Guyana - Multiple Indicator Cluster Survey 2014

Similar documents
Turkmenistan - Multiple Indicator Cluster Survey

Barbados - Multiple Indicator Cluster Survey 2012

Malawi - MDG Endline Survey

Montenegro - Multiple Indicator Cluster Survey Roma Settlements

Egypt, Arab Rep. - Multiple Indicator Cluster Survey

Sierra Leone - Multiple Indicator Cluster Survey 2017

Lao PDR - Multiple Indicator Cluster Survey 2006

São Tomé and Príncipe - Multiple Indicator Cluster Survey 2014

Nigeria - Multiple Indicator Cluster Survey

Jamaica - Multiple Indicator Cluster Survey 2011

Moldova - Multiple Indicator Cluster Survey 2012

Namibia - Demographic and Health Survey

Zambia - Demographic and Health Survey 2007

Albania - Demographic and Health Survey

Indonesia - Demographic and Health Survey 2007

Botswana - Botswana AIDS Impact Survey III 2008

Tanzania - Demographic and Health Survey 2010

Liberia - Demographic and Health Survey 2007

Ghana - Ghana Living Standards Survey

Nepal - Demographic and Health Survey 2011

Tajikistan - Living Standards Survey 2007

Thailand - The Population and Housing Census of Thailand IPUMS Subset

Liberia - Household Income and Expenditure Survey 2016

Pakistan - Demographic and Health Survey

SAMOA - Samoa National Population and Housing Census 2006

Tonga - National Population and Housing Census 2011

AF Measure Analysis Issues I

Section 2: Preparing the Sample Overview

Thailand - The Population and Housing Census of Thailand IPUMS Subset

PMA2020 Household and Female Survey Sampling Strategy in Nigeria

SAMPLE DESIGN A.1 OBJECTIVES OF THE SAMPLE DESIGN A.2 SAMPLE FRAME A.3 STRATIFICATION

SAMPLE IMPLEMENTATION

Vietnam - Household Living Standards Survey 2004

Sample size, sample weights in household surveys

SURVEY ON USE OF INFORMATION AND COMMUNICATION TECHNOLOGY (ICT)

INTEGRATED COVERAGE MEASUREMENT SAMPLE DESIGN FOR CENSUS 2000 DRESS REHEARSAL

Chapter 4: Sampling Design 1

6 Sampling. 6.2 Target Population and Sample Frame. See ECB (2011, p. 7). Monetary Policy & the Economy Q3/12 addendum 61

India - WSP Global Scaling Up Rural Sanitation Access (TSSM) Impact Evaluation, Madhya Pradesh State, Baseline and Endline Surveys

Benefits of Sample long Form to Enlarge the scope of Census Data Analysis: The Experience Of Bangladesh

Ghana - Financial Inclusion Insights Survey 2014

6 Sampling. 6.2 Target population and sampling frame. See ECB (2013a), p. 80f. MONETARY POLICY & THE ECONOMY Q2/16 ADDENDUM 65

Experiences with the Use of Addressed Based Sampling in In-Person National Household Surveys

Saint Lucia Country Presentation

NATIONAL SOCIO- ECONOMIC SURVEY (SUSENAS) 2001 MANUAL HEAD OF PROVINCIAL, REGENCY/ MUNICIPALITY AND CORE SUPERVISOR/ EDITOR

Year Census, Supas, Susenas CPS and DHS pre-2000 DHS Retro DHS 2007 Retro

PUBLIC EXPENDITURE TRACKING SURVEYS. Sampling. Dr Khangelani Zuma, PhD

Session V: Sampling. Juan Muñoz Module 1: Multi-Topic Household Surveys March 7, 2012

Chapter 1: Economic and Social Indicators Comparison of BRICS Countries Chapter 2: General Chapter 3: Population

ONLINE APPENDIX: SUPPLEMENTARY ANALYSES AND ADDITIONAL ESTIMATES FOR. by Martha J. Bailey, Olga Malkova, and Zoë M. McLaren.

Statistics for Development in Pacific Island Countries: State-of-the-art, Challenges and Opportunities

Vincent Thomas Mule, Jr., U.S. Census Bureau, Washington, DC

A Country paper on Population and Housing census of Nepal and Consideration for Electronic data capture

Vanuatu - Vanuatu National Population and Housing Census 2009

Investing in evidence-based health programme planning in northern Nigeria: The Nahuche HDSS pilot census

Key Words: age-order, last birthday, full roster, full enumeration, rostering, online survey, within-household selection. 1.

