Multiple Indicator Cluster Survey, Palestinian Refugee Camps, Lebanon 2006, Monitoring the Situation of Children and Women
Lebanon, 2005 - 2006
The Palestinian Central Bureau of Statistics and Natural Resources
Identification
Survey ID Number
LBN_2006_MICSPAL_v01_M
Title
Multiple Indicator Cluster Survey, Palestinian Refugee Camps, Lebanon 2006, Monitoring the Situation of Children and Women
Subtitle
Monitoring the Situation of Children and Women
Country/Economy
| Name |
|---|
| Palestinian Refugee Camps, Lebanon |
Study type
Multiple Indicator Cluster Survey - Round 3 [hh/mics-3]
Series Information
The Multiple Indicator Cluster Survey, Round 3 (MICS3) is the third round of MICS surveys, previously conducted around 1995 (MICS1) and 2000 (MICS2). Many questions and indicators are consistent and compatible with the prior round of MICS (MICS2) but less so with MICS1, although there have been a number of changes in definition of indicators between rounds. Details can be found by reviewing the indicator definitions.
Abstract
The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular. MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.
Survey Objectives
The 2006 Palestinian Refugee Camps, Lebanon Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Generic
- To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action;
- To contribute to the improvement of data and monitoring systems in Generic and to strengthen technical expertise in the design, implementation, and analysis of such systems.
Survey Content
MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.
Survey Implementation
The surveys are typically carried out by government organizations, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.
Survey results
Results from the surveys, including national reports, standard sets of tabulations and micro level datasets will all be made widely available after completion of the surveys. Results from the surveys will also be made available in DevInfo format. DevInfo v5.0 is a powerful database system which has been adapted from UNICEF's ChildInfo technology to specifically monitor progress towards the Millennium Development Goals. MICS Results will also be available through UNICEF's web site dedicated to monitoring the situation of children and women at www.childinfo.org. Results of the prior round of MICS can already be found at this site.
Survey Objectives
The 2006 Palestinian Refugee Camps, Lebanon Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Generic
- To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action;
- To contribute to the improvement of data and monitoring systems in Generic and to strengthen technical expertise in the design, implementation, and analysis of such systems.
Survey Content
MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.
Survey Implementation
The surveys are typically carried out by government organizations, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.
Survey results
Results from the surveys, including national reports, standard sets of tabulations and micro level datasets will all be made widely available after completion of the surveys. Results from the surveys will also be made available in DevInfo format. DevInfo v5.0 is a powerful database system which has been adapted from UNICEF's ChildInfo technology to specifically monitor progress towards the Millennium Development Goals. MICS Results will also be available through UNICEF's web site dedicated to monitoring the situation of children and women at www.childinfo.org. Results of the prior round of MICS can already be found at this site.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households (defined as a group of persons who usually live and eat together)
De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)
Women aged 15-49
Children aged 0-4
De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)
Women aged 15-49
Children aged 0-4
Version
Version Description
Version 1.0: Edited data used for final report
Version Date
2008-11-27
Scope
Notes
Lebanon (Palestinian Refugee Camps) scope of the Multiple Indicator Cluster Survey includes:
HOUSEHOLD QUESTIONNAIRE : Household Listing, Education, Water and Sanitation Facilities, Household , Background Characteristics, Child Discipline, Child Labour, and Salt Iodization.
WOMEN'S QUESTIONNAIRE: Women's characteristics, Child Mortality, Tetanus Toxoid, Maternal and Newborn Health, Contraception, and HIV/AIDS.
CHILDREN'S QUESTIONNAIRE: Children's characteristics, Birth Registration and Early Learning, Vitamin A, Breastfeeding, Care of Illness, Immunization, and Anthropometry.
HOUSEHOLD QUESTIONNAIRE : Household Listing, Education, Water and Sanitation Facilities, Household , Background Characteristics, Child Discipline, Child Labour, and Salt Iodization.
