United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009 Sampling Frames and Sample Design Pres. 5

United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009 Sample Frames & Sample Design Frames: Material from which a sample is drawn  Each unit to be included in the universe  There should be no duplicates  Each unit should be well defined and distinguishable from other units (it should be unique)  Should be updated  For PES first stage units Primary Sampling Units (PSUs), in many countries area clusters

Choices of PSUs  Must have clearly identifiable and stable boundaries  Must completely cover the relevant population  Preferably must have measures of size  They should be mapped  Must cover the whole country  The number of PSUs must be relatively large United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009

Common problems with EAs  Incomplete coverage  Inadequate maps  Poor measures of size or lack of them United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009

Sampling Strategies  Probability household surveys  It is usual to make inferences in a PES for a number of analytical domains  Relatively large samples necessary in each domain for reliable estimates  Stratified cluster sample design-common  First-stage units–area clusters/EAs  PPS systematic sample selection  Second-stage, common to canvass all persons in selected households

United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009 Multi-stage Cluster Sampling  Usually used when sampling hierarchical populations  e.g. persons within households which can be selected from EAs  The hierarchical levels are called stages  First stage units are called primary sampling units (PSUs) e.g. EAs  Second stage units are called secondary sampling units (SSUs) e.g. households  Last stage units are called ultimate sampling units (USUs) e.g. persons

Why Area sampling?  At national level only a frame of EAs is required  Data collection is more efficient  Lower costs compared to simple random sampling (SRS)  Supervision is easier  However, estimates are prone to higher variability compared to SRS United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009

Importance of Stratification  Population subdivided into heterogeneous groups that are internally homogenous  Stratification based on variables correlated with the extent of coverage-geopolitical subdivisions  Internal homogeneity can be maintained with regard to socio-demographic variables e.g. urban stratum  Common strata may include: rural, urban, provinces etc.

PES sample design  A single-stage stratified clustered sample design is commonly adopted  When the PSUs i.e. EAs are selected all households in selected EAs are canvassed  This is necessary because they have to be matched with the census population United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009

PES sample selection  First stage units selected are PSUs (EAs)  At the next stage all households in selected EAs are included in the sample United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009

Sample Size Sample size depends on estimate requirements  Geographic level (national, province, urban/rural)  Demographic (sex, age)  Reliability  Confidence level

United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009 Sample Size  To estimate sample size in the case of proportions you must: Know the occurrence of the event in the population Specify a confidence interval Specify the margin of error or precision  To estimate percentage of households with access to family planning services about 55%; confidence interval for a standard error of 2 %  The sample size works out to be:

United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009 Sample Size  Adjusting for non-response, e.g. 10%:  Adjusting for the design effect for a complex sample design Design effect of 2 is a default value : 2 x 688 =1,376 This may apply to each province (analysis) domains. If they are five provinces Sample size will be 5 x 1, 376 = 6,880

Sample Size United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009

Sample Size United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009

Sample Size United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis Ababa, Ethiopia, September 2009

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