This dataset contains a selection of 27 indicators of public health significance by Chicago community area, with the most updated information available. The indicators are rates, percents, or other measures related to natality, mortality, infectious disease, lead poisoning, and economic status. See the full description at http://bit.ly/Nb3R7m.

Abstract

The objective of the endline surveys in 2016 were to gather household, biomedical, and cognition data in order to evaluate the long-term impact of home supplementation with micronutrient powders (MNP), when combined with seasonal malaria chemoprevention (SMC) and early stimulation, delivered through community preschools and parenting sessions, on the health and cognitive development of children during the first five years of life.

The trial consisted of 3 arms. First, 60 villages with established Early Childhood Development centres (ECD) were randomised to 1 of 2 arms:

1) Children living in villages in the ECD control arm received SMC as part of national health programming and a national parenting intervention delivered by ECD center staff trained and supported by Save the Children, with ALL resident children eligible to participate in the interventions irrespective of enrolment in ECD program (ECD Control group).

2) Children living in villages in the intervention arm also received the SMC and parenting interventions described above, but additionally were eligible to receive home supplementation with micronutrient powders (MNP intervention arm).

3) Second, a third non-randomised arm was recruited comprised of children living in 30 randomly selected villages where there were no ECD centers in place and thus both the parenting interventions and MNPs were absent. These children received SMC only, as part of national health programming (non-ECD comparison arm).

Trial arm and Interventions received:

T1. MNP intervention arm: 30 villages with ECD centre (randomised); MNP-Yes, Parenting-Yes, SMC-Yes C1. ECD control arm: 30 villages with ECD centre (randomised); MNP-No, Parenting-Yes, SMC-Yes C2. Non-ECD comparison arm: 30 villages without ECD centre (not randomised); MNP-No, Parenting-No, SMC-Yes

Three cross-sectional endline surveys took place during the period May-August 2016, three years after the original MNP intervention began, and consisted of the following questionnaires and assessments in two age groups of children, 3 year olds and 5 year olds:

i) A household questionnaire was used to collect data from the primary adult caregiver of the child on home environment, exposure to the interventions, and reported practice outcomes of relevance to the parenting intervention.

ii) Biomedical outcomes were measured in children through laboratory and clinical assessment.

iii) A battery of tests were used to assess cognitive performance and school readiness in childen, using a different age-specific test battery for each age group adapted for local language and culture.

Note: Household and cognitive performance data were gathered from participants in all three arms. Biomedical data were only collected from children in the two randomised arms, to evaluate impact of MNP supplementation on anaemia (primary biomedical outcome) in children who received MNPs and those who did not, using a robust study design.

Geographic coverage

Districts (cercles) of Sikasso and Yorosso, Region of Sikasso

Analysis unit

Individuals and communities

Universe

Random sample of target population for the intervention in the 90 communities that consented to participate in the trial, namely pre-school children 0-6 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The target population for the interventions comprised all children aged 3 months to 6 years, who were resident in the 90 study communities participating in the trial; the primary sampling unit is the individual child.

Sample Frame:

To identify the number of target beneficiaries, a complete census of all children of eligible age was carried out in the 90 study villages in August 2013. The census listing from 2013 thus defined the population of children who are eligible to have received the interventions every year for the three years between 2013-2016; and was used as the sampling frame of children in whom the impact after three years of implementation of the interventions was evaluated. The intention was to evaluate study outcomes in the same child one year after the start of the MNP intervention (May 2014) and again after three years of the intervention (2016).

A random sample of children was drawn from all children listed in the census for each community participating in the trial, according to the following age criteria:

Date of Birth, or Age in August 2013 (Age group in 2016 surveys) (i) Born between 1 Jan 2013 – 30 June 2013, or aged <1 year in 2013 census if DOB not known (3 years) (ii) Born between 1 May 2010 – 30 April 2011, or aged 2 years in census if DOB not known (5 years)

Thus, all children previously randomly selected and enrolled in the evaluation cohort in 2014 were, if still resident in the village and present on the day of the survey, re-surveyed in May 2016.

