Multiple Indicator Cluster Surveys Data Interpretation, Further Analysis and
Dissemination Workshop
Tables on Sample and Survey Characteristics, Data Quality and
Sampling Error
2
Sample and Survey Characteristics
Response rates and background characteristics:
• Set of 8 tables that:
• Presents sample coverage and characteristics of households and respondents
• Age and sex distribution of survey population
• Characteristics of respondents
• Household characteristics and wealth quintiles
3
Table HH.1: Results of household, women's, men's and under-5 interviewsNumber of households, women, men, and children under 5 by results of the household, women's, men's and under-5's interviews, and household, women's, men's and under-5's response rates, Country, Year
Residence Region Urban Rural Region 1 Region 2 Region 3 Region 4 Region 5 Total
Households Sampled Occupied Interviewed Household response rate
Women Eligible Interviewed Women's response rate Women's overall response rate
Men Eligible Interviewed Men's response rate Men's overall response rate
Children under 5 Eligible Mothers/caretakers interviewed Under-5's response rate Under-5's overall response rate
Overall response rates are calculated for women, men and under-5's by multiplying the household response rate by the women's, men's and under-5's response rates, respectively.
4
Table HH.2: Household age distribution by sexPercent and frequency distribution of the household population by five-year age groups, dependency age groups, and by child (age 0-17 years) and adult populations (age 18 or more), by sex, Country, Year
Males Females Total
Number Percent Number Percent Number PercentTotal 100.0 100.0 100.0
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Missing/DK
Dependency age groups
0-14 15-64 65+ Missing/DK
Child and adult populations Children age 0-17 years
Adults age 18+ years Missing/DK
Missing information on sex is normally not expected; in the event that few household members have missing sex in the final data set, this should be indicated in the final report in a footnote to the table, and such cases should be excluded from the table.
5
Table HH.3: Household compositionPercent and frequency distribution of households by selected characteristics, Country, Year
Weighted percentNumber of households
Weighted Unweighted
Total weighted and unweighted numbers of households should be equal when normalized sample weights are used.
Tables HH.3, HH.4, HH.4M and HH.5 present main background characteristics of the household, women's, men's and under-5 samples, and should be produced and finalized before the rest of tables are produced, to ensure that the categories adopted for presentation in the tables will include sufficiently sized denominators.
Religion/Language/Ethnicity of household head should be constructed from information collected in the Household Questionnaire, in questions HC1A, HC1B, and HC1C. In most surveys, some combination of these three questions will be used as the final variable that best describes the main socio-cultural or ethnic groups in the country.
Table HH.4 /HH.4M/HH5: Women's/Men's/Under-5's background characteristicsPercent and frequency distribution of women / men / children under 5 by selected background characteristics, Country, Year
Weighted percentNumber
Weighted Unweighted
Table HH.6: Housing characteristicsPercent distribution of households by selected housing characteristics, according to area of residence and regions, Country, Year
TotalArea Region
Urban Rural Region 1 Region 2 Region 3 Region 4 Region 5
Electricity Yes No Missing/DK
Flooring Natural floor Rudimentary floor Finished floor Other Missing/DK
Roof Natural roofing Rudimentary roofing Finished roofing Other Missing/DK
Exterior walls Natural walls Rudimentary walls Finished walls Other Missing/DK
Rooms used for sleeping 1 2 3 or more Missing/DK
Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households Mean number of persons per room used for sleeping
Information on housing characteristics are obtained in the Household Characteristics module of the Household Questionnaire: Electricity (HC8A), flooring (HC3), roof (HC4), exterior walls (HC5) and rooms used for sleeping (HC2).
To limit the size of the table, detailed floor, roof, and exterior wall categories are not shown. If needed, these categories may be indicated in a footnote below the table, in the final report.
Additional relevant housing characteristics may be added to the table if included in the household questionnaire.
Most of the information collected on these housing characteristics are used in the construction of the wealth index.
Table HH.7: Household and personal assetsPercentage of households by ownership of selected household and personal assets, and percent distribution by ownership of dwelling, according to area of residence and regions, Country, Year
Information on household and personal assets are obtained in the Household Characteristics module of the Household Questionnaire: Radio (HC8B), television (HC8C), Non-mobile telephone (HC8D), refrigerator (HC8E), agricultural land (HC11), farm animals/livestock (HC13), watch (HC9A), mobile telephone (HC9B).bicycle (HC9C), motorcycle or scooter (HC9D), animal-drawn cart (HC9E), car or truck (HC9F), and boat with a motor (HC9G). Ownership of dwelling is based on responses to HC10.
