Welfare Monitoring Survey 2007
Malawi, 2007
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Apr 12, 2012
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Identification
Survey ID Number
MWI_2007_WMS-R3_v01_M
Title
Welfare Monitoring Survey 2007
Subtitle
Third Round
Country
| Name | Country code |
|---|---|
| Malawi | MWI |
Study type
Core Welfare Indicators Questionnaire [hh/cwiq]
Series Information
The Welfare Monitoring Survey, Round 3 (WMS3) is the third round of WMS surveys, previously conducted around 2005 (WMS1) and 2006 (WMS2). WMS surveys are designed by NSO, and implemented by national agencies in participating countries. WMS was designed to monitor various indicators identified at the second Integrated Household Survey (IHS2) conducted in 2004 by National Statistical Office. Many questions and indicators in WMS3 are consistent and compatible with the prior round of (WMS2) and (WMS1), and there has been no changes in definition of indicators between rounds. Round 1 and 2 covered 5,400 households while round 3 comprised of 20,000 households.
Abstract
The objective of the WMS is to provide rapid information about the selected core indicators in the population, as well as monitoring changes over time when repeated on a regular basis. More specifically, the objectives of the WMS are:
· Elaborating main indicators for monitoring MDG's, MGDS indicators and other indicators on social welfare and basic needs of the population and various subgroups
· Monitoring changes over time in the MDG's, MGDS indicators and the other indicators used to monitor the development of living conditions and poverty in the population and various target groups
· Providing a database for social research.
· Elaborating on numerous sector programs aimed at improving the welfare of the population across the country. In order to prepare these programs, it is necessary to identify the problems to be addressed by the policies and to know to which extent the population is affected by these problems
The following are the contens covered in this survey:
· Characteristics of the Household Members
· Health
· Education
· Employment
· Food Security
· Housing Condition and Amenities
· Poverty Predictors
· Child health - Birth and anthropometric measures
· Child health - Malaria protection and Treatment
· Child health - Vaccination
· HIV/AIDS Testing and Knowledge
· Elaborating main indicators for monitoring MDG's, MGDS indicators and other indicators on social welfare and basic needs of the population and various subgroups
· Monitoring changes over time in the MDG's, MGDS indicators and the other indicators used to monitor the development of living conditions and poverty in the population and various target groups
· Providing a database for social research.
· Elaborating on numerous sector programs aimed at improving the welfare of the population across the country. In order to prepare these programs, it is necessary to identify the problems to be addressed by the policies and to know to which extent the population is affected by these problems
The following are the contens covered in this survey:
· Characteristics of the Household Members
· Health
· Education
· Employment
· Food Security
· Housing Condition and Amenities
· Poverty Predictors
· Child health - Birth and anthropometric measures
· Child health - Malaria protection and Treatment
· Child health - Vaccination
· HIV/AIDS Testing and Knowledge
Kind of Data
Sample survey data [ssd]
Unit of Analysis
A living standards survey questionnaire with the following units of analysis: individuals, households, and children under 5 years of age.
Scope
Notes
The scope of the Welfare Monitoring Survey includes:
- HOUSEHOLD:Household characteristics, Household listing, Interview Information, Characteristics of the Household Members, orphaned and vulnerable children, Health, Education, Employment, Food Security, Housing condition and amenities, Poverty predictors, Child module- Birth and anthropometric measures, Child health - Malaria Treatment, Child health - Vaccination, HIV/AIDS Knowledge, water and sanitation, household use of insecticide treated mosquito nets and durability of housing.
- WOMEN: Women's characteristics, child mortality, maternal and newborn health, marriage, polygyny, HIV/AIDS knowledge.
- CHILDREN: Children's characteristics, birth registration and early learning, vitamin A, breastfeeding, care of illness, malaria, immunization, and anthropometry.