Sample Size:

Power analysis was undertaken for a comparison of two arms, taking account of clustering by community. Survey data on biomedical and cognitive outcomes collected in 2014 were used to inform sample size assumptions, including prevalence of primary outcomes, intraclass correlation (ICC) and number of children recruited per cluster. Prevalence of anaemia amongst 3-year old children in 2014 was found to be 61.6% and 64.0% in the intervention and control arms respectively (p=0.618) and 53.8% and 51.9% respectively amongst 5-year old children (p=0.582). The observed ICC for anaemia endpoint at baseline was 0.08 in 3-year old children and 0.06 in 5-year old children. Observed ICC for cognitive outcomes measured in 2014 was 0.09, ranging from 0.05 to 0.16 for individual tasks within the cognitive battery.

Sample Size Estimation for Health Outcomes:

Approximately 20-25 children per cluster were recruited into each age cohort in 2013. Power calculations for anaemia (primary endpoint) were undertaken for three alternative scenarios at endline: (i) to allow for the possibility of up to 20% loss to follow up between 2014 and 2016, power calculations were performed for a sample size at endline of 16 children per cluster; (ii) a smaller cluster size of 14 children sampled per village, under a scenario of 30% loss to follow-up; and (iii) unequal clusters, to allow for the possibility that variation in losses to follow-up between villages could result in an unequal number of children sampled in each village. In this case, cluster size is the mean number of children sampled per cluster.

Thus, assuming a conservative prevalence of anaemia of 50% in the control group and ICC of 0.08, a sample size of 30 communities per arm with 14-20 children sampled per community, will under all of these scenarios provide 80% power to detect a reduction in anemia of at least 28% at 5% level of significance.

Sample Size Estimation for Cognitive Outcomes:

Power calculations for cognitive outcomes explored: (i) a smaller cluster size of 14 children sampled per village, for example resulting from a higher than expected loss to follow-up of 30%; (ii) statistical analysis of differences between arms which does not adjust for baseline - a scenario which allows for the possibility to increase the sample size to compensate for losses to follow-up by increased recruitment of new children for whom no baseline data would be available; and (iii) effect of unequal clusters. Thus, for cognitive-linguistic skills, a sample size of 30 communities per arm with 14-20 children in each age cohort sampled per community will provide 80% power to detect an effect size between 0.27-0.29 at 5% level of significance, assuming an (ICC) of 0.10 and individual, household and community-level factors account for at least 25% of variation in cognitive foundation skills. Whilst for a similar sample size of 30 communities per arm with 14-20 children sampled per community and ICC of 0.10, a statistical analysis which does not adjust for baseline will provide 80% power to detect an effect size between 0.28-0.30 at 5% level of significance.

The sample at endline in May 2016 thus comprised a total of up to 600 children aged 3y and 600 children aged 5y at endline in each arm: T1 Intervention group (with ECD): 30 communities, with approx. 40 randomly selected children in each community (20 aged 3y; 20 aged 5y). C1 ECD control group (with ECD): 30 communities, with approx. 40 randomly selected children in each community (20 aged 3y; 20 aged 5y). C2 Comparison group (without ECD): 30 communities, with approx. 40 randomly selected children in each community (20 aged 3y; 20 aged 5y).

Strategy for Absent Respondents/Not Found/Refusals:

Every effort was made to trace children previously recruited into the evaluation cohort. Since some losses-to-follow-up (for example to due to child deaths, outward migration) were expected between 2014 and 2016, the primary strategy was to oversample in 2014. However, for villages where loss-to-follow-up was higher than expected and it was not possible to trace sufficient number of children remaining from the original sample to meet the required sample size per cluster, additional children were recruited into the evaluation survey in 2016. New recruits were selected at random from the children listed as resident in the village at the time of the original census in 2013. All new recruits had thus been resident in the village and exposed to the interventions throughout the three preceding years.

Mode of data collection

Face-to-face [f2f]

Research instrument

1. Household questionnaire (Form_Parent_MaliSIEF_2016_french.pdf ; Form_Parent_MaliSIEF_2016_english.pdf)

The questionnaires for the parent interview were structured questionnaires. A questionnaire was administered to the child’s primary caregiver

National immunisation coverage rates, 2015 to 2020. Human Papillomavirus (HPV) immunisation coverage rates, 2015 to 2017.

