Multiple Indicator Cluster Survey 2005
Jamaica, 2005 - 2006
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Reference ID
JAM_2005_MICS_v01_M
Producer(s)
Statistical Institute Of Jamaica
Collection(s)
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Mar 21, 2011
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Sep 26, 2013
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Identification
Survey ID Number
JAM_2005_MICS_v01_M
Title
Multiple Indicator Cluster Survey 2005
Country/Economy
| Name | Country code |
|---|---|
| Jamaica | JAM |
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). However, this is the second round for Jamaica, the first was done in 2000. 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.
Survey Objectives
The 2005 Jamaica Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Jamaica.
- To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals, 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 Jamaica 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 survey was carried out by STATIN 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 Objectives
The 2005 Jamaica Multiple Indicator Cluster Survey has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Jamaica.
- To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals, 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 Jamaica 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 survey was carried out by STATIN 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.
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 members 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 members 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
2007-12-12
Scope
Notes
The Jamaica Multiple Indicator Cluster Survey included the following modules in the questionnaires:
HOUSEHOLD QUESTIONNAIRE : Household information panel, household listing, orphaned and vulnerable children, education, child labour, water and sanitation, salt iodization, child discipline and child disability.
WOMEN'S QUESTIONNAIRE: Women's characteristics, child mortality, tetanus toxoid, maternal and newborn health, marriage and HIV/AIDS knowledge and domestic violence.
CHILDREN'S QUESTIONNAIRE: Children's characteristics, birth registration and early learning, breastfeeding, care of illness plus source and cost of oral rehydration salts (ORS) and antibiotics, immunization and child development.
HOUSEHOLD QUESTIONNAIRE : Household information panel, household listing, orphaned and vulnerable children, education, child labour, water and sanitation, salt iodization, child discipline and child disability.
WOMEN'S QUESTIONNAIRE: Women's characteristics, child mortality, tetanus toxoid, maternal and newborn health, marriage and HIV/AIDS knowledge and domestic violence.
CHILDREN'S QUESTIONNAIRE: Children's characteristics, birth registration and early learning, breastfeeding, care of illness plus source and cost of oral rehydration salts (ORS) and antibiotics, immunization and child development.
Topics
| Topic | Vocabulary |
|---|---|
| Household members | MICS Topics |
| Education | MICS Topics |
| Water and sanitation | 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 |
| Marriage and union | MICS Topics |
| HIV/AIDS | MICS Topics |
| Children's background | MICS Topics |
| Birth registration | MICS Topics |
| Early learning | MICS Topics |
| Breastfeeding | MICS Topics |
| Care of illness | MICS Topics |
| Immunization | MICS Topics |
| Support to children orphaned and made vulnerable by HIV/AIDS | MICS Topics |
| Child discipline | MICS Topics |
| Source and cost of ORS and antibiotics | MICS Topics |
| Attitudes towards domestic violence | MICS Topics |
| Child development | MICS Topics |
| Disability | MICS Topics |
Coverage
Geographic Coverage
The survey is nationally representative and covers the whole of Jamaica.
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 |
|---|---|
| Statistical Institute Of Jamaica | Office of the Prime Minister |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Statistical Institute Of Jamaica | Office of the Prime Minister | Technical implementation and supervision |
| UNICEF, Jamaica Office | UNICEF | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| UNICEF | UNICEF | Funding of survey implementation |
| UNESCO | UNESCO | Funding of survey implementation |
| UNDP | UNDP | Funding of survey implementation |
| UNAIDS | UNAIDS | Funding of survey implementation |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| CABINET OFFICE | CABINET OFFICE | Steering Committee |
| ECC | Early Childhood Commission | Steering Committee |
| PIOJ | Planning Institute of Jamaica | Steering Committee |
| SALISES | University of the West Indies | Steering Committee |
| UNFPA | UNFPA | Steering Committee |
| PAHO | PAHO | Steering Committee |
| CDA | CDA | Steering Committee |
| MOH | Ministry of Health | Steering Committee and training |
| STATIN | Statistical Institute of Jamaica | Data collection and survey management |
| OECD | Organization for Economic Cooperation and Development | Financial and Technical Support in Data Archiving |
Sampling
Sampling Procedure
The sample for the Jamaica Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, as well as urban and rural areas. Parishes were identified as the main sampling domains and were divided into sampling regions of equal sizes. The sample was selected in two stages. Within each sampling region, two census enumeration areas/Primary Sampling Units (PSUs) were selected with probability proportional to size. Using the household listing from the selected PSUs a systematic sample of 6,276 dwellings was drawn.