APPENDIX A UNDERSTANDING SOCIETY: THE UK HOUSEHOLD LONGITUDINAL STUDY (UKHLS)

Botswana - Population and Housing Census 2001

ILO-IPEC Interactive Sampling Tools No. 5. Listing the sample Primary Sampling Units (PSUs)

SECOND LAO CENSUS OF AGRICULTURE

Mozambique - Rural Water Supply

; ECONOMIC AND SOCIAL COUNCIL

Presented by Doris Ma Fat on behalf of the. Department of Health Statistics and Information Systems World Health Organization, Geneva

Sample Registration System in India. State Institute of Health & Family Welfare, Jaipur

Overview of the Course Population Size

Vanuatu - Demographic Health Survey 2013

THE 2009 VIETNAM POPULATION AND HOUSING CENSUS

Vanuatu - Household Income and Expenditure Survey 2010

Comparing Generalized Variance Functions to Direct Variance Estimation for the National Crime Victimization Survey

Sierra Leone 2015 Population and Housing Census POST ENUMERATION SURVEY RESULTS AND METHODOLOGY

Gender Situation at The Republic of Tajikistan. Serbia 27 November - 1 December of 2017

AmericasBarometer, 2016/17

Understanding and Using the U.S. Census Bureau s American Community Survey

Sampling Subpopulations in Multi-Stage Surveys

Measuring Multiple-Race Births in the United States

LOGO GENERAL STATISTICS OFFICE OF VIETNAM

Methodology for selection of survey sites by PPS sampling 1

Economic and Social Council

Methodology Marquette Law School Poll February 25-March 1, 2018

Albania - Living Standards Measurement Survey 2002 (Wave 1 Panel)

FINANCIAL LITERACY SURVEY IN BOSNIA AND HERZEGOVINA 2011

NATIONAL SOCIO-ECONOMIC SURVEY 2001

SURVEY ON POLICE INTEGRITY IN THE WESTERN BALKANS (ALBANIA, BOSNIA AND HERZEGOVINA, MACEDONIA, MONTENEGRO, SERBIA AND KOSOVO) Research methodology

IUSSP XXV International Population Conference Tours, France July, 2005

Other Effective Sampling Methods

Demographic and Social Statistics in the United Nations Demographic Yearbook*

National approaches to the dissemination of demographic statistics and their implication for the Demographic Yearbook

1981 CENSUS COVERAGE OF THE NATIVE POPULATION IN MANITOBA AND SASKATCHEWAN

COUNTRY REPORT MONGOLIA

An Introduction to ACS Statistical Methods and Lessons Learned

Estimation Methodology and General Results for the Census 2000 A.C.E. Revision II Richard Griffin U.S. Census Bureau, Washington, DC 20233

K.R.N.SHONIWA Director of the Production Division Zimbabwe National Statistics Agency

population and housing censuses in Viet Nam: experiences of 1999 census and main ideas for the next census Paper prepared for the 22 nd

The Population Estimation Survey (PESS)

SAMPLING. A collection of items from a population which are taken to be representative of the population.

Poverty in the United Way Service Area

Workshop on the Improvement of Civil Registration and Vital Statistics in SADC Region Blantyre, Malawi 1 5 December 2008

Proceedings of the Annual Meeting of the American Statistical Association, August 5-9, 2001

American Community Survey 5-Year Estimates

American Community Survey 5-Year Estimates

Transcription:

Microdata Library Guyana - Multiple Indicator Cluster Survey 2014 United Nations Children s Fund, Guyana Bureau of Statistics, Guyana Ministry of Public Health Report generated on: December 1, 2016 Visit our data catalog at: http://microdata.worldbank.org/index.php 1