Key Table Information.Table Title.Population of Subcounty General-Purpose Governments by Population-Size Group: U.S. and State: 2012 - 2022.Table ID.GOVSTIMESERIES.CG00ORG07.Survey/Program.Public Sector.Year.2024.Dataset.PUB Public Sector Annual Surveys and Census of Governments.Source.U.S. Census Bureau, Public Sector.Release Date.2023-08-24.Release Schedule.For information about Census of Governments planned data product releases, see https://www.census.gov/programs-surveys/gus/newsroom/updates.html.Dataset Universe.Census of Governments - Organization (CG):The universe of this file is all federal, state, and local government units in the United States. In addition to the federal government and the 50 state governments, the Census Bureau recognizes five basic types of local governments. The government types are: County, Municipal, Township, Special District, and School District. Of these five types, three are categorized as General Purpose governments: County, municipal, and township governments are readily recognized and generally present no serious problem of classification. However, legislative provisions for school district and special district governments are diverse. These two types are categorized as Special Purpose governments. Numerous single-function and multiple-function districts, authorities, commissions, boards, and other entities, which have varying degrees of autonomy, exist in the United States. The basic pattern of these entities varies widely from state to state. Moreover, various classes of local governments within a particular state also differ in their characteristics. Refer to the Individual State Descriptions report for an overview of all government entities authorized by state.The Public Use File provides a listing of all independent government units, and dependent school districts active as of fiscal year ending June 30, 2024. The Annual Surveys of Public Employment & Payroll (EP) and State and Local Government Finances (LF):The target population consists of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Survey of Public Pensions (PP):The target population consists of state- and locally-administered defined benefit funds and systems of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Surveys of State Government Finance (SG) and State Government Tax Collections (TC):The target population consists of all 50 state governments. No local governments are included. For the purpose of Census Bureau statistics, the term "state government" refers not only to the executive, legislative, and judicial branches of a given state, but it also includes agencies, institutions, commissions, and public authorities that operate separately or somewhat autonomously from the central state government but where the state government maintains administrative or fiscal control over their activities as defined by the Census Bureau. Additional details are available in the survey methodology description.The Annual Survey of School System Finances (SS):The Annual Survey of School System Finances targets all public school systems providing elementary and/or secondary education in all 50 states and the District of Columbia..Methodology.Data Items and Other Identifying Records.Percent of population in areas with municipal governmentsPercent of population in areas with township governmentsPopulation-size group - Municipal Governments - Less than 1,000 - PopulationPopulation-size group - Municipal Governments - 1,000 to 2,499 - PopulationPopulation-size group - Municipal Governments - 2,500 to 4,999 - PopulationPopulation-size group - Municipal Governments - 5,000 to 9,999 - PopulationPopulation-size group - Municipal Governments - 10,000 to 24,999 - PopulationPopulation-size group - Municipal Governments - 25,000 to 49,999 - PopulationPopulation-size group - Municipal Governments - 50,000 to 99,999 - PopulationPopulation-size group - Municipal Governments - 100,000 to 199,999 - PopulationPopulation-size group - Municipal Governments - 200,000 to 299,999 - PopulationPopulation-size group - Municipal Governments - 300,000 or more - PopulationPopulation-size group - Township Governments - Less than 1,000 - PopulationPopulation-size group - Township Governments - 1,000 to 2,499 - PopulationPopulation-size group - ...

Indicator 3.b.1Proportion of the target population covered by all vaccines included in their national.Methodology:Percentage of Vaccination =number of children vaccinated /targeted children * 1000. Data Source:Ministry of Public Health .

The survey shows what Grammys' target audience was believed to be as of February 2016. during a survey, seven percent of U.S. respondents said that the Grammys were mostly geared at people in their own age group.

Series Name: Proportion of the target population with access to pneumococcal conjugate 3rd dose (PCV3) (percent)Series Code: SH_ACS_PCV3Release Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 3.b.1: Proportion of the target population covered by all vaccines included in their national programmeTarget 3.b: Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries, provide access to affordable essential medicines and vaccines, in accordance with the Doha Declaration on the TRIPS Agreement and Public Health, which affirms the right of developing countries to use to the full the provisions in the Agreement on Trade-Related Aspects of Intellectual Property Rights regarding flexibilities to protect public health, and, in particular, provide access to medicines for allGoal 3: Ensure healthy lives and promote well-being for all at all agesFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Weighting procedures for different target population data scenarios.