- HOUSEHOLD:Household characteristics, Household listing, Interview Information, Characteristics of the Household Members, orphaned and vulnerable children, Health, Education, Employment, Food Security, Housing condition and amenities, Poverty predictors, Child module- Birth and anthropometric measures, Child health - Malaria Treatment, Child health - Vaccination, HIV/AIDS Knowledge, water and sanitation, household use of insecticide treated mosquito nets and durability of housing.
- WOMEN: Women's characteristics, child mortality, maternal and newborn health, marriage, polygyny, HIV/AIDS knowledge.
- CHILDREN: Children's characteristics, birth registration and early learning, vitamin A, breastfeeding, care of illness, malaria, immunization, and anthropometry.
Coverage
Geographic Coverage
National
Universe
The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Statistical Office (NSO) | Ministry of Development Planning and Cooperation |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Norwegian Government | NORAD | Funding and technical assistance |
Sampling
Sampling Procedure
Sample size
- Selection process (e.g., probability proportional to size or over sampling)
- Stratification (implicit and explicit)
- Stages of sample selection (WMS 2006 contained 4,500 households and 350 Enumeration Areas [EAs] across the country drawn as a two stage design)
- Design omissions in the sample
- Level of representation (More EAs were included in the sample so as to provide estimates at regional level)
- Strategy for absent respondents/not found/refusals (replacement or not) -(Sampling of the households was with replacement)
- Sample frame used, and listing exercise conducted to update it -(WMS 2006 sample was drawn from the The Second Integrated Household Survey [IHS2] 20003/04 sample. Since the EAs were from IHS2, there was no listing of the households)
- Selection process (e.g., probability proportional to size or over sampling)
- Stratification (implicit and explicit)
- Stages of sample selection (WMS 2006 contained 4,500 households and 350 Enumeration Areas [EAs] across the country drawn as a two stage design)
- Design omissions in the sample
- Level of representation (More EAs were included in the sample so as to provide estimates at regional level)
- Strategy for absent respondents/not found/refusals (replacement or not) -(Sampling of the households was with replacement)
- Sample frame used, and listing exercise conducted to update it -(WMS 2006 sample was drawn from the The Second Integrated Household Survey [IHS2] 20003/04 sample. Since the EAs were from IHS2, there was no listing of the households)
Weighting
It may be observed from the design above that the sample of WMS is not self weighting. A set of household weights has been calculated to obtain unbiased estimates at national and regional levels. WMS provides reliable estimates at the national level and regional level.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2007-07 | 2007-10 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
Training of field staff for the main Welfare Monitoring Survey was conducted over a 2 week period in July 2006. Since the enumerators were already experienced in field work, the training concentrated on the content of the questionnaire and practice in weighing and measuring of under five children. The Central Management of the project will be the responsibility of the Management team at NSO. Senior statisticians from this service will be responsible for the training of field staff and data entry clerks and the supervision and monitoring of fieldwork. This team will also be responsible for technical and administrative tasks of all the survey steps.
A team of National supervisors, consisting of experiences staff from the NSO was appointed. This team was responsible for the overall supervision of the field work, ensuring conformity of data collection and quality control. The team supervisors reported to them.
The survey work was carried out by mobile teams. Each team consisted of:
- 6 enumerators,
- A team supervisor
- Each team will be allocated a vehicle with space for 8 people
- Each vehicle will be allocated a driver
It was envisaged that 12 field teams were needed, each team covering about 83 Enumeration areas. The allocation of work areas to the teams were done in such a way as to minimize travelling time. The whole field work was done in 80 days. The allocation of enumerators to teams took into account proficiency in the relevant local languages.
The local authorities were contacted and informed of the team coming in by the supervisor. Coming into a local community, the supervisor had to present him-/herself to the administrator (the local community leader) and request their assistance to locate the EAs/clusters where the survey was to be done. It is very important that the EA map should be the guiding tool and not the local leader in the identification of the EA boundaries.