Additional household and personal assets should to be added to the questionnaires (for wealth index construction) and shown in this table.
Missing/DK values are included in the denominators and households with missing information are considered not to own or have these assets. However, a careful examination of the extent of missing values needs to be undertaken prior to the construction of this table. If Missing/DK cases exceed 5 percent, this should be shown in the table.
Most of the information collected on household and personal assets are used in the construction of the wealth index.
Table HH.8: Wealth quintilesPercent distribution of the household population by wealth index quintiles, according to area of residence and regions, Country, Year
Wealth index quintiles
TotalNumber of household
membersPoorest Second Middle Fourth Richest
Total 100.0
Area Urban 100.0 Rural 100.0
Region Region 1 100.0 Region 2 100.0 Region 3 100.0 Region 4 100.0 Region 5 100.0
Wealth index quintiles are constructed by using data on housing characteristics, household and personal assets, and on water and sanitation via principal components analysis.
Household members should be equally distributed to the five wealth index quintiles for the total sample, in the first row of the table (percentages that deviate from the equal distribution of 20 percent per quintile by 0.1 - 0.2 percent are permissible).
Other background characteristics (such as Religion/Language/Ethnicity, education and sex of household head) may be added to the table, if needed.
9
Data Quality Tables
Before producing tabulations and writing the report narrative, 28 tables are produced for assessment of data quality
Intended to check distributions, heaping, understatement or overstatement, sex ratios, eligibility and coverage, out-transference of eligible persons, the extent of missing information, outliers, sex ratios, quality of anthropometric measurements
Useful for understanding quality issues, familiarity with issues in data sets, indicative of the quality of training and implementation
10
DQ.1: Age distribution of household populationSingle-year age distribution of household population by sex, Country, Year
Males Females
Males Females
Number Percent Number Percent Number Percent Number Percent Age Age
0 45 1 46 2 47 3 48 4 49 5 50 6 51 7 52 8 53 9 54 10 55 11 56 12 57 13 58 If age reporting is good, the distribution should be smooth.
The table should also provide insights into overreporting or underreporting at certain age groups or intervals, and the extent of missing information on age.
Deficits at ages 4, 15, and 49, excesses at ages 5 and 6, 14, and 50 might be indicative of out-transference of ages to avoid administering individual questionnaires.
11
Distribution of household members by single age
12
Table DQ.2: Age distribution of eligible and interviewed women
DQ.2: Age distribution of eligible and interviewed womenHousehold population of women age 10-54 years, interviewed women age 15-49 years, and percentage of eligible women who were interviewed, by five-year age groups, Country, Year
Household population of women age 10-54 years Interviewed women age 15-49 years
Percentage of eligible women
interviewed (Completion rate)Number Number Percent
Age
10-14 na na na15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 na na na
Total (15-49) 100.0 Ratio of 50-54 to 45-49 na na nana: not applicable
The purpose of these tables is to detect both displacement of respondents out of the eligible age range and differential response rates by age.