Series Name: Proportion of the target population with access to affordable medicines and vaccines on a sustainable basis human papillomavirus (HPV) (percent)Series Code: SH_ACS_HPVRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 3.b.1: Proportion of the target population covered by all vaccines included in their national programmeTarget 3.b: Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries, provide access to affordable essential medicines and vaccines, in accordance with the Doha Declaration on the TRIPS Agreement and Public Health, which affirms the right of developing countries to use to the full the provisions in the Agreement on Trade-Related Aspects of Intellectual Property Rights regarding flexibilities to protect public health, and, in particular, provide access to medicines for allGoal 3: Ensure healthy lives and promote well-being for all at all agesFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Abstract

The main objectives of the study were to assess the knowledge and beliefs of high-risk groups about STI and HIV, determine the prevalence of HIV infection and syphilis among these groups and obtain baseline data that will permit comparisons of risk behaviours, HIV infection and syphilis over time.

Geographic coverage

Six selected states

Analysis unit

State, group, individual

Universe

The Integrated Biological and Behavioural Surveillance Survey 2007 covered only males and females aged up to 15-49 years among seven sub-populations at risk of HIV in six selected states of Nigeria, namely Female Sex Workers (both brothel- and non-brothel-based), men who have sex with men (MSM), injecting drug users (IDU), members of the armed forces, police, and transport workers (TW).

Kind of data

Sample survey data [ssd]

Sampling procedure

In order to reach a representative sample of all groups involved in the 2007 IBBSS, a number of different sampling techniques were used depending on the group in question, including simple random sampling (SRS), cluster sampling (probability proportionate to size (PPS) for fixed populations), time-location sampling (TLS) and respondent-driven sampling (RDS). For MSM and IDU, the RDS method was used, while a TLS technique was used to select non-brothel-based FSW and TW. The brothel-based FSW, armed forces, and police were selected using a two-stage cluster sampling technique. The take all (TA) sampling method was used when the desired sample size was not attainable based on the results of target population mapping.

ITLS is a form of cluster sampling that contains both time and location dimensions. TLS provides the opportunity to reach members of a target population who access certain locations at any point in time. The process starts by creating time * location PSU (PSU that have both a time and a location dimensions) from which a random sample is selected. At the second stage all or a sub-sample of randomly selected population members who appear at the site during a designated time interval of fixed length, for example 4 hours, are interviewed. To the extent that all members of a target population access the locations at some point in time, TLS is a probability sampling method because: (i) all population members have a non-zero chance of selection as long as the TLS frame is complete; and (ii) the selection probabilities can be calculated by taking the time dimension as well as the space dimension into account.

RDS is a method that combines "snowball sampling" with a mathematical model that weights the sample to compensate for the fact that the sample was collected in a non-random way. Characterized by long referral chains (to ensure that all members of the target population can be reached) and a statistical theory of the sampling process which controls for bias including the effects of choice of seeds and differences in network size, RDS overcomes the shortcomings of institutional sampling (coverage) and snow-ball type methods (statistical validity). By making chain-referral into a probability sampling method and consequently resolving the dilemma of a choice between coverage and statistical validity, RDS has become the most appropriate method for reaching the hard-to-reach population groups. The RDS process starts with the recruitment of the initial seeds each of whom recruits a maximum of two to three members from their population group.

Sampling deviation

Cluster samples were chosen randomly based on sampling frames developed through the mapping process. This process was to identify places where potential subjects could be reached and sampled. Field work for the mapping exercise was performed over one week. Due to the limited period some hidden populations may not be adequately represented in sampling frames.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed in collaboration with FMOH, SFH, CDC, WHO, UNAIDS and other stakeholders. At both central- and state-level trainings, each question in the questionnaire was reviewed and role-played and possible challenges were identified and addressed. The questionnaire of Integrated Biological and Behavioural Surveillance Survey 2007 was grouped into fifteen sections

Section 0: Identification particularsBackground characteristics Section 1: Background characteristics Section 2: Marriage and partnerships Section 3: Sexual history numbers and types of partners Section 4: Sexual history-regular partners (for those with spouse/live-in sexual partners only; for MSM, female spouse/live-in sexual partners only) Section 5: Sexual history-boy friends/girl friends (for those with boy friends/girl friends sexual partners only; for MSM, female boy friends/girl friends sexual partners only) Section 6: Sexual history-purchasing sex (male only) (for those with commercial sex partners only; for MSM, female commercial sex partners only) Section 7: Sexual history-casual-non regular non-paying sexual partners (for those with casual sexual partners only; for MSM, female casual sexual partners only) Section 8: Selling sex (for female populatios only) Section 9: Social habits (all groups) Section 10: Dru use/needle sharing (all population reporting drug injection in the past 12 months) Section 11: MSM-men who have sex with men (ask all respondents) Section 12: STIs (ask all respondents) Section 13: Knowledge, opinions, and attitudes towards HIV/AIDS (ask all respondents) Section 12: Exposure to interventions

