Presentation on theme: "Multiple Indicator Cluster Surveys Data Interpretation, Further Analysis and Dissemination Workshop Tables on Sample and Survey Characteristics, Data Quality."— Presentation transcript:
Multiple Indicator Cluster Surveys Data Interpretation, Further Analysis and Dissemination Workshop Tables on Sample and Survey Characteristics, Data Quality and Sampling Error
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 2
Table HH.1: Results of household, women's, men's and under-5 interviews Number 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 UrbanRural Region 1Region 2Region 3Region 4Region 5Total 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 3 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.
Table HH.2: Household age distribution by sex Percent 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 NumberPercent NumberPercent NumberPercent Total Missing/DK Dependency age groups Missing/DK Child and adult populations Children age 0-17 years Adults age 18+ years Missing/DK 4 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.
Table HH.3: Household composition Percent and frequency distribution of households by selected characteristics, Country, Year Weighted percent Number of households WeightedUnweighted 5 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 characteristics Percent and frequency distribution of women / men / children under 5 by selected background characteristics, Country, Year Weighted percent Number WeightedUnweighted
Table HH.6: Housing characteristics Percent distribution of households by selected housing characteristics, according to area of residence and regions, Country, Year Total Area Region UrbanRural Region 1Region 2Region 3Region 4Region 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 or more Missing/DK Total100.0 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 assets Percentage 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 quintiles Percent distribution of the household population by wealth index quintiles, according to area of residence and regions, Country, Year Wealth index quintiles Total Number of household members PoorestSecondMiddleFourthRichest Total100.0 Area Urban100.0 Rural100.0 Region Region Region Region Region Region 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 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.
Data Quality Tables 9 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 population Single-year age distribution of household population by sex, Country, Year MalesFemales MalesFemales NumberPercent NumberPercent NumberPercent NumberPercent Age 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.
Distribution of household members by single age 11
12 Table DQ.2: Age distribution of eligible and interviewed women DQ.2: Age distribution of eligible and interviewed women Household population of women age years, interviewed women age years, and percentage of eligible women who were interviewed, by five-year age groups, Country, Year Household population of women age yearsInterviewed women age years Percentage of eligible women interviewed (Completion rate) Number Percent Age 10-14na na Total (15-49)100.0 Ratio of to na na: 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.
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 13
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 14
15 DQ.5: Birth date reporting: Household population Percent 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 birthYear of birth onlyMonth of birth onlyBoth missing Total100.0 Age DK/Missingna Region Region Region Region Region Region Area Urban100.0 Rural na: not applicable
Completeness of reporting (DQ11) 16 DQ.11: Completeness of reporting Percentage of observations that are missing information for selected questions and indicators, Country, Year Questionnaire and type of missing informationReference group Percent with missing/incomplete information a Number of cases Household Salt test resultAll households interviewed that have salt Starting time of interviewAll households interviewed Ending time of interviewAll households interviewed Women Date of first marriage/unionAll ever married women age Only month Both month and year Age at first marriage/union All ever married women age with year of first marriage not known Age at first intercourseAll women age who have ever had sex Time since last intercourseAll women age who have ever had sex Starting time of interviewAll women interviewed Ending time of interviewAll women interviewed Men Date of first marriage/unionAll ever married men age Only month Both month and year Age at first marriage/unionAll ever married men age with year of first marriage not known Age at first intercourseAll men age who have ever had sex Time since last intercourseAll men age who have ever had sex Starting time of interviewAll men interviewed Ending time of interviewAll men interviewed Under-5 Starting time of interviewAll under-5 children Ending time of interviewAll 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.
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 17
18 Completeness of anthropometric data (DQ12) - Underweight DQ.12: Completeness of information for anthropometric indicators: Underweight Percent 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 measure d Incomplete date of birth Weight not measured and incomplete date of birth Flagged cases (outliers) Total100.0 Age <6 months months months months months months 100.0
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. 19
Heaping in anthropometric data (DQ15) 20 DQ.15: Heaping in anthropometric measurements Distribution of weight and height/length measurements by digits reported for the decimal points, Country, Year WeightHeight or length NumberPercent NumberPercent Total100.0 Digits 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.
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 21
22 DQ.17: Observation of vaccination cards Percent 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 cardChild has vaccination card DK/Missin gTotal 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) Total100.0 Region Region Region Region Region Region Area Urban100.0 Rural100.0 Child's age 0-5 months months months months 100.0
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 23 DQ.20: Presence of mother in the household and the person interviewed for the under-5 questionnaire Distribution 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 householdMother 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
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
DQ.21: Selection of children age 1-17 years for the child labour and child discipline modules Percent 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 Total Number of households Percentage of households where correct selection was performed Number of households with 2 or more children age years NoneOne Two or more Total100.0 Region Region Region Region Region Region Area Urban100.0 Rural100.0 Wealth index quintiles Poorest100.0 Second100.0 Middle100.0 Fourth100.0 Richest 100.0
DQ.22: School attendance by single age 26 Not attending school Currently attending DK/Mis singTotal Number of househol d members Presc hool Primary school Grade Secondary school Grade Higher than seconda ry Age at beginning of school year 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.
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 27
DQ.23: Sex ratio at birth among children ever born and living 28 Children Ever BornChildren LivingChildren Deceased Number of women SonsDaugthers Sex ratio at birth SonsDaugthers Sex ratio SonsDaugthers Sex ratio Total Age
DQ.24: Births by calendar years 29 Number 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 birthsPercent with complete birth date b Sex ratio at birth c Calendar year ratio d LivingDeceasedTotal LivingDeceasedTotal LivingDeceasedTotal LivingDeceasedTotal na Year of birth 2013 a na 2012na na na <1994na DK/miss ing na na: not applicable a Interviews were conducted from [Month] to [Month], 2013 b Both month and year of birth given c (Bm/Bf) x 100, where Bm and Bf are the numbers of male and female births, respectively d (2 x B t /(B t -1 + B t +1)) x 100, where B t 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 days Distribution 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) 0–45–910–1415–19 Age at death ( days ) DQ.26: Reporting of age at death in months Distribution 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) 0–45–910–1415–19 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.
Maternal mortality related (DQ27 and DQ28) DQ.27: Completeness of information on siblings DQ.28: Sibship size and sex ratio of siblings 31
Sampling error tables 32
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 33
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 34
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 35
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 36
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 37
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 count Unweighted count Confidence limits Lower bound r - 2se Upper bound r + 2se Household members Use of improved drinking water sources Use of improved sanitation Primary school net attendance ratio (adjusted) Women Infant mortality rate Under five mortality rate Adolescent birth rate Contraceptive prevalence rate Unmet need Antenatal care coverage (1+ times, skilled provider) 5.5a Antenatal care coverage (4+ times, any provider)5.5b Skilled attendant at delivery Maternal mortality ratio Literacy rate (young women) Knowledge about HIV prevention (young women) Condom use with non-regular partners Men Literacy rate (young men) Knowledge about HIV prevention (young men) Condom use with non-regular partners Under-5s Underweight prevalence (moderate and severe)2.1a Underweight prevalence (severe)2.1b Children under age 5 who slept under an ITN Anti-malarial treatment of children under age 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.
Comprehensive knowledge about HIV prevention among young people 39