The sampling procedures are more fully described in the the sampling appendix (appendix A) of the final report.
The sampling procedures are more fully described in the the sampling appendix (appendix A) of the final report.
Deviations from the Sample Design
Five of the selected enumeration areas were not visited because they were inaccessible due to flooding during the fieldwork period. Sample weights were used in the calculation of national level results.
Response Rate
In the 6,276 dwellings selected for the sample, 5,604 households were found to be occupied (Table HH.1). Of these, 4,767 were successfully interviewed for a household response rate of 85.1 percent. The reason for this lower response rate is given in the previous section. In the interviewed households, 3,777 women (age 15-49) were identified. Of these, 3,647 were successfully interviewed, yielding a response rate of 96.6 percent. In addition, 1,444 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 1,427 which correspond to a response rate of 98.8 percent.
Overall response rates of 82.1 and 84.1 percent were calculated for the women's and under-5's interviews respectively. Note that the response rates for the Kingston Metropolitan Area (KMA) were lower than in other urban areas and in the rural area. Two factors contributed to this - more dwellings were vacant, often as a result of urban violence, and in the upper income areas access to dwellings was more difficult. In the rural areas, the rains prevented access to some households as some roads were inundated.
Overall response rates of 82.1 and 84.1 percent were calculated for the women's and under-5's interviews respectively. Note that the response rates for the Kingston Metropolitan Area (KMA) were lower than in other urban areas and in the rural area. Two factors contributed to this - more dwellings were vacant, often as a result of urban violence, and in the upper income areas access to dwellings was more difficult. In the rural areas, the rains prevented access to some households as some roads were inundated.
Weighting
The Jamaica Multiple Indicator Cluster Survey sample is not self-weighted. Essentially, by allocating equal numbers of households to each of the regions, different sampling fractions were used in each region since the size of the regions varied. For this reason, sample weights were calculated and these were used in the subsequent analyses of the survey data.
The major component of the weight is the reciprocal of the sampling fraction employed in selecting the number of sample households in that particular sampling domain:
Since the estimated numbers of households per enumeration area prior to the first stage selection (selection of primary sampling units) and the updated number of households per enumeration area were different, individual sampling fractions for households in each enumeration area (cluster) were calculated. The sampling fractions for households in each enumeration area (cluster) therefore included the probability of selection of the enumeration area in that particular sampling domain and the probability of selection of a household in the sample enumeration area (cluster).
Sample weights were appended to all data sets and analyses were performed by weighting each household, woman or under-5 with these sample weights.
The major component of the weight is the reciprocal of the sampling fraction employed in selecting the number of sample households in that particular sampling domain:
Since the estimated numbers of households per enumeration area prior to the first stage selection (selection of primary sampling units) and the updated number of households per enumeration area were different, individual sampling fractions for households in each enumeration area (cluster) were calculated. The sampling fractions for households in each enumeration area (cluster) therefore included the probability of selection of the enumeration area in that particular sampling domain and the probability of selection of a household in the sample enumeration area (cluster).
Sample weights were appended to all data sets and analyses were performed by weighting each household, woman or under-5 with these sample weights.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2005-10-10 | 2006-11-30 |
Data Collection Mode
Face-to-face [f2f]
Supervision
Interviewing was conducted by teams of interviewers. Each interviewing team comprised of 3-4 female interviewers, a field editor and a supervisor, and a driver. Each teams used a 4 wheel dirve vehicle to travel from cluster to cluster (and where necessary within cluster).