Cleaning operations

After data entry, the data was cleaned using STATA 10. Frequency counts were carried out to check consistency and assess cleaniness of the database. The data cleaning also included the following:

Searching for ages outside the age range criteria; Cross-checking all corresponding skips to the questionnaire; Reviewing the cluster allocations; Cross-checking the questionnaire completion responses from the interviewers in the database with the records in the supervisors log to ensure they matched; Tallying the supervisors log of blood samples collected to ensure that recorded numbers of samples collected matched the results recorded in the database; and Consistency checks involving cross-checking answers to related questions.

Response rate

There were 11,175 individuals selected for this study out of whom 0.8% and 8.1% refused to participate in behavioural and biological componenets of the study respectively.

Non-brothel based FSW had the highest refusal rate of 2.7% and 19.4% for behavioural and biological components respectively, followed by brothel-based FSW at 2.2% and 13.1% respectively. Refusal rates for the behavioural component were less than 0.5% for other groups.

For the biological component, refusal rates were 3% for police, 0.8% for the armed forces, 1 .2% for TW, 4.6% for MSM, and 3.3% for IDU.

Sampling error estimates

No sampling error estimate

Data appraisal

A template for the questionnaire was designed with pre-programmed consistency checks for cross-checking answers, including skips and eligibility criteria. Laboratory data forms were collected on a periodic basis from the central laboratories and brought to the same centralized location for data entry. At least 25% of the questionnaires entered daily by each data entry clerk had the behaviour and other non-biological data entered, while 100% double-data entry was achieved for the biological data for quality control purposes. The data entry clerks were supervised by three supervisors who reviewed and validated all questionnaires entered.

Social Welfare Attitudes and Immigrants as a Target Population: Experimental Evidence Jake Haselswerdt (University of Missouri) Replication files (all in Stata format) Main dataset: immigsocwef_main.dta Replication code for main analyses: immigsocwef_main_rep.do Log file for main analyses: immigsocwef_main_rep.log Google Trends dataset: immigsocwef_google.dta Replication code for Google Trends analysis: immigsocwef_google_rep.do Log file for Google Trends analysis: immigsocwef_google_rep.log Follow-up survey dataset: immigsocwef_followup.dta Replication code for follow-up survey analyses: immigsocwef_followup.do Log file for follow-up survey analyses: immigsocwef_followup.log

Key Table Information.Table Title.Percentage Distribution of Revenue of Public Elementary-Secondary School Systems in the United States: Fiscal Year 2012- 2023.Table ID.GOVSTIMESERIES.GS00SS14.Survey/Program.Public Sector.Year.2024.Dataset.PUB Public Sector Annual Surveys and Census of Governments.Source.U.S. Census Bureau, Public Sector.Release Date.2025-05-01.Release Schedule.The Annual Survey of School System Finances occurs every year. Data are typically released in early May. There are approximately two years between the reference period and data release..Dataset Universe.Census of Governments - Organization (CG):The universe of this file is all federal, state, and local government units in the United States. In addition to the federal government and the 50 state governments, the Census Bureau recognizes five basic types of local governments. The government types are: County, Municipal, Township, Special District, and School District. Of these five types, three are categorized as General Purpose governments: County, municipal, and township governments are readily recognized and generally present no serious problem of classification. However, legislative provisions for school district and special district governments are diverse. These two types are categorized as Special Purpose governments. Numerous single-function and multiple-function districts, authorities, commissions, boards, and other entities, which have varying degrees of autonomy, exist in the United States. The basic pattern of these entities varies widely from state to state. Moreover, various classes of local governments within a particular state also differ in their characteristics. Refer to the Individual State Descriptions report for an overview of all government entities authorized by state.The Public Use File provides a listing of all independent government units, and dependent school districts active as of fiscal year ending June 30, 2024. The Annual Surveys of Public Employment & Payroll (EP) and State and Local Government Finances (LF):The target population consists of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Survey of Public Pensions (PP):The target population consists of state- and locally-administered defined benefit funds and systems of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Surveys of State Government Finance (SG) and State Government Tax Collections (TC):The target population consists of all 50 state governments. No local governments are included. For the purpose of Census Bureau statistics, the term "state government" refers not only to the executive, legislative, and judicial branches of a given state, but it also includes agencies, institutions, commissions, and public authorities that operate separately or somewhat autonomously from the central state government but where the state government maintains administrative or fiscal control over their activities as defined by the Census Bureau. Additional details are available in the survey methodology description.The Annual Survey of School System Finances (SS):The Annual Survey of School System Finances targets all public school systems providing elementary and/or secondary education in all 50 states and the District of Columbia..Methodology.Data Items and Other Identifying Records.Fall enrollmentTotal percentage distribution of revenuePercentage distribution of revenue - Revenue from federal sources - TotalPercentage distribution of revenue - Revenue from federal sources - Title IPercentage distribution of revenue - Revenue from state sources - TotalPercentage distribution of revenue - Revenue from state sources - General formula assistancePercentage distribution of revenue - Revenue from local sources - TotalPercentage distribution of revenue - Revenue from local sources - Taxes and parent government contributionsPercentage distribution of revenue - Revenue from local sources - Other local governmentsPercentage distribution of revenue - Revenue from local sources - Current chargesDefinitions can be found by clicking on the column header in the table or by accessing the Glossary.For detailed information, see Government Finance and Employment Classification Manual..Unit(s) of Observation.The basic reporting unit is the governmental unit, defined as an org...