WOMEN'S QUESTIONNAIRE: Women's characteristics, Child Mortality, Tetanus Toxoid, Maternal and Newborn Health, Contraception, and HIV/AIDS.
CHILDREN'S QUESTIONNAIRE: Children's characteristics, Birth Registration and Early Learning, Vitamin A, Breastfeeding, Care of Illness, Immunization, and Anthropometry.
Topics
| Topic | Vocabulary |
|---|---|
| Household listing | MICS Topics |
| Education | MICS Topics |
| Water and sanitation | MICS Topics |
| Household background characteristics | MICS Topics |
| Child discipline | MICS Topics |
| Child labour | MICS Topics |
| Salt iodization | MICS Topics |
| Women's background | MICS Topics |
| Child mortality | MICS Topics |
| Tetanus toxoid | MICS Topics |
| Maternal and newborn health | MICS Topics |
| Contraception | MICS Topics |
| HIV/AIDS | MICS Topics |
| Children's background | MICS Topics |
| Birth registration | MICS Topics |
| Early learning | MICS Topics |
| Vitamin A | MICS Topics |
| Breastfeeding | MICS Topics |
| Care of illness | MICS Topics |
| Immunization | MICS Topics |
| Anthropometry | MICS Topics |
Coverage
Geographic Coverage
The survey is representative and covers the whole of refugee camps and gatherings in Lebanon.
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 |
|---|---|
| The Palestinian Central Bureau of Statistics and Natural Resources | PCBS |
Producers
| Name | Affiliation | Role |
|---|---|---|
| UNICEF Lebanon Country Office | UNICEF | International technical assistance |
| Pan Arab Project for Family Health | Arab League | International technical assistance |
| Palestinian NGO's | Funding of survey implementation | |
| Lebanese Ministry of Health | Funding of survey implementation |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| UNICEF Lebanon Country Office | UNICEF | Funding of survey implementation |
| UNICEF HQ | UNICEF | Funding of survey implementation |
Sampling
Sampling Procedure
The sample for the Multiple Indicator Cluster Survey (MICS) in Palestinian Refugee Camps and Gatherings in Lebanon was designed to provide estimates on a large number of indicators on the situation of children and women at the geographical area and camp/gathering level, for urban and rural areas, and for 12 camps and 12 gatherings in 5 geographical areas. With this design we could monitor a large number of women and children indicators at the geographical area and camp level for urban and rural areas.
The sample population (based on the Palestinian Refugee Camps and Gatherings in Lebanon Census of 1999) was divided into equal clusters each containing 20 households (totaling 1300 clusters). Sample clusters (310 clusters, i.e. 6200 households) were drawn with uniformity, random start and a sampling fraction of 0.25.
The sample population (based on the Palestinian Refugee Camps and Gatherings in Lebanon Census of 1999) was divided into equal clusters each containing 20 households (totaling 1300 clusters). Sample clusters (310 clusters, i.e. 6200 households) were drawn with uniformity, random start and a sampling fraction of 0.25.
Deviations from the Sample Design
No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates.
Response Rate
The response rate of households, mothers and children was remarkably high. Of the 6200 households selected for the sample, only 33 households could not be interviewed thus making the household response rate 99.5 percent.
In the interviewed households, 4001 ever married women (age 15-49) were identified. Of these, 3955 were successfully interviewed, yielding a response rate of 98.9 percent. In addition, 2431 children under age five were listed in the household questionnaire. Questionnaires were completed for 2381 of these children, which corresponds to a response rate of 97.9 percent.
In the interviewed households, 4001 ever married women (age 15-49) were identified. Of these, 3955 were successfully interviewed, yielding a response rate of 98.9 percent. In addition, 2431 children under age five were listed in the household questionnaire. Questionnaires were completed for 2381 of these children, which corresponds to a response rate of 97.9 percent.
Weighting
Sample is self-weighted, and sample weights were not used for analysis. In order to make possible usage of syntax files developed for global MICS project in all data files there are variables for sample weight and their value is set to 1.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2005-04-25 | 2006-02-05 |
Data Collection Mode
Face-to-face [f2f]
Supervision
The data were collected by 10 teams; each comprised of 4 interviewers, one measurer and a supervisor.
