to Estimate Coverage Rates for Smallest Target Population MICS4 Survey Design Workshop

  20. Number of PSUs and cluster size • More PSUs and smaller clusters • Statistically more efficient – greater dispersion of sample • More costly – transportation, listing • Minimum number of PSUs - 300 to 400 at national level • Minimum of 30 PSUs for subnational domains • Number of sample households per cluster generally in range of 15 to 30 households MICS4 Survey Design Workshop

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