25% sample data.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Group quarters: A collective household is a group of persons that does not live in an ordinary household, but lives in a collective establishment, sharing meal times.

Universe

Residents in France, of any nationality. Does not include French citizens living in other countries, foreign tourists, or people passing through.

Kind of data

Census/enumeration data [cen]

Sampling procedure

SAMPLE DESIGN: Systematic manual sorting into lots with different sample units according to target population. Lots divide the population into different samples (1/20,1/5,3/4).

SAMPLE UNIT: Private dwellings and individuals for group quarters and compte a part

SAMPLE FRACTION: 5%

SAMPLE UNIVERSE: The microdata sample includes mainland France and Corsica.

SAMPLE SIZE (person records): 2,487,778

Mode of data collection

Face-to-face [f2f]

Research instrument

Separate forms for buildings, group quarters (collective households), group quarters (compte a part), private households, and boats. Four forms for individuals (living in group quarters and private dwellings; two different forms for people compte a part; living in boats).

Key Table Information.Table Title.Revenue for Public Elementary-Secondary School Systems by Revenue Source: U.S. and State: 2012 - 2023.Table ID.GOVSTIMESERIES.GS00SS02.Survey/Program.Public Sector.Year.2024.Dataset.PUB Public Sector Annual Surveys and Census of Governments.Source.U.S. Census Bureau, Public Sector.Release Date.2025-05-01.Release Schedule.The Annual Survey of School System Finances occurs every year. Data are typically released in early May. There are approximately two years between the reference period and data release..Dataset Universe.Census of Governments - Organization (CG):The universe of this file is all federal, state, and local government units in the United States. In addition to the federal government and the 50 state governments, the Census Bureau recognizes five basic types of local governments. The government types are: County, Municipal, Township, Special District, and School District. Of these five types, three are categorized as General Purpose governments: County, municipal, and township governments are readily recognized and generally present no serious problem of classification. However, legislative provisions for school district and special district governments are diverse. These two types are categorized as Special Purpose governments. Numerous single-function and multiple-function districts, authorities, commissions, boards, and other entities, which have varying degrees of autonomy, exist in the United States. The basic pattern of these entities varies widely from state to state. Moreover, various classes of local governments within a particular state also differ in their characteristics. Refer to the Individual State Descriptions report for an overview of all government entities authorized by state.The Public Use File provides a listing of all independent government units, and dependent school districts active as of fiscal year ending June 30, 2024. The Annual Surveys of Public Employment & Payroll (EP) and State and Local Government Finances (LF):The target population consists of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Survey of Public Pensions (PP):The target population consists of state- and locally-administered defined benefit funds and systems of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Surveys of State Government Finance (SG) and State Government Tax Collections (TC):The target population consists of all 50 state governments. No local governments are included. For the purpose of Census Bureau statistics, the term "state government" refers not only to the executive, legislative, and judicial branches of a given state, but it also includes agencies, institutions, commissions, and public authorities that operate separately or somewhat autonomously from the central state government but where the state government maintains administrative or fiscal control over their activities as defined by the Census Bureau. Additional details are available in the survey methodology description.The Annual Survey of School System Finances (SS):The Annual Survey of School System Finances targets all public school systems providing elementary and/or secondary education in all 50 states and the District of Columbia..Methodology.Data Items and Other Identifying Records.Total revenue from federal sourcesRevenue from federal sources - Distributed through the state - TotalRevenue from federal sources - Distributed through the state - Title IRevenue from federal sources - Distributed through the state - Special EducationRevenue from federal sources - Distributed through the state - Child nutritionRevenue from federal sources - Distributed through the state - VocationalRevenue from federal sources - Distributed through the state - Other and nonspecifiedRevenue from federal sources - Direct federal aid - TotalRevenue from federal sources - Direct federal aid - Impact aidTotal revenue from state sourcesRevenue from state sources - General formula assistanceRevenue from state sources - Compensatory programsRevenue from state sources - Special educationRevenue from state sources - Vocational programsRevenue from state sources - Transportation programsRevenue from state sources - Other and nonspecified state aidRevenue from state sources - State payments on behalf of LEATotal...