The driver was responsible for driving the team car, ensure maintenance of the car and transport the team members to the areas selected for the survey. He was under direct order of the supervisor. The enumerators were responsible for collecting the information from the selected households. Team supervisors were to supervise the work of the enumerators, who collected the data directly from the households. In turn, the team supervisors were supervised by the national WMS staff. The team supervisor assessed the work. After submition of the household questionnaires to the field supervisor upon completing your interviews, he or she returned to those questionnaires that were incomplete or that contain errors. If time allowed, had to go back to the survey households to make the corrections. The WMS team supervisors were themselves under the supervision of WMS National supervisors. These persons are permanent NSO staff assigned to oversee the administration of the WMS. Data entry was done through optical reading, at the Head Office and Analysis of the data that collected was also the responsibility of the WMS management team.
A team of National supervisors, consisting of experiences staff from the NSO was appointed. This team was responsible for the overall supervision of the field work, ensuring conformity of data collection and quality control. The team supervisors reported to them.
The survey work was carried out by mobile teams. Each team consisted of:
- 6 enumerators,
- A team supervisor
- Each team will be allocated a vehicle with space for 8 people
- Each vehicle will be allocated a driver
It was envisaged that 12 field teams were needed, each team covering about 83 Enumeration areas. The allocation of work areas to the teams were done in such a way as to minimize travelling time. The whole field work was done in 80 days. The allocation of enumerators to teams took into account proficiency in the relevant local languages.
The local authorities were contacted and informed of the team coming in by the supervisor. Coming into a local community, the supervisor had to present him-/herself to the administrator (the local community leader) and request their assistance to locate the EAs/clusters where the survey was to be done. It is very important that the EA map should be the guiding tool and not the local leader in the identification of the EA boundaries.
The driver was responsible for driving the team car, ensure maintenance of the car and transport the team members to the areas selected for the survey. He was under direct order of the supervisor. The enumerators were responsible for collecting the information from the selected households. Team supervisors were to supervise the work of the enumerators, who collected the data directly from the households. In turn, the team supervisors were supervised by the national WMS staff. The team supervisor assessed the work. After submition of the household questionnaires to the field supervisor upon completing your interviews, he or she returned to those questionnaires that were incomplete or that contain errors. If time allowed, had to go back to the survey households to make the corrections. The WMS team supervisors were themselves under the supervision of WMS National supervisors. These persons are permanent NSO staff assigned to oversee the administration of the WMS. Data entry was done through optical reading, at the Head Office and Analysis of the data that collected was also the responsibility of the WMS management team.
Questionnaires
Questionnaires
The questionnaires for the Generic WMS were structured questionnaires based on the WM Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status. The household questionnaire includes household characteristics, o health, education, employment, food security, poverty predictors, housing conditions and amenities, child health and anthropometric measures and HIV and AIDS knowledge.
In addition to the household questions, the questionnaire asked questions on children under age five. For children, the questionnaire was administered to the mother or caretaker of the child. The children's questions included children's characteristics, birth registration and early learning, vitamin A, malaria, immunization, and anthropometry.
The questionnaires were developed in English from the WMS Model Questionnaire.
In addition to the household questions, the questionnaire asked questions on children under age five. For children, the questionnaire was administered to the mother or caretaker of the child. The children's questions included children's characteristics, birth registration and early learning, vitamin A, malaria, immunization, and anthropometry.
The questionnaires were developed in English from the WMS Model Questionnaire.
Data Processing
Data Editing
Data editing took place at a number of stages throughout the processing, including:
a) Office editing and coding
b) During data entry
c) Structure checking and completeness
d) Secondary editing
e) Structural checking of SPSS data files
Detailed documentation of the editing of data can be found in the "Data processing guidelines" document provided as an external resource.
Data processing for this WMS involved: -
• Scanning and editing of questionnaires, using Eyes and Hands software
• Consistency checks and data cleaning in SPSS
• Designing tabulation programs in SPSS
• Final table editing in Microsoft Excel.
a) Office editing and coding
b) During data entry
c) Structure checking and completeness
d) Secondary editing
e) Structural checking of SPSS data files
Detailed documentation of the editing of data can be found in the "Data processing guidelines" document provided as an external resource.
