Stratiication Afghanistan - National Risk and Vulnerability Survey 2011-2012, Living Conditions Survey NRVA 2011 12 report
IV.7 Sample design implementation
Two major issues impeded the implementation of the sampling design during the ieldwork period. One was the security situation in parts of the country, which halfway the survey led to the introduction of the reserve sample. In total 133 clusters 6.3 percent of the original 2,100 clusters were thus replaced with ones from other districts. In addition, 17 clusters, representing 170 households, were not implemented and not replaced. Figure 1.1 in chapter 2 shows in which districts the survey was implemented according to the sample design, and in which districts fewer or no data collection took place. A second interference with the sampling design concerned delays in the ieldwork due to administrative, logistic and technical issues. This had the following implications: • The ieldwork was extended from 12 to 16 months in order to capture the full sample. • Information for spring and summer time was collected in two different years 2011 and 2012 • The Kuchi sample was implemented in winter 2011-12 and summer 2012 instead of summer 2011 and winter 2011-12. • There was especially an underrepresentation of coverage during the autumn season. Table IV.2 presents the number of households interviewed by season and year. In total 20,828 households were covered, 172 0.8 percent short of the targeted sample. Table IV.2 Interviewed households, by year, and by season Shamsi calendar Season Year Total 1390 1391 Spring 1,671 4,866 6,537 Summer 3,289 4,149 7,438 Autumn 2,753 2,753 Winter 4,100 4,100 Total 11,813 9,015 20,828 Non-response within clusters was very limited. Only in 797 3.8 percent of the scheduled interviews in the 2,099 accessed EAs households were not available or refused or were unable to participate. In 779 of these cases households were replaced by reserve households listed in the cluster reserve list, leaving 18 households unaccounted for 0.09 percent.IV.8 Calculation of sampling weights and post-stratiication
By design, the sample observations in the sample are self-weighted. An implication of this is that the expansion factor for all observations within a speciic stratum is simply the ratio of the number of households in a stratum divided by the number of sample observations from each stratum. This applies to the provincial strata as well as to the Kuchi stratum. For the purpose of calculating the sampling weights, scaling factors were constructed based on the number of households in Afghanistan. The estimated number of households was derived from the CSO population projections by province for January 2012. For the settled population, the provincial population was divided by the average household size in the NRVA 2011 sample of each province to obtain the number of households in the middle of the survey period. This ratio is the scaling factor Whsq that expands the sample of households to the total population of households and relects the product of the probabilities of selection for the Primary Sampling Unit PSU and the Ultimate Sampling Unit USU: Whsq = [probPSU probUSU] where h identiies the household, s identiies the stratum, and q identiies the calendar quarter.Parts
» Pilot training and pilot survey
» Training and selection of ield staff
» Sampling design and implementation
» Population structure and distribution
» Marriage patterns Household composition and marriage patterns .1 Household structure
» Introduction Labour force participation
» Economic sector and occupation
» Characteristics of the employed population .1 Status in employment percent
» Irrigated land Farming and horticulture
» Rain-fed land Farming and horticulture
» Horticulture Farming and horticulture
» Farming input costs Farming and horticulture
» Sale of animals and animal products
» Livestock production factors Livestock .1 Livestock numbers
» Main reason not to use veterinary services in percentages
» Measuring trends in poverty 2007-2011 percent
» b, c Growth and distribution percent
» Demographic proile Poverty proile
» Household head characteristics Poverty proile
» Comparison of food security between NRVA 2011-12 and NRVA 2007-08
» Characterization by asset ownership
» Harvest and lean season’s differences
» Availability of different food items by residence
» Sources of food items by population group and food security status
» Sources of food items by main income source
» Sources of food items by season
» Food Consumption Score Food consumption .1 Dietary diversity
» Contribution of different food groups to caloric intake
» Change in educational attendance
» Literacy .1 Literacy in residential and gender perspective Sex Gender equity indicators
» Gender equity indicators percent percent
» Distance to nearest health facility and costs to reach it
» Public clinic Public clinic District or provincial hospital District or provincial hospital
» Private doctor or clinic Private doctor or clinic
» District or provincial hospital
» Household expenditure on health
» Other health-related expenditure Total health-related expenditure
» Visits to health care facilities
» Use of health care providers
» In-patient health care provider
» Out-patient health care provider
» Birth registration Child health
» Child health indicators Child health
» Ante-natal care Maternal health
» Dwelling characteristics Tenancy and dwelling characteristics .1 Tenancy
» Construction material of walls
» Construction material of roof
» Construction material of floor
» Durability of dwelling percent
» Household amenities .1 Water and sanitation percent
» percent Other household amenities
» Coping strategies Household shocks and coping strategies .1 Household shocks
» Steering Committee Technical Advisory Committee
» Cluster size and number of clusters
» Sampling stages and selection process
» Calculation of sampling weights and post-stratiication
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