The MICS Punjab, 2017-18 has as its primary objectives:
- To provide high quality data for assessing the situation of children, adolescents, women and households in Punjab;
- To furnish data needed for monitoring progress toward national goals, as a basis for future action;
- To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable;
- To validate data from other sources and the results of focused interventions;
- To generate data on national and global SDG indicators;
- To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention;
- To generate behavioural and attitudinal data not available in other data sources.
- v01: Edited, anonymous datasets for public distribution.
The sample for the MICS Punjab, 2017-18 was designed to provide estimates for a large number of indicators on the situation of children and women at the Punjab level, for urban and rural areas, and for all 36 districts of Punjab.
Unit of analysis
The survey covered all de jure household members (usual residents), all women age 15-49 years, all men age 15-49 years, all children under 5 and children age 5-17 years living in the household.
Producers and sponsors
Bureau of Statistics
United Nations Children’s Fund
United Nations Children’s Fund
The urban and rural areas within each district were identified as the main sampling strata, and the sample of households was selected in two stages. Within each stratum, a specified number of census enumeration areas were selected systematically with probability proportional to size. Using the listing of households from the Census 2017 for each sample enumeration area, provided by Pakistan Bureau of Statistics, a systematic sample of 20 households was drawn in each sample enumeration area1. The total sample size was 53,840 households in 2,692 sample clusters. All the selected enumeration areas were visited during the fieldwork period. As the sample is not self-weighting, sample weights are used for reporting survey results.
Response rate (Households): 97.9%
Essentially, by allocating specific number of sample households to each of the districts, different sampling fractions were used in each district since the size of the districts varied. For this reason, sample weights were calculated which were used in the subsequent analysis of the survey data.
The major component of the 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).
The term fhi is the sampling fraction for the i-th sample PSU in the h-th stratum and defined as the product of the probabilities of selection at every stage in each sampling stratum.
Where pshi is the probability of selection of the sampling unit at stage s for the i-th sample PSU in the h-th sampling stratum.
The number of households in each enumeration block (PSU) from the frame was used for the first stage selection and the updated number of households in the enumeration block from the actual household listing is generally different. Consequently, individual overall probabilities of selection for households in each sample enumeration block (cluster) were calculated.
After the completion of fieldwork, response rates were calculated for each sampling stratum. These were used to adjust the sample weights calculated for each cluster.
The non-response adjustment factors for the individual women and under-5 questionnaires were applied to the adjusted household weights. Numbers of eligible women and under-5 children were obtained from the list of household members in the Household Questionnaire for households where interviews were completed.
The weights for the questionnaire for individual men were calculated in a similar way. In this case, the number of eligible men in the list of household members in all the MICS sample households in the stratum was used as the numerator of the non-response adjustment factor, while the number of completed questionnaires for men in the stratum was obtained from the 50% subsample of households. Therefore, this adjustment factor includes an implicit subsampling weighting factor of 2 in addition to the adjustment for the non-response to the individual questionnaire for men.
In the case of the questionnaire for children age 5-17 years, in each sample household, one child was randomly selected from all the children in this age group recorded in the list of household members. The household weight for the children age 5-17 years is first adjusted based on the response rate for this questionnaire at the stratum level. Once this adjusted household weight is normalised as described below, it is multiplied by the number of children age 5-17 years recorded in the list of household members. Therefore, the weights for the individual children age 5-17 years will vary by sample household.
For the water quality testing (both in household and at source) a subsample of 3 households was selected from the 20 MICS sample households in each sample cluster. Therefore, the basic (unadjusted) household weight would be multiplied by the inverse of this subsampling rate.
Since the response rate may be different for the water quality testing for home consumption and at the source, the basic weights for each were adjusted separately for non-response at the stratum level.
The MICS Punjab, 2017-18 full (raw) weights for the households were calculated by multiplying the inverse of the probabilities of selection by the non-response adjustment factor for each stratum. These weights were then standardised (or normalised), one purpose of which is to make the weighted sum of the interviewed sample units equal to the total sample size at the national level. Normalisation is achieved by dividing the full sample weights (adjusted for nonresponse) by the average of these weights across all households at the national level. This is performed by multiplying the sample weights by a constant factor equal to the unweighted number of households at the national level divided by the weighted total number of households (using the full sample weights adjusted for non-response). A similar standardization procedure was followed in obtaining standardised weights for the individual women, men, under-5 questionnaires and water quality testing. Adjusted (normalised) household weights varied between 0.297817 and 3.101398 in the 2,692 sample enumeration areas (clusters).
Dates of collection
Mode of data collection
Data collection supervision
Team supervisors were responsible for the daily monitoring of fieldwork. Mandatory re-interviewing was implemented on three households per cluster. Daily observations of interviewer skills and performance were conducted.
During the fieldwork period, each team was visited multiple times by survey management team members and field visits were arranged for UNICEF MICS Team members.
Throughout the fieldwork, field check tables (FCTs) were produced weekly for analysis and action with field teams. The FCTs were customised versions of the standard tables produced by the MICS Programme.
Six questionnaires were used in the survey: 1) a household questionnaire to collect basic demographic information, the household, and the dwelling; 2) a water quality testing questionnaire administered in three households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) a questionnaire for individual men administered in every second household to all men age 15-49 years; 5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.
Data were received at the Bureau of Statistics, Punjab via Internet File Streaming System (IFSS) integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.
During data collection and following the completion of fieldwork, data were edited according to the editing process described in detail in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.
Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 24 Model syntax and tabulation plan developed by UNICEF were customised and used for this purpose.
Survey datasets are distributed at no cost for legitimate research, with the condition that we receive a description of the objectives of any research project that will be using the data prior to authorizing their distribution. Copies of all reports and publications based on the requested data must be sent to the following:
1. Name: Mr. Ch. Sajid Rasul, Director General,
Affiliation: Bureau of Statistics, Planning & Development Department, Govt. of Punjab
Address: 65-Trade center block, Ayub Chowk, Johar Town, Lahore, Pakistan
2. Name: Mr. Nouman Ghani, PME Specialist,
Affiliation: UNICEF Punjab Field Office, Lahore
Address: House 09, Aitchison Housing Society, Malik Naeem Road,
Johar Town, Lahore, Pakistan
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Bureau of Statistics, United Nations Children's Fund. Pakistan- Multiple Indicator Cluster Survey (MICS) 2017-2018, Punjab. Ref. PAK_2017_MICS-PUN_v01_M. Dataset downloaded from [url] on [date].
Data collection locations
Original archive where collection stored
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.