Data processing for this WMS involved: -
• Scanning and editing of questionnaires, using Eyes and Hands software
• Consistency checks and data cleaning in SPSS
• Designing tabulation programs in SPSS
• Final table editing in Microsoft Excel.
Other Processing
Data were processed in clusters, with each cluster being processed as a complete unit through each stage of data processing. Each cluster goes through the following steps:
1) Questionnaire reception
2) Office editing and coding
3) Structure and completeness checking
4) Data entry by Scanning questionnaires, using Eyes and Hands software)
5) Interpretation of scanned entry
6) Verification of scanned entry
7) Transfering of verification data
8) Transforming of out files to SPSS flat files
9) Back up of raw data
10) Secondary editing and cleaning of SPSS flat files
11) Edited and cleaned data back up
After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files:
12) Restructuring of SPSS flat files into (in - individual, ch - children under 5)
13) Extracting (hhold-household) from SPSS flat file
14) Adding value and variable lebels to all the three SPSS files
15) Recoding of variables needed for analysis in all the three SPSS files
16) Adding of sample weights
17) Calculation of wealth quintiles and merging into data
18) Structural checking of SPSS files
19) Data quality tabulations
20) Production of analysis tabulations
Details of each of these steps can be found in the data processing documentation, data editing guidelines, data processing programs in SPSS, and tabulation guidelines.
Data entry was conducted by 6 data entry operators in two shifts, supervised by 1 data processing supervisors, using a total of 4 computers (4 data entry computers plus one supervisors' computer). All data entry was conducted at the National Statistical Office (Agriculture Division) head office using optical reading through scanners. For data entry, Eyes and Hands version 5.0 scanning software was used with a highly structured data entry program, using system controlled approach that controlled entry of each variable. All range checks and skips were controlled by the program and operators could not override these. A limited set of consistency checks were also included in the data entry program. In addition, the calculation of anthropometric was done during tabulation of the data for use during analysis. There were no open-ended responses ("Other" answers) were also coded, where the response matched an existing code in the questionnaire.
Structure and completeness checking ensured that all questions of the questionnare for the cluster had been entered, were structurally sound, and that eligible respondents in the individual, household and child part of the questionnaire were responded to the relevant questions.
100% verification of all variables was performed using independent verification, i.e. double entry of one third of the data, with separate comparison of data followed by modification of one or both datasets to correct keying errors by original operators who first keyed the files.
After completion of all processing in Eyes and Hands, all flat cluster out files were backed up before transforming to SPSS and merging data together using the SPSS add cases utility.
For tabulation and analysis SPSS versions 12.0 and 13.0 were used. Version 12.0 was originally used for all tabulation programs, except for poverty analysis where version 13.0 was used.
After transferring all files to SPSS, certain variables were recoded for use as background characteristics in the tabulation of the data, including grouping age, education, geographic areas as needed for analysis. In the process of recoding ages and dates some random imputation of dates (within calculated constraints) was performed to handle missing or "don't know" ages or dates. Additionally, a wealth (asset) index of household members was calculated using principal components analysis, based on household assets, and both the score and quintiles were included in the datasets for use in tabulations.
1) Questionnaire reception
2) Office editing and coding
3) Structure and completeness checking
4) Data entry by Scanning questionnaires, using Eyes and Hands software)
5) Interpretation of scanned entry
6) Verification of scanned entry
7) Transfering of verification data
8) Transforming of out files to SPSS flat files
9) Back up of raw data
10) Secondary editing and cleaning of SPSS flat files
11) Edited and cleaned data back up
After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files:
12) Restructuring of SPSS flat files into (in - individual, ch - children under 5)
13) Extracting (hhold-household) from SPSS flat file
14) Adding value and variable lebels to all the three SPSS files
15) Recoding of variables needed for analysis in all the three SPSS files
16) Adding of sample weights
17) Calculation of wealth quintiles and merging into data
18) Structural checking of SPSS files
19) Data quality tabulations
20) Production of analysis tabulations
Details of each of these steps can be found in the data processing documentation, data editing guidelines, data processing programs in SPSS, and tabulation guidelines.