Key Table Information.Table Title.Government Units: U.S. and State: Census Years 1942 - 2022.Table ID.GOVSTIMESERIES.CG00ORG01.Survey/Program.Public Sector.Year.2024.Dataset.PUB Public Sector Annual Surveys and Census of Governments.Source.U.S. Census Bureau, Public Sector.Release Date.2023-08-24.Release Schedule.For information about Census of Governments planned data product releases, see https://www.census.gov/programs-surveys/gus/newsroom/updates.html.Dataset Universe.Census of Governments - Organization (CG):The universe of this file is all federal, state, and local government units in the United States. In addition to the federal government and the 50 state governments, the Census Bureau recognizes five basic types of local governments. The government types are: County, Municipal, Township, Special District, and School District. Of these five types, three are categorized as General Purpose governments: County, municipal, and township governments are readily recognized and generally present no serious problem of classification. However, legislative provisions for school district and special district governments are diverse. These two types are categorized as Special Purpose governments. Numerous single-function and multiple-function districts, authorities, commissions, boards, and other entities, which have varying degrees of autonomy, exist in the United States. The basic pattern of these entities varies widely from state to state. Moreover, various classes of local governments within a particular state also differ in their characteristics. Refer to the Individual State Descriptions report for an overview of all government entities authorized by state.The Public Use File provides a listing of all independent government units, and dependent school districts active as of fiscal year ending June 30, 2024. The Annual Surveys of Public Employment & Payroll (EP) and State and Local Government Finances (LF):The target population consists of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Survey of Public Pensions (PP):The target population consists of state- and locally-administered defined benefit funds and systems of all 50 state governments, the District of Columbia, and a sample of local governmental units (counties, cities, townships, special districts, school districts). In years ending in '2' and '7' the entire universe is canvassed. In intervening years, a sample of the target population is surveyed. Additional details on sampling are available in the survey methodology descriptions for those years.The Annual Surveys of State Government Finance (SG) and State Government Tax Collections (TC):The target population consists of all 50 state governments. No local governments are included. For the purpose of Census Bureau statistics, the term "state government" refers not only to the executive, legislative, and judicial branches of a given state, but it also includes agencies, institutions, commissions, and public authorities that operate separately or somewhat autonomously from the central state government but where the state government maintains administrative or fiscal control over their activities as defined by the Census Bureau. Additional details are available in the survey methodology description.The Annual Survey of School System Finances (SS):The Annual Survey of School System Finances targets all public school systems providing elementary and/or secondary education in all 50 states and the District of Columbia..Methodology.Data Items and Other Identifying Records.Total federal, state, and local government units by state.Unit(s) of Observation.The basic reporting unit is the governmental unit, defined as an organized entity which in addition to having governmental character, has sufficient discretion in the management of its own affairs to distinguish it as separate from the administrative structure of any other governmental unit.The reporting units for the Annual Survey of School System Finances are public school systems that provide elementary and/or secondary education. The term "public school systems" includes two types of government entities with responsibility for providing education services: (1) school districts that are administratively and fiscally independent of any other government and are counted as separate governments; and (2) public school systems that lack sufficient autonomy to be counted as separate governments and are classified as a dependent agency of some other government—a county, municipal, township, or state government. Charter school systems whose charters are held by nongovernmental entities are deemed to be out of...

Target population of patients with hypertension according to the two modes of identification.