2

Sampling Sampling Procedure The primary objective of the sample design for the Guyana MICS 2014was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, and for the two geographic sub-areas defined as interior areas and coastal areas. Urban and rural areas in each of the two domains were defined as the sampling strata. A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The sample size for the Guyana MICS 5 2014 was established as 6,000 households. For the calculation of the sample size, the key indicator used was the underweight prevalence among children age 0-4 years which produced a sample size of 8,623. But the budget allocated for the survey only allowed for sample 6,000 households. The number of households selected per cluster for the Guyana MICS 5 2014 was determined as 20 households, based on a number of considerations, including the design effect, the budget available, and the time that would be needed per team to complete one cluster. Dividing the total number of households by the number of sample households per cluster, it was calculated that 300 sample clusters would be needed to be allocated to the two domains across the 10 geographic regions of the country. The allocation was not proportional to the size of the domain. The Interior Domain represents 12.52 percent of the population and if proportional allocation had been used, only 30 clusters would have been allocated to the interior domain instead of the 80. Within each domain the specified number of sample clusters was allocated to the regions approximately in proportion to their size. The 2012 census frame was used for the selection of clusters. Census enumeration areas (or Enumeration Districts in Guyana) were defined as primary sampling units (PSUs), and were selected from each of the sampling strata by using systematic pps (probability proportional to size) sampling procedures, based on the number of households in each enumeration area from the 2012 Population and Housing Census frame. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the two domains, separately for the urban and rural strata. Even though the sample frame (i.e. the 2012 Population and Housing Census) was relatively up-to-date, the maps and household listings of the selected clusters/eds were updated prior to selecting the households. A household listing to identify households with children under 5 was done in the field prior to interviewing. This was done to ensure that a certain number of households in the sample would have children and a certain number would not. Therefore, within each PSU the households in the listing were stratified in two groups: (1) households with children under 5 and (2) households without children in that age group. The mapping and listing exercise was carried out on the coast, from 27th January to 30th March, 2014, prior to the commencement of the field work (prelisted), while this exercise was conducted in the interior areas from 16th April to 6th July 2014 during the actual field work activities. Unlike on the coast where generally the listing was done and the sample was drawn in office, in the case of the interior, the listing was carried out by the data collection teams and the sample households were drawn in the field, prior to conducting interviews. The listing and mapping exercise utilized 17 teams consisting of two persons in each team: one listed and the other mapped the cluster. All the teams were supervised by checkers. The main responsibilities of the checkers were to identify the boundaries of each of the assigned clusters and verify 10 percent of households in each assigned cluster. Lists of households for each ED were prepared by the listing teams on the coast and by the data collection teams in the interior areas, identifying the households with and without children under 5 years. The households were then sequentially numbered from 1 to n (the total number of households in the group for each enumeration area), separately for the households with and without children under 5. A total of 20 sample households in each enumeration area allocated to the groups of households with and without children as described below, and within each group the allocated number of households was selected using random systematic selection procedures. Note that selection of the households for the coastal EDs was done in office by the Guyana Bureau of Statistics, while for the interior EDs, this was done in the field by the respective data collection supervisor. The survey also included a questionnaire for individual men that was to be administered in one-half of the sample of households, with every other household in each sample cluster selected for interviews with all eligible men. The households listed in each sample cluster were divided into two strata for the second stage selection: Households with children under 5 and households without children under 5.From the household listing sheets 12 households with children under 5 were selected and 8 without children in that age group. If for instance a PSU had only 5 households with children 3

under 5, these were all selected and the other 15 sample households came from the other stratum (without children under 5).A separate sample of households was selected from each group, using a higher sampling rate for households with children under 5. This sampling strategy increased the number of children under 5 in the sample in order to increase the precision of the indicators based on under-5 children. The sampling procedures are more fully described in "Multiple Indicator Cluster Survey 2014 - Final Report" pp.339-341. Response Rate Of the 5,904 households selected for the sample, 5,526 were found to be occupied. Of these, 5,077 were successfully interviewed for a household response rate of 91.9 percent. In the interviewed households, 5,809 women (age 15-49 years) were interviewed. Of these, 5,076 were successfully interviewed, yielding a response rate of 87.4 percent within the interviewed households. The survey also sampled men (age 15-49 years), but required only a subsample. All men (age 15-49 years) were identified in every other household. Two thousand five hundred and twenty-six (2,526) men (age 15-49 years) were listed in the household questionnaires. Questionnaires were completed for 1,682 eligible men, corresponding to a response rate of 66.6 percent within eligible interviewed households. There were 3,482 children under age five listed in the household questionnaires. Questionnaires were completed for 3,358 of these children, which corresponds to a response rate of 96.4 percent within the households that were interviewed. Overall response rates of 80.3 percent, 61.2 percent, and 88.6 percent are calculated for the individual interviews of women, men, and under-five s, respectively. Weighting The Guyana MICS 5 2014 sample is not self-weighting. Essentially, by allocating a disproportionate number of households to each of the domains, different sampling fractions were used in each domain since the sizes of the regions varied. At the second stage different sampling rates were also used for the households with and without children under 5. For these reasons, 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 stratum and PSU. A final component in the calculation of sample weights takes into account the level of non-response for the households and individual interviews. The adjustment for household non-response in each stratum is equal to: 1/ RRh The non-response adjustment factors for the individual women, men, and under-5 questionnaires were applied to the adjusted household weights. Numbers of eligible women, men, and under-5 children were obtained from the roster of household members in the Household Questionnaire for households where interviews were completed. The design weights for the households were calculated by multiplying the inverse of the probabilities of selection by the non-response adjustment factor for each stratum. These weights were then standardized (or normalized) in order to make the weighted sum of the interviewed sample units equal to the total sample size at the national level. Normalization is achieved by dividing the full sample weights (adjusted for nonresponse) by the average of these weights across all households at the national level. This is performed by multiplying the sample weights by a constant factor equal to the unweighted number of households at the national level divided by the weighted total number of households (using the full sample weights adjusted for nonresponse). A similar standardization procedure was followed in obtaining standardized weights for the individual women, men, and under-5 questionnaires. Adjusted (normalized) weights varied between 0.039742092 and 4.89493688 in the 296 sample enumeration areas (clusters). Four PSUs in the Interior domain could not be visited because they were inaccessible during the interview period. Sample weights were appended to all data sets and analyses were performed by weighting households, women, men, or under-5s with these sample weights. Since interviews with eligible men were conducted in one-half of the selected households, the raw sample weight for men includes a factor of 2, in addition to the nonresponse adjustment factor. The last stage probability of selection in each sample EA is different for households with and without children under 5. For this reason separate weights were calculated for each group of households in the sample EA. 4