13
Completion rates - women, men & under-5s (DQ2, DQ3, DQ4)
Fieldwork performance – re-visits, good planning
Completion rates need to be high, but also uniform by age and background characteristics
Low completion rates for certain age groups are likely to bias results
14
Birth date and age reporting (DQ5, DQ6, DQ7, DQ8, DQ9, DQ10)
Surveys always have cases with missing information
The extent of missing information is important, because it can result in biased results if such proportions are high
Particularly informative about the quality of survey is the extent of missing information on measurements, ages, and dates of events
15
DQ.5: Birth date reporting: Household population
DQ.5: Birth date reporting: Household populationPercent distribution of household population by completeness of date of birth information, Country, Year
Completeness of reporting of month and year of birth
Total
Number of household members
Year and month of birth Year of birth only Month of birth only Both missing
Total 100.0 Age
0-4 100.0 5-14 100.0 15-24 100.0 25-49 100.0 50-64 100.0 65-84 100.0 85+ 100.0 DK/Missing na na 100.0
Region Region 1 100.0 Region 2 100.0 Region 3 100.0 Region 4 100.0 Region 5 100.0
Area Urban 100.0 Rural 100.0
na: not applicable
16
Completeness of reporting (DQ11)DQ.11: Completeness of reportingPercentage of observations that are missing information for selected questions and indicators, Country, Year
Questionnaire and type of missing information Reference group
Percent with missing/incomplete
informationaNumber of
cases Household
Salt test result All households interviewed that have salt Starting time of interview All households interviewed Ending time of interview All households interviewed
Women
Date of first marriage/union All ever married women age 15-49 Only month Both month and year
Age at first marriage/union All ever married women age 15-49 with year of first marriage not known
Age at first intercourse All women age 15-24 who have ever had sex Time since last intercourse All women age 15-24 who have ever had sex Starting time of interview All women interviewed Ending time of interview All women interviewed
Men
Date of first marriage/union All ever married men age 15-49 Only month Both month and year
Age at first marriage/union All ever married men age 15-49 with year of first marriage not known
Age at first intercourse All men age 15-24 who have ever had sex Time since last intercourse All men age 15-24 who have ever had sex Starting time of interview All men interviewed Ending time of interview All men interviewed
Under-5
Starting time of interview All under-5 children Ending time of interview All under-5 children
a Includes "Don't know" responses
The purpose is to examine the amount of missing information for certain key indicators.
High levels of missing data may indicate that the non-missing data are biased or of poor quality.
17
Completeness of anthropometric data (DQ12, DQ13, DQ14)
Many tools have been developed for assessing data quality of anthropometric indicators
Completeness of anthropometric data influenced by Birth date reporting Children not weighed, measured Bad quality measurements
Expected completeness should be above 90 percent, preferably 95
18
Completeness of anthropometric data (DQ12) - Underweight
DQ.12: Completeness of information for anthropometric indicators: UnderweightPercent distribution of children under 5 by completeness of information on date of birth and weight, Country, Year
Valid weight and
date of birth
Reason for exclusion from analysis
Total
Percent of children excluded
from analysis
Number of children under 5
Weight not
measured
Incomplete date of birth
Weight not measured and
incomplete date of birth
Flagged cases
(outliers) Total 100.0 Age
<6 months 100.0 6-11 months 100.0 12-23 months 100.0 24-35 months 100.0 36-47 months 100.0 48-59 months 100.0
19
Heaping in anthropometric data (DQ15)
Under normal circumstances, approximately 10 percent of anthropometric measurements should be reported for each of the digits for the decimals.
Significant excesses over 10 percent are indicative of heaping, and therefore quality problems in anthropometric measurements, either due to truncation or rounding.
Typically, more heaping is expected in height/length than weight measurements.
20
Heaping in anthropometric data (DQ15)
DQ.15: Heaping in anthropometric measurementsDistribution of weight and height/length measurements by digits reported for the decimal points, Country, Year
Weight Height or length
Number Percent Number Percent Total 100.0 100.0 Digits
0 1 2 3 4 5 6 7 8 9
0 or 5
The table includes all children with weight and height/length measurements, regardless of the completeness of date of birth information, and flagged cases, which may not be included in the anthropometric analysis.