The role of the supervisor was to coordinator field data collection activities, including management of the field teams, supplies and equipment, finances, maps and listings, coordinate with local authorities concerning the survey plan and make arrangements for accomodation and travel. Additionally, the field supervisor assigned the work to the interviewers, spot checked work, maintained field control documents, and sent completed questionnaires and progress reports to the central office.
The field editor was responsible for reviewing each questionnaire at the end of the day, checking for missed questions, skip errors, fields incorrectly completed, and checking for inconsistencies in the data. The field editor also observed interviews and conducted review sessions with interviewers.
Responsibilities of the supervisors and field editors are described in the Instructions for Supervisors and Field Editors, together with the different field controls that were in place to control the quality of the fieldwork.
Field visits were also made by a team of central staff on a periodic basis during fieldwork. The senior staff of GenCenStat also made 3 visits to field teams to provide support and to review progress.
The role of the supervisor was to coordinator field data collection activities, including management of the field teams, supplies and equipment, finances, maps and listings, coordinate with local authorities concerning the survey plan and make arrangements for accomodation and travel. Additionally, the field supervisor assigned the work to the interviewers, spot checked work, maintained field control documents, and sent completed questionnaires and progress reports to the central office.
The field editor was responsible for reviewing each questionnaire at the end of the day, checking for missed questions, skip errors, fields incorrectly completed, and checking for inconsistencies in the data. The field editor also observed interviews and conducted review sessions with interviewers.
Responsibilities of the supervisors and field editors are described in the Instructions for Supervisors and Field Editors, together with the different field controls that were in place to control the quality of the fieldwork.
Field visits were also made by a team of central staff on a periodic basis during fieldwork. The senior staff of GenCenStat also made 3 visits to field teams to provide support and to review progress.
Data Collection Notes
Training for the fieldwork team members (interviewers, measurers and supervisors) was conducted centrally (in Beirut) for 10 days from 15 to 24 December 2006. The data were collected by 10 teams; each comprised of 4 interviewers, one measurer and a supervisor. Fieldwork began on April 25 2005 and was concluded on February 5, 2006.
Data Collectors
| Name | Abbreviation |
|---|---|
| The Palestinian Central Bureau of Statistics and Natural Resources | PCBS |
Questionnaires
Questionnaires
Three sets of questionnaires were used in the survey:
1) a household questionnaire was used to collect information on all household members, the household, and the dwelling;
2) a women’s questionnaire administered in each household to all women aged 15-49 years;
3) an under-5 questionnaire, administered to mothers or caretakers of all children under 5 living in the household.
The questionnaires included the following modules: Household Questionnaire, Household Listing, Education, Water and Sanitation Facilities, Household Background Characteristics, Child Labour, and Salt Iodization.
Questionnaire for Individual Women: Child Mortality, Tetanus Toxoid, Maternal and Newborn Health, Contraception, and - HIV/AIDS.
Questionnaire for Children Under Five: Birth Registration and Early Learning, Vitamin A, Breastfeeding, Care of Illness, Immunization, and Anthropometry.
The questionnaires are based on the MICS3 model questionnaire. Changes in format were made to the UNICEF MICS3 model Arabic version questionnaires that were pre-tested during March 2006.
1) a household questionnaire was used to collect information on all household members, the household, and the dwelling;
2) a women’s questionnaire administered in each household to all women aged 15-49 years;
3) an under-5 questionnaire, administered to mothers or caretakers of all children under 5 living in the household.
The questionnaires included the following modules: Household Questionnaire, Household Listing, Education, Water and Sanitation Facilities, Household Background Characteristics, Child Labour, and Salt Iodization.
Questionnaire for Individual Women: Child Mortality, Tetanus Toxoid, Maternal and Newborn Health, Contraception, and - HIV/AIDS.