5

Questionnaires Overview The questionnaires for the Generic MICS were structured questionnaires based on the MICS5 model questionnaire with some modifications and additions. Household questionnaires were administered in each household, which collected various information on household members including sex, age and relationship. The household questionnaire includes List of Household Members, Education, Child Labour, Child Discipline, Household Characteristics, Insecticide Treated Nets, Water and Sanitation, Handwashing, and Salt Iodization. In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49, men age 15-49 and children under age five. The questionnaire was administered to the mother or primary caretaker of the child. The women's questionnaire includes Woman's Background, Access to Mass Media and Use of Information, Communication Technology, Fertility/Birth History, Desire for Last Birth, Maternal and Newborn Health, Post-natal Health Checks, Illness Symptoms, Contraception, Unmet Need, Attitudes Toward Domestic Violence, Marriage/Union, Sexual Behaviour, Prevention, HIV/AIDS, Tobacco and Alcohol Use, Chronic Illness Control, and Life Satisfaction. The men's questionnaire includes Man's Background, Access to Mass Media and Use of Information, Communication Technology, Fertility, Attitudes Toward Domestic Violence, Marriage/Union, Sexual Behaviour, HIV/AIDS, Tobacco and Alcohol Use, Chronic Illness Control, and Life Satisfaction. The children's questionnaire includes Child's age, Birth Registration, Early Childhood Development, Breastfeeding and Dietary Intake, Immunization, Care of Illness, and Anthropometry. The questionnaires are based on the MICS5 model questionnaire. From the MICS5 model English version, the questionnaires were customised and were pre-tested in three (3) locations in both urban and rural areas including a community in the interior areas during February 2014. Based on the results of the pre-test, modifications were made to the wording of the questionnaires. 6

Data Collection Data Collection Dates Start End Cycle 2014-04 2014-07 N/A Data Collection Mode Face-to-face [f2f] DATA COLLECTION NOTES Training for the fieldwork was conducted for 15 days (three work-weeks) between the 25th of February and 18th of March 2014. The training methodologies included lectures on interviewing techniques utilising each of the questionnaires and role-play modelling the various functions interchangeably. As part of the selection process, participants were observed during the role-plays and scored. Quizzes were also administered to participants. Once the questionnaires were finalised and the teams were selected, the survey implementation was piloted. During this process, trainees spent a day in the field in six (6) locations in both urban and rural areas, to ensure that the processes of the fieldwork would work as close as possible to how it was envisioned during the training. Both the pilot and training were conducted in the coastal regions and therefore the interior areas were visited at the time of the listing and enumeration. In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for handwashing, and measured the weights and heights of children age under five years. Details and findings of these observations and measurements are provided in the respective sections of the report. The data were collected by 14 teams; each was comprised of four (4) interviewers, one (1) editor, one (1) measurer, one (1) supervisor and one (1) driver. Fieldwork began in April 2014 and concluded in July 2014. SUPERVISION There is one supervisor for each of the 14 data collection teams in the field. 7

Data Processing Data Editing The data were entered using the CSPro software, Version 5.0. The data were entered on nine (9) desktop computers and carried out by nine (9) data entry operators and one (1) data entry supervisor. For quality assurance purposes, all questionnaires were double-entered and internal consistency checks were conducted. The procedures and standard programs developed by the global MICS programme, informed the adaption of Guyana MICS5 2014 questionnaires, and guided the process throughout. Data processing began just after the second week of data collection in April 2014 and was completed in mid-december 2014. Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 21. The model syntax and tabulation plans developed by UNICEF were customised and used for this purpose. 8