21
Observation of documents (DQ16-DQ18) and observation of bednets and places for handwashing
(DQ19)
Interviewers are required to ask and see the specific documents and copy relevant information on the questionnaire
This is important for the completion of the several modules in women and under-5 questionnaire, and may also be useful for obtaining accurate information on children's dates of birth and ages
22
DQ.17: Observation of vaccination cardsPercent distribution of children age 0-35 months by presence of a vaccination card, and the percentage of vaccination cards seen by the interviewers, Country, Year
Child does not have vaccination card Child has vaccination card
DK/Missing Total
Percentage of vaccination cards
seen by the interviewer
(1)/(1+2)*100
Number of children age 0-35 months
Had vaccination card previously
Never had vaccination
card Seen by the interviewer
(1)
Not seen by the
interviewer (2)
Total 100.0
Region
Region 1 100.0
Region 2 100.0
Region 3 100.0
Region 4 100.0
Region 5 100.0
Area
Urban 100.0
Rural 100.0
Child's age
0-5 months 100.0
6-11 months 100.0
12-23 months 100.0
24-35 months 100.0
23
DQ20: Respondent to under-5 questionnaire
Presence of mother in the household and the person interviewed for the under-5 questionnaire:
The under-5 questionnaire should be administered to the mother, if the mother is listed the household roster
DQ.20: Presence of mother in the household and the person interviewed for the under-5 questionnaireDistribution of children under five by whether the mother lives in the same household, and the person who was interviewed for the under-5 questionnaire, Country, Year
Mother in the household Mother not in the household
Total
Number of children under 5
Mother interviewed
Father interviewed
Other adult
female interview
ed
Other adult male interviewe
d Father
interviewed
Other adult female
interviewed
Other adult male
interviewed
24
DQ21: Correct selection for child labour and child discipline modules
Selection of children age 1-17 years for the child labour and child discipline modules
In households where 2 or more children age 1-17 years live, interviewers are required to select, according to pre-determined random selection procedures, one child for the child discipline module
Percentages with correct selection should be close to 100.0
DQ.21: Selection of children age 1-17 years for the child labour and child discipline modulesPercent distribution of households by the number of children age 1-17 years, and the percentage of households with at least two children age 1-17 years where where correct selection of one child for the child labour and child discipline modules was performed, Country, Year
Number of children age 1-17 years
TotalNumber of households
Percentage of households where
correct selection was performed
Number of households with 2 or more children age 1-17 yearsNone One
Two or more
Total 100.0
Region
Region 1 100.0
Region 2 100.0
Region 3 100.0
Region 4 100.0
Region 5 100.0
Area
Urban 100.0
Rural 100.0
Wealth index quintiles
Poorest 100.0
Second 100.0
Middle 100.0
Fourth 100.0
Richest 100.0
26
DQ.22: School attendance by single age
Not attending
school
Currently attending
DK/Missing Total
Number of
household
membersPreschool
Primary schoolGrade
Secondary schoolGrade
Higher than
secondary1 2 3 4 5 6 1 2 3 4 5 6
Age at beginning of school year
5 100.0 6 100.0 7 100.0 8 100.0 9 100.0 10 100.0 11 100.0 12 100.0
Age at the beginning of the school year is calculated from dates of birth of household members or by rejuvenating household members based on the date of the survey and current age. Levels and grades refer to the current school year, or the most recent school year if data collection was completed between school years.
Many cases outside the diagonal would be indicative of both poor fieldwork supervision, as well as poor data entry and (lack of) verification.
27
Child mortality related (DQ23-DQ26)
DQ.23: Sex ratio at birth among children ever born and living
DQ.24: Births by calendar years DQ.25: Reporting of age at death in days DQ.26: Reporting of age at death in months
28
DQ.23: Sex ratio at birth among children ever born and living
Children Ever Born Children Living Children DeceasedNumber
of womenSons Daugthers
Sex ratio at
birth Sons DaugthersSex
ratio Sons DaugthersSex
ratio Total Age
15-19 20-24 25-29 30-34 35-39 40-44 45-49
29
DQ.24: Births by calendar yearsNumber of births, percentage with complete birth date, sex ratio at birth, and calendar year ratio by calendar year, according to living, deceased, and total children (weighted, unimputed), as reported in the birth histories, Country, Year
Number of births Percent with complete birth dateb Sex ratio at birthc Calendar year ratiod
Living Deceased Total Living Deceased Total Living Deceased Total Living Deceased Total
Total na na na Year of birth
2013a na na na2012 na na na2011 2010 2009 1999-2003 na na na
1994-1998 na na na
<1994 na na naDK/missing na na na
na: not applicable a Interviews were conducted from [Month] to [Month], 2013b Both month and year of birth givenc (Bm/Bf) x 100, where Bm and Bf are the numbers of male and female births, respectivelyd (2 x Bt/(Bt-1 + Bt+1)) x 100, where Bt is the number of births in calendar year t
The purpose is to examine the impact of omission of births in the five years preceding the survey.
If large amounts of omission are suspected, then careful interpretation of current fertility and mortality levels and trends is needed.
Graphic presentation of these data can provide good visual appreciation of omission and transference.