Questionnaire for Children Under Five: Birth Registration and Early Learning, Vitamin A, Breastfeeding, Care of Illness, Immunization, and Anthropometry.
The questionnaires are based on the MICS3 model questionnaire. Changes in format were made to the UNICEF MICS3 model Arabic version questionnaires that were pre-tested during March 2006.
Data Processing
Data Editing
Data editing took place at a number of stages throughout the processing (see Other 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 in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)
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 in the MICS Manual (http://www.childinfo.org/mics/mics3/manual.php)
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) Data entry
4) Structure and completeness checking
5) Verification entry
6) Comparison of verification data
7) Back up of raw data
8) Secondary editing
9) Edited data back up After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files:
10) Export to SPSS in 4 files (hh - household, hl - household members, wm - women, ch - children under 5)
11) Recoding of variables needed for analysis
12) Adding of sample weights
13) Calculation of wealth quintiles and merging into data
14) Structural checking of SPSS files
15) Data quality tabulations
16) 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 CSPro and SPSS, and tabulation guidelines.
Data entry was conducted by 12 data entry operators in tow shifts, supervised by 2 data entry supervisors, using a total of 7 computers (6 data entry computers plus one supervisors computer). All data entry was conducted at the GenCenStat head office using manual data entry. For data entry, CSPro version 2.6.007 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 inthe data entry program. In addition, the calculation of anthropometric Z-scores was also included in the data entry programs for use during analysis. Open-ended responses ("Other" answers) were not entered or coded, except in rare circumstances where the response matched an existing code in the questionnaire.
Structure and completeness checking ensured that all questionnaires for the cluster had been entered, were structurally sound, and that women's and children's questionnaires existed for each eligible woman and child.
100% verification of all variables was performed using independent verification, i.e. double entry of 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 CSPro, all individual cluster files were backed up before concatenating data together using the CSPro file concatenate utility.
For tabulation and analysis SPSS versions 10.0 and 14.0 were used. Version 10.0 was originally used for all tabulation programs, except for child mortality. Later version 14.0 was used for child mortality, data quality tabulations and other analysis activities.
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) Data entry
4) Structure and completeness checking
5) Verification entry
6) Comparison of verification data
7) Back up of raw data
8) Secondary editing
9) Edited data back up After all clusters are processed, all data is concatenated together and then the following steps are completed for all data files:
10) Export to SPSS in 4 files (hh - household, hl - household members, wm - women, ch - children under 5)
11) Recoding of variables needed for analysis
12) Adding of sample weights
13) Calculation of wealth quintiles and merging into data
14) Structural checking of SPSS files
15) Data quality tabulations
16) 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 CSPro and SPSS, and tabulation guidelines.
Data entry was conducted by 12 data entry operators in tow shifts, supervised by 2 data entry supervisors, using a total of 7 computers (6 data entry computers plus one supervisors computer). All data entry was conducted at the GenCenStat head office using manual data entry. For data entry, CSPro version 2.6.007 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 inthe data entry program. In addition, the calculation of anthropometric Z-scores was also included in the data entry programs for use during analysis. Open-ended responses ("Other" answers) were not entered or coded, except in rare circumstances where the response matched an existing code in the questionnaire.
Structure and completeness checking ensured that all questionnaires for the cluster had been entered, were structurally sound, and that women's and children's questionnaires existed for each eligible woman and child.
100% verification of all variables was performed using independent verification, i.e. double entry of 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 CSPro, all individual cluster files were backed up before concatenating data together using the CSPro file concatenate utility.
For tabulation and analysis SPSS versions 10.0 and 14.0 were used. Version 10.0 was originally used for all tabulation programs, except for child mortality. Later version 14.0 was used for child mortality, data quality tabulations and other analysis activities.