Data Appraisal Estimates of Sampling Error Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data. The following sampling error measures are presented in this appendix for each of the selected indicators: - Standard error (se): Standard error is the square root of the variance of the estimate. For survey indicators that are means, proportions or ratios, the Taylor series linearization method is used for the estimation of standard errors. For more complex statistics, such as fertility and mortality rates, the Jackknife repeated replication method is used for standard error estimation. - Coefficient of variation (se/r) is the ratio of the standard error to the value (r) of the indicator, and is a measure of the relative sampling error. - Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling based on the same sample size. The square root of the design effect (deft) is used to show the efficiency of the sample design in relation to the precision. A deft value of 1.0 indicates that the sample design of the survey is as efficient as a simple random sample for a particular indicator, while a deft value above 1.0 indicates an increase in the standard error due to the use of a more complex sample design. - Confidence limits are calculated to show the interval within which the true value for the population can be reasonably assumed to fall, with a specified level of confidence. For any given statistic calculated from the survey, the value of that statistic will fall within a range of plus or minus two times the standard error (r + 2.se or r 2.se) of the statistic in 95 percent of all possible samples of identical size and design. For the calculation of sampling errors from MICS data, programs developed in CSPro Version 5.0, SPSS Version 21 Complex Samples module and CMRJack have been used. The results are shown in the tables that follow. In addition to the sampling error measures described above, the tables also include weighted and unweighted counts of denominators for each indicator. Given the use of normalized weights, by comparing the weighted and unweighted counts it is possible to determine whether a particular domain has been under-sampled or oversampled compared to the average sampling rate. If the weighted count is smaller than the unweighted count, this means that the particular domain had been oversampled. Sampling errors are calculated for indicators of primary interest, for the national level, for urban and rural areas, for the geographic sub-areas defined as interior and coastal areas, as well as urban coastal and rural coastal areas, and for all regions. Three of the selected indicators are based on household members, 12 are based on women, 3 are based on men, and 4 are based on children under 5. 9

Other forms of Data Appraisal A series of data quality tables are available to review the quality of the data and include the following: - Age distribution of household population - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Age distribution of children in household and under-5 questionnaires - Birth date reporting: Household population - Birth date and age reporting: Women - Birth date and age reporting: Men - Birth date and age reporting: Under-5s - Birth date reporting: Children, adolescents and young people - Birth date reporting: First and last births - Completeness of reporting - Completeness of information for anthropometric indicators: Underweight - Completeness of information for anthropometric indicators: Stunting - Completeness of information for anthropometric indicators: Wasting - Heaping in anthropometric measurements - Observation of birth certificates - Observation of vaccination cards - Observation of women's health cards - Observation of bednets and places for handwashing - Presence of mother in the household and the person interviewed for the under-5 questionnaire - Selection of children age 1-17 years for the child labour and child discipline modules - School attendance by single age - Sex ratio at birth among children ever born and living - Births by periods preceding the survey - Reporting of age at death in days - Reporting of age at death in months The results of each of these data quality tables are shown in appendix E in document "Multiple Indicator Cluster Survey 2014 - Final Report" pp.363-382. 10

11

Related Materials Questionnaires Guyana Multiple Indicator Cluster Survey 2014 - Questionnaire Title Date 2014-12-01 Country Language Table of contents Filename Reports Guyana Multiple Indicator Cluster Survey 2014 - Questionnaire Guyana English Household questionnaire modules Household member questionnaire modules Women questionnaire modules Children questionnaire modules Vaccination records at health facility questionnaire modules Guyana 2014 MICS_English_Questionnaire.pdf Guyana Multiple Indicator Cluster Survey 2014 - Report Title Guyana Multiple Indicator Cluster Survey 2014 - Report Author(s) Guyana Bureau of Statistics United Nations Children's Fund (UNICEF) Date 2014-12-01 Country Guyana Language English Filename https://mics-surveys-prod.s3.amazonaws.com/mics5/latin%20america%20and%20caribbean/guyana/2014/final/guyana%202014%20mics_english.pdf Guyana Multiple Indicator Cluster Survey 2014 - Key Findings Title Guyana Multiple Indicator Cluster Survey 2014 - Key Findings Author(s) Guyana Bureau of Statistics United Nations Children's Fund (UNICEF) Date 2014-07-01 Country Guyana Language English Filename https://mics-surveys-prod.s3.amazonaws.com/mics5/latin%20america%20and%20caribbean/guyana/2014/key%20findings/guyana%202014%20mics%20kfr_english.pdf 12