DQ.25: Reporting of age at death in daysDistribution of reported deaths under one month of age by age at death in days and the percentage of neonatal deaths reported to occur at ages 0–6 days, by 5-year periods preceding the survey (weighted, imputed), Country, Year
Number of years preceding the survey Total(0–19)0–4 5–9 10–14 15–19
Age at death (days)
DQ.26: Reporting of age at death in monthsDistribution of reported deaths under two years of age by age at death in months and the percentage of infant deaths reported to occur at age under one month, for the 5-year periods of birth preceding the survey (weighted, imputed), Country, Year
Number of years preceding the survey Total(0-19)0–4 5–9 10–14 15–19
Age at death (months)
The purposes of tables DQ25 and DQ26 are to examine the possible omission of neonatal and early neonatal deaths; and the effects of age at death heaping.
31
Maternal mortality related (DQ27 and DQ28)
DQ.27: Completeness of information on siblings
DQ.28: Sibship size and sex ratio of siblings
32
Sampling error tables
33
Sampling Error Tables: Background
The sample selected in a survey is one of the many samples that could have been selected (with same design and size)
Sampling errors are measures of the variability between all possible samples, which can be estimated from survey results
34
Sampling Error Tables: Background
Calculation of sampling errors is very important
Provides information on the reliability of your results
Tells you the ranges within which your estimates most probably fall
Provides clues as to the sample sizes (and designs) to be selected in forthcoming surveys
35
Sampling Error Tables: Background
MICS sample designs are complex designs, usually based on stratified, multi-stage, cluster samples
It is not possible to use straightforward formula for the calculation of sampling errors. Sophisticated approaches have to be used
36
Sampling Error Tables: Background
Versions 13 and above of SPSS are used for this purpose
SPSS uses Taylor linearization method of variance estimation for survey estimates that are means or proportions
This approach is used by most other package programs: Wesvar, Sudaan, Systat, EpiInfo, SAS
37
Sampling Error Tables: Background
In MICS, the objective is to calculate sampling errors for a selection of variables, for the national sample, as well as for each of the reported domains
Sampling error tabulation plan includes separate excel worksheets for: total sample, urban, rural, and 6 regions. SE tables can be produced for other domains such as ethnicity and wealth quintiles
38
MICS Indicator
MDG Indicator
Value (r)
Standard error (se)
Coefficient of variation
(se/r)Design
effect (deff)
Square root of design
effect (deft)Weighted
countUnweighte
d count
Confidence limits
Lower boundr - 2se
Upper boundr + 2se
Household members
Use of improved drinking water sources 4.1 7.8 0.000 0.000
Use of improved sanitation 4.3 7.9 0.000 0.000
Primary school net attendance ratio (adjusted) 7.4 2.1 0.000 0.000
Women
Infant mortality rate 1.2 4.2 0.000 0.000
Under five mortality rate 1.5 4.1 0.000 0.000
Adolescent birth rate 5.1 5.4 0.000 0.000
Contraceptive prevalence rate 5.3 5.3 0.000 0.000
Unmet need 5.4 5.6 0.000 0.000
Antenatal care coverage (1+ times, skilled provider) 5.5a 5.5 0.000 0.000
Antenatal care coverage (4+ times, any provider) 5.5b 5.5 0.000 0.000
Skilled attendant at delivery 5.7 5.2 0.000 0.000
Maternal mortality ratio 5.13 5.1 0.000 0.000
Literacy rate (young women) 7.1 2.3 0.000 0.000
Knowledge about HIV prevention (young women) 9.1 6.3 0.000 0.000
Condom use with non-regular partners 9.15 6.2 0.000 0.000
Men
Literacy rate (young men) 7.1 2.3 0.000 0.000
Knowledge about HIV prevention (young men) 9.1 6.3 0.000 0.000
Condom use with non-regular partners 9.15 6.2 0.000 0.000
Under-5s
Underweight prevalence (moderate and severe) 2.1a 1.8 0.000 0.000
Underweight prevalence (severe) 2.1b 1.8 0.000 0.000
Children under age 5 who slept under an ITN 3.18 6.7 0.000 0.000
Anti-malarial treatment of children under age 5 3.22 6.8 0.000 0.000
Note that mortality SEs can only be calculated for results based on birth history with the existing and separate SPSS syntax.
Also note that SEs for the maternal mortality ratio can be calculated only through the CS Pro application.
The indicators listed in SE tab plan represent the MDG indicators for which SEs can be calculated. SEs can easily be produced for most other MICS indicators and included if desired.
39
Comprehensive knowledge about HIVprevention among young people
40
Thank You