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
The pretest for the survey took place in August 2005 and included 4 interviewers and one supervisor.
Data collection took place over a period of about 6 weeks from October, 10 2006 until late November of the same year.
Interviews averaged 35 minutes for the household questionnaire (excluding salt testing), 23 minutes for the women's questionnaire, and 27 for the under five children's questionnaire.
Three staff members of Statistical Institute of Jamaica provided overall fieldwork coordination and supervision. The overall field coordinator was Isbeth Bernard.
Data collection took place over a period of about 6 weeks from October, 10 2006 until late November of the same year.
Interviews averaged 35 minutes for the household questionnaire (excluding salt testing), 23 minutes for the women's questionnaire, and 27 for the under five children's questionnaire.
Three staff members of Statistical Institute of Jamaica provided overall fieldwork coordination and supervision. The overall field coordinator was Isbeth Bernard.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Statistical Institute of Jamaica | STATIN | Office of the Prime Minister |
Questionnaires
Questionnaires
The questionnaires for the Jamaica MICS were structured questionnaires based on the MICS3 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 support to orphaned and vulnerable children, education, child labour, water and sanitation, and salt iodization, with optional modules for child discipline, child disability and security of tenure and durability of housing. In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or caretaker of the child. The women's questionnaire include women's characteristics, child mortality, tetanus toxoid, maternal and newborn health, marriage, contraception, and HIV/AIDS knowledge, with optional modules for unmet need, domestic violence, and sexual behavior. The children's questionnaire includes children's characteristics, birth registration and early learning, vitamin A, breastfeeding, care of illness, malaria, immunization, and an optional module for child development. All questionnaires and modules are provided as external resources.
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
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
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 2005-2006 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 2005-2006 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 2005-2006 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 2005-2006 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 national sample, urban and rural areas, and for each of the five regions. 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 2005-2006 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 2005-2006 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 2005-2006 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 national sample, urban and rural areas, and for each of the five regions. 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
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| STATIN | STATIN | info@statinja.com | www.statinja.com |
| UNICEF Jamaica Country Office | UNICEF | unicefja@cwjamaica.com | www.unicef.org/jamaica |
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 research, with the condition that we receive and approve 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 STATIN (info@statinja.com) and UNICEF(unicefja@cwjamaica.com).
Requests for access to the datasets may be made through the website www.childinfo.org.
Requests for access to the datasets may be made through the website www.childinfo.org.
Citation requirements
Statistical Institute Of Jamaica . Multiple Indicator Cluster Survey: Household , household listing, women and children's files, 2006 [Computer file]. Kingston, Jamaica: Statistical Institute Of Jamaica [producer], 2006. Kingston, Jamaica: Statistical Institute Of Jamaica and New York: Strategic Information Section, Division of Policy and Planning, UNICEF [distributors], 2005.
Disclaimer and copyrights
Disclaimer
The Statistical Institute of Jamaica and UNICEF provides these data to external users without any warranty or responsibility implied. The Statistical Institute of Jamaica and UNICEF accepts no responsibility for the results and/or implications of any actions resulting from the use of these data.
Copyright
(c) 2007, STATIN
Metadata production
DDI Document ID
DDI_JAM_2005_MICS_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Gaynor, Avery | STATIN | Statistical Institute of Jamaica, Office of the Prime Minister | Producer of Jamaica MICS3 Archive |
| Forbes, Douglas | STATIN | Statistical Institute of Jamaica, Office of the Prime Minister | Producer of Jamaica MICS3 Archive |
| James, Rhiannon | UNICEF | UNICEF | Adaption of Jamaica MICS3 archive for childinfo.org |
Date of Metadata Production
2008-12-23
DDI Document version
JAMAICA MICS 2005 UNICEF v0.2
Slightly edited version of UNICEF's DDI ref. DDI-JAM-UNICEF-MICS32005/v0.1
Slightly edited version of UNICEF's DDI ref. DDI-JAM-UNICEF-MICS32005/v0.1