United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 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, Bangkok, Thailand, May, 2010 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
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 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, Bangkok, Thailand, May, 2010 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.
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Multi-stage Cluster Sampling Usually used when sampling hierarchical populations 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 within households which can be selected from EAs
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 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, Bangkok, Thailand, May, 2010 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, Bangkok, Thailand, May, 2010 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, Bangkok, Thailand, May, 2010 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, or more rarely only a sample (e.g. 1 every 5). This is beneficial for matching operation
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 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, Bangkok, Thailand, May, 2010 Sample Size To estimate sample size in the case of proportions you must: Know the occurrence of the event in the population by domain of estimation Specify a confidence interval (e.g 95%) Specify the margin of error or precision (e.g 1%)
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Sample Size (contd.) To estimate sample size in the case of proportions, the following formula can be used:
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Sample size (contd.) From that it is deduced :
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Sample Size (contd.) Example: To estimate percentage of households omitted in the census (expected about 5%) ; confidence interval at 95% (t=1.96) for a margin of 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, Bangkok, Thailand, May, 2010 Sample Size (contd.) 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 507 =1,014 This may apply to each province (analysis) domains. If they are five provinces Sample size will be 5 x 1,014 = 5,070
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Sample selection procedures For greater convenience and efficiency, the sample of PSUs should be selected using a systematic procedure. If there are good measures of size, probability proportional to size (PPS) should be used to increase the efficiency of the sample design. Otherwise, the selection should be made with equal probabilities
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Sample selection procedures -- PPS 1)Order the EAs geographically (and, if applicable, by other stratification characteristic) to allow implicit stratification 2)Record for each EA i of the stratum h the measure of size M hi, typically the number of households or persons from the census mapping operation 3)Cumulate the size measures down the list of EAs, the last cumulated number will be equal to the total number of households (or persons) in stratum h (M h ) 4)Determine the number of EAs (n h ) to be selected in a stratum according to the allocation
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Sample selection procedures –- PPS (contd.) 5)Determine the sampling interval (I h ) by: 6)Obtain a random number (A h ) between 1 and I h inclusively; 7) Determine the selected EAs as follows: S hi =A h + (i-1) x I h, for i = 1,...,n h, rounded up to the next integer The i-th EA selected will be the one for which the cumulated measure is closest to S hi without exceeding it.
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Illustration: Selection of Eight EAs with probability Proportional to size
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Sample Allocation – 2009 Kenyan PES
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok, Thailand, May, 2010 Thank You!