Sample Design covers all the steps involved in development and sample selection. Sample Design is very important aspect of survey methodology because it provide basis for good measurement of social and economic behavior from household and business surveys.
The functions of Sample Design Section consist of the following work related to development of efficient sample designs of sample surveys/censuses to be conducted by Pakistan Bureau of Statistics or other agencies: –
Sample Design Section provides Sample Design to all PBS regular surveys; few are given below:-
PBS also provides Sample Designing of ad-hoc Surveys requested by Government Departments, National and International Organizations; few surveys are given below:
There are also various other small surveys/studies in which PBS provides technical support for sample designing and selection of ultimate sampling units.
Total number of blocks – 2023 Population & Housing Census
Province | Rural | Urban | Total |
---|---|---|---|
Khyber Pakhtunkhwa | 24988 | 3885 | 28873 |
Punjab | 59284 | 34462 | 93746 |
Sindh | 19561 | 24252 | 43813 |
Balochistan | 9261 | 2596 | 11857 |
Islamabad | 904 | 833 | 1737 |
Total (I) | 113998 | 66028 | 180026 |
Azad Jammu & Kashmir | 3431 | 693 | 4124 |
Gilgit-Baltistan | 1165 | 174 | 1339 |
Total (II) | 4596 | 867 | 5463 |
Total (I+II) | 118594 | 66895 | 185489 |
Pakistan Bureau of Statistics (PBS) conducts routine and ad-hoc surveys spanning national, provincial and district domains. The Labor Force Survey (LFS) and Pakistan Social and Living Standards Measurement Survey (PSLM) are district specific, the household Integrated Economic Survey (HIES) focus on provincial representation, while Pakistan Demographic Surveys ensures national representation. It is worth mentioning here that, PDS and HIES utilizes provinces as strata where as PSLM and LFS districts are used for stratification.
A two stage stratified sample design is often used in PBS regular household based surveys where PSUs/EBs are selected at first stage and certain number of households as Secondary Sampling Units (SSUs) at the second stage.
Enumeration blocks are taken as Primary Sampling Units (PSUs). Sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS). The number of households in an enumeration block is considered as measure of size (MOS).
The total number of listed households of sample PSUs are taken as Secondary Sampling Units (SSUs). A specified number of households from each PSU are selected with equal probability using systematic random sampling technique with a random start.
For estimation of sample size; the core survey variables correlated to the survey objective and scope considered. The following formula used to estimate the sample size under simple random sampling
$$ n = \left(\frac{{4r(1-r)}}{{(RME \times r)^2}}\right) $$
Where,
n = the required sample size, expressed as number of households
4 = a factor to achieve the 95 percent level of confidence
r = the predicted or anticipated value of the indicator
RME = the relative margin of error
Generally, for the complex sample design, sample size inflated by incorporating the Design effect (Deff) and Response rate
$$ n = \frac{{4r(1-r)D_{\text{eff}}}}{{(RME \times r)^2} \times RR} $$
RR = the predicted response rate
deff = the design effect for the indicator
After estimation of sample size; the sample size is further distributed into various stratum as per survey objectives, i.e province, division, district, Rural/Urban. Different types of allocation used as shown below.
As per sampling scheme, Survey weights are developed for each stratum because different sampling fractions used in each stratum. For this reason, sample weights calculated, which later used in the subsequent analysis of the survey data. Sampling weight is the reciprocal of the sampling probabilities employed in selecting the number of sample households in that particular sampling stratum (h) and PSU (i):
$$ W_{\text{hi}} = 1/f_{\text{hi}} $$
The term fhi, the sampling fraction for the ith sample PSU in the hth stratum, and defined as the product of the probabilities of selection at every stage in each sampling stratum:
$$ f_{\text{hi}} = p_{\text{1hi}} X {\text{2hi}} $$
Where pshi is the probability of selection of the sampling unit at stage s for the ith sample PSU in the hth sampling stratum. Based on the sample design, the two stage probabilities of selection calculated as follows:
$$ ( p_{1hi} = \frac{n_h \times M_{hi}}{M_h} )$$,
where,
nh = number of sample PSUs selected in hth stratum
Mhi = number of households in the frame for the ith sample PSU in the hth stratum
Mh = total number of households in the frame for hth stratum
$$ ( p_{2hi} = \frac{m_hi }{M_hi} )$$,
where,
mhi= take of certain households from each PSU
M’hi = number of households listed in the ith sample PSU in the hth stratum
As we know automation has enhanced efficiency, accuracy, and productivity in the organizations and it has also reduced human error and labour costs. Sample Design Section uses Sample Design Software developed by Data Processing Centre team of Pakistan Bureau of Statistics for the Selection of PSUs from Population & Housing Census 2023.
Industry Surveys
A single stage sample design is often used in PBS Industry based surveys where sampling frame is provided by the Business Register Section. Based on some specific variables, stratification are made. After selection of PSUs, all establishments/ industries are covered.
Sample surveys are planned and designed based on the objectives and requirements of data users. The following information is pre-requisite to design sample surveys precisely.
Sample Design Section provides following services to different surveys and Censuses