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 PLS Lebanon MICS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors can be evaluated statistically. The sample of respondents to the 2006 PLS Lebanon MICS is only one of many possible samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differe somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability in the results of the survey between all possible samples, and, although, the degree of variability is not known exactly, it can be estimated from the survey results. The sampling erros are measured in terms of the standard error for a particular statistic (mean or percentage), which is the square root of the variance. Confidence intervals are calculated for each statistic within which the true value for the population can be assumed to fall. Plus or minus two standard errors of the statistic is used for key statistics presented in MICS, equivalent to a 95 percent confidence interval.
If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formulae for calculating sampling errors. However, the 2006 PLS Lebanon MICS sample is the result of a multi-stage stratified design, and consequently needs to use more complex formulae. The SPSS complex samples module has been used to calculate sampling errors for the 2006 PLS Lebanon MICS. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. This method is documented in the SPSS file CSDescriptives.pdf found under the Help, Algorithms options in SPSS.
Sampling errors have been calculated for a select set of statistics (all of which are proportions due to the limitations of the Taylor linearization method) for the total sample, and for each of the 5 governorate. For each statistic, the estimate, its standard error, the coefficient of variation (or relative error -- the ratio between the standard error and the estimate), the design effect, and the square root design effect (DEFT -- the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used), as well as the 95 percent confidence intervals (+/-2 standard errors).
Details of the sampling errors are presented in the sampling errors appendix to the report and in the sampling errors table presented in te external resources.
Sampling errors can be evaluated statistically. The sample of respondents to the 2006 PLS Lebanon MICS is only one of many possible samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differe somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability in the results of the survey between all possible samples, and, although, the degree of variability is not known exactly, it can be estimated from the survey results. The sampling erros are measured in terms of the standard error for a particular statistic (mean or percentage), which is the square root of the variance. Confidence intervals are calculated for each statistic within which the true value for the population can be assumed to fall. Plus or minus two standard errors of the statistic is used for key statistics presented in MICS, equivalent to a 95 percent confidence interval.
If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formulae for calculating sampling errors. However, the 2006 PLS Lebanon MICS sample is the result of a multi-stage stratified design, and consequently needs to use more complex formulae. The SPSS complex samples module has been used to calculate sampling errors for the 2006 PLS Lebanon MICS. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. This method is documented in the SPSS file CSDescriptives.pdf found under the Help, Algorithms options in SPSS.
Sampling errors have been calculated for a select set of statistics (all of which are proportions due to the limitations of the Taylor linearization method) for the total sample, and for each of the 5 governorate. For each statistic, the estimate, its standard error, the coefficient of variation (or relative error -- the ratio between the standard error and the estimate), the design effect, and the square root design effect (DEFT -- the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used), as well as the 95 percent confidence intervals (+/-2 standard errors).
Details of the sampling errors are presented in the sampling errors appendix to the report and in the sampling errors table presented in te external resources.
Data Appraisal
A series of data quality tables and graphs are available to review the quality of the data and include the following:
Age distribution of the household population
Age distribution of eligible women and interviewed women
Age distribution of eligible children and children for whom the mother or caretaker was interviewed
Age distribution of children under age 5 by 3 month groups
Age and period ratios at boundaries of eligibility
Percent of observations with missing information on selected variables
Presence of mother inthe household and person interviewed for the under 5 questionnaire
School attendance by single year age
Sex ratio at birth among children ever born, surviving and dead by age of respondent
Distribution of women by time since last birth
Scatterplot of weight by height, weight by age and height by age
Graph of male and female population by single years of age
Population pyramid
The results of each of these data quality tables is shown in the appendix of the final report and is also given in the external resources section.
The general rule for presentation of missing data in the final report tabulations is that a column is presented for missing data if the percentage of cases with missing data is 1% or more. Cases with missing data on the background characteristics (e.g. education) are included in the tables, but the missing data rows are suppressed and noted at the bottom of the tables in the report (not in the SPSS output, however).