Data entry was conducted by 6 data entry operators in two shifts, supervised by 1 data processing supervisors, using a total of 4 computers (4 data entry computers plus one supervisors' computer). All data entry was conducted at the National Statistical Office (Agriculture Division) head office using optical reading through scanners. For data entry, Eyes and Hands version 5.0 scanning software was used with a highly structured data entry program, using system controlled approach that controlled entry of each variable. All range checks and skips were controlled by the program and operators could not override these. A limited set of consistency checks were also included in the data entry program. In addition, the calculation of anthropometric was done during tabulation of the data for use during analysis. There were no open-ended responses ("Other" answers) were also coded, where the response matched an existing code in the questionnaire.
Structure and completeness checking ensured that all questions of the questionnare for the cluster had been entered, were structurally sound, and that eligible respondents in the individual, household and child part of the questionnaire were responded to the relevant questions.
100% verification of all variables was performed using independent verification, i.e. double entry of one third of the data, with separate comparison of data followed by modification of one or both datasets to correct keying errors by original operators who first keyed the files.
After completion of all processing in Eyes and Hands, all flat cluster out files were backed up before transforming to SPSS and merging data together using the SPSS add cases utility.
For tabulation and analysis SPSS versions 12.0 and 13.0 were used. Version 12.0 was originally used for all tabulation programs, except for poverty analysis where version 13.0 was used.
After transferring all files to SPSS, certain variables were recoded for use as background characteristics in the tabulation of the data, including grouping age, education, geographic areas as needed for analysis. In the process of recoding ages and dates some random imputation of dates (within calculated constraints) was performed to handle missing or "don't know" ages or dates. Additionally, a wealth (asset) index of household members was calculated using principal components analysis, based on household assets, and both the score and quintiles were included in the datasets for use in tabulations.
Data Appraisal
Estimates of Sampling Error
Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2006 WMS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.
Access policy
Contacts
| Name | URL | |
|---|---|---|
| The Commissioner of Statistics (National Statistics Office) | enquiries@statistics.gov.mw | www.nso.malawi.net |
Confidentiality
It is extremely important that you recognize that the survey is being conducted under the Statistics Act of 1967 that empowers you to collect information from selected households. However the information collected remains confidential to National Statistical Office and must therefore not be divulged to any unauthorized person.
Access conditions
The dataset has been anonymized and is available as a Public Use Dataset. It is accessible to all for statistical and research purposes only, under the following terms and conditions:
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the [National Statistical Office].
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the [National Statistical Office].
4. No attempt will be made to produce links among datasets provided by the [National Statistical Office), or among data from the [National Statistical Office] and other datasets that could identify individuals or organizations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the [National Statistical Office] will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to the [National Statistical Office].
The original collector of the data, the [National Statistical Office], and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the [National Statistical Office].
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the [National Statistical Office].
4. No attempt will be made to produce links among datasets provided by the [National Statistical Office), or among data from the [National Statistical Office] and other datasets that could identify individuals or organizations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the [National Statistical Office] will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to the [National Statistical Office].
The original collector of the data, the [National Statistical Office], and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Access authority
| Name | URL | |
|---|---|---|
| The Commissioner of Statistics (National Statistics Office) | enquiries@statistics.gov.mw | www.nso.malawi.net |
Metadata production
DDI Document ID
DDI_MWI_2007_WMS-R3_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| National Statistical Office | NSO | Ministry of Development Planning and Cooperation | Ducumentation of the DDI |
Date of Metadata Production
2012-03-06
DDI Document version
Version 02: Adopted from "MWI-NSO-WMS-2007-v01" ddi that were done by Malawi National Statistical Office.