Age distribution of the household population
Age distribution of eligible women and interviewed women
Age distribution of eligible children and children for whom the mother or caretaker was interviewed
Age distribution of children under age 5 by 3 month groups
Age and period ratios at boundaries of eligibility
Percent of observations with missing information on selected variables
Presence of mother inthe household and person interviewed for the under 5 questionnaire
School attendance by single year age
Sex ratio at birth among children ever born, surviving and dead by age of respondent
Distribution of women by time since last birth
Scatterplot of weight by height, weight by age and height by age
Graph of male and female population by single years of age
Population pyramid
The results of each of these data quality tables is shown in the appendix of the final report and is also given in the external resources section.
The general rule for presentation of missing data in the final report tabulations is that a column is presented for missing data if the percentage of cases with missing data is 1% or more. Cases with missing data on the background characteristics (e.g. education) are included in the tables, but the missing data rows are suppressed and noted at the bottom of the tables in the report (not in the SPSS output, however).
Access policy
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| The Palestinian Central Bureau of Statistics and Natural Resources | PCBS | www.pcbs.gov.ps | |
| Hancioglu, Attila | ahancioglu@unicef.org | www.childinfo.org |
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| The Palestinian Central Bureau of Statistics and Natural Resources | www.pcbs.gov.ps | ||
| Khaddoura, Nasser | UNICEF | nkaddoura@unicef.org | |
| Hancioglu, Attila | UNICEF | ahancioglu@unicef.org | www.childinfo.org |
Confidentiality
Users of the data agree to keep confidential all data contained in these datasets and to make no attempt to identify, trace or contact any individual whose data is included in these datasets.
Access conditions
Survey datasets are distributed at no cost for legitimate academic research, with the condition that we receive an abstract or a detailed description of any research project that will be using the data prior to authorizing their distribution. Once received, the datasets must not be passed on to other researchers without the written consent of UNICEF and The Palestinian Central Bureau of Statistics and Natural Resources.Copies of all reports and publications based on the requested data must be sent to UNICEF and The Palestinian Central Bureau of Statistics and Natural Resources.
Copies of all reports and publications based on the requested data must be sent to:
UNICEF Lebanon, Nasser Khaddoura, Email: nkaddoura@unicef.org,
Address: UNICEF Lebanon, Yamout Street, Hamra, Ras Beirut, Lebanon (P.O.Box 5902)
Requests for access to the datasets may be made through the website www.childinfo.org.
Copies of all reports and publications based on the requested data must be sent to:
UNICEF Lebanon, Nasser Khaddoura, Email: nkaddoura@unicef.org,
Address: UNICEF Lebanon, Yamout Street, Hamra, Ras Beirut, Lebanon (P.O.Box 5902)
Requests for access to the datasets may be made through the website www.childinfo.org.
Citation requirements
PCBS, The Palestinian Central Bureau of Statistics and Natural Resources, Palestinian Refugee Camps, Lebanon, Multiple Indicator Cluster Survey: Household, household listing, women, children's files, 2006 [Computer file]. Palestinian Refugee Camps, Lebanon: PCBS, The Palestinian Central Bureau of Statistics and Natural Resources, [producer], 2007. Palestinian Refugee Camps, Lebanon: PCBS, The Palestinian Central Bureau of Statistics and Natural Resources and New York: Strategic Information Section, Division of Policy and Planning, UNICEF [distributors], 2007.
Disclaimer and copyrights
Disclaimer
The Palestinian Central Bureau of Statistics and Natural Resources and UNICEF provides these data to external users without any warranty or responsibility implied. The Palestinian Central Bureau of Statistics and Natural Resources and UNICEF accept no responsibility for the results and/or implications of any actions resulting from the use of these data.
Copyright
2007, PCBS, The Palestinian Central Bureau of Statistics and Natural Resources
Metadata production
DDI Document ID
DDI_LBN_2006_MICSPAL_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Croft, Trevor | TNC | Blancroft Research International | Producer of generic template |
| PAPFAM | Pan Arab Project for Family Health | Customization of generic template | |
| Bjelic, Ivana | Data archiving consultant |
Date of Metadata Production
2008-11-27
DDI Document version
PLS Lebanon MICS 2006 v0.1