In financial year 2021, expenditure on specialized mental health services with a general target population in Australia was 2.18 billion Australian dollars, which accounted for the majority spending for public sector specialized mental health services. Total Australian population expenditure on specialized mental health services that year amounted to more than three billion Australian dollars.

Description: The 2005 HSRC Master Sample was used for SABSSM 2008 and 2012, the SANHANES study in 2012 and SASAS 2007-2010 (adjacent EAs) to obtain an understanding of geographical spread of HIV/AIDS, perceptions and attitudes of people and other health related studies over time. Abstract: A sample can be defined as a subset containing the characteristics of a larger population. Samples are used in statistical testing when population sizes are too large for the test to include all possible members or observations. A sample should represent the whole population and not reflect bias toward a specific attribute.[1] One of the most crucial aspects of sample design in household surveys is its frame. The sampling frame has significant implications on the cost and the quality of any survey, household or otherwise.[2] The sampling frame .... in a household survey must cover the entire target population. When that frame is used for multiple surveys or multiple rounds of the same survey it is known as a master sample frame or .... master sample.[3] A master sample is a sample drawn from a population for use on a number of future occasions, so as to avoid ad hoc sampling on each occasion. Sometimes the master sample is large and subsequent inquiries are based on a sub-sample from it.[4] The HSRC compiles master samples in order to construct samples for various HSRC research studies. The 2005 HSRC Master Sample was used for SABSSM 2008 and 2012, SASAS 2007-2010 and the SANHANES study in 2012 to obtain an understanding of geographical spread of HIV/AIDS, perceptions and attitudes of people and other health related studies over time. The 2005 HSRC Master Sample was created in the following way: South Africa was delineated into EAs according to municipality and province. Municipal boundaries were obtained from the Municipal Demarcation Board. An Enumeration area (EA) is the smallest geographical unit (piece of land) into which the country is divided for census or survey enumeration.[5] The concepts and definitions of terms used for Census 2001 comply in most instances with United Nations standards for censuses. A total of 1,000 census enumeration areas (EAs) from the 2001 population census were randomly selected using probability proportional to size and stratified by province, locality type and race in urban areas from a database of 80 787 EAs that were mapped using aerial photography to develop an HSRC master sample for selecting households. The ideal frame would be complete with respect to the target population if all of its members (the universe) are covered by the frame. Ideal characteristics of a master sample: The master frame should be as complete, accurate and current as practicable. A master sample frame for household surveys is typically developed from the most recent census, just as a regular sample frame is. Because the master frame may be used during an entire intercensal (between census) period, however, it will usually require periodic and regular updating such as every 2-3 years. This is in contrast to a regular frame which is more likely to be up-dated on an ad hoc basis and only when a particular survey is being planned[6] [1] http://www.investopedia.com/terms/s/sample.asp [2] http://unstats.un.org/unsd/demographic/meetings/egm/sampling_1203/docs/no_3.pdf [3] http://unstats.un.org/unsd/demographic/meetings/egm/sampling_1203/docs/no_3.pdf [4] A Dictionary of Statistical Terms, 5th edition, prepared for the International Statistical Institute by F.H.C. Marriott. Published for the International Statistical Institute by Longman Scientific and Technical. http://stats.oecd.org/glossary/detail.asp?ID=3708 [5] http://africageodownloads.info/128_mokgokolo.pdf [6] http://unstats.un.org/unsd/demographic/meetings/egm/sampling_1203/docs/no_3.pdf All enumeration areas (80 787 EAs) within the South African borders during the 2001 Census. The whole country was delimited into EAs according to municipality and province. Municipal boundaries were obtained from the Municipal Demarcation Board. A total of 1,000 census enumeration areas (EAs) from the 2001 population census were randomly selected using probability proportional to size and stratified by province, locality type and race in urban areas from a database of 80 787 EAs that were mapped in all surveys using aerial photography to develop all HSRC master sample for selecting households. The first digit represents the province The second and third digits represent the municipality

Abstract

The PIRLS 2006 aimed to generate a database of student achievement data in addition to information on student, parent, teacher, and school background data for the 47 areas that participated in PIRLS 2006.

Geographic coverage

Nationally representative

Analysis unit

Units of analysis in the study are schools, students, parents and teachers.

Universe

PIRLS is a study of student achievement in reading comprehension in primary school, and is targeted at the grade level in which students are at the transition from learning to read to reading to learn, which is the fourth grade in most countries. The formal definition of the PIRLS target population makes use of UNESCO's International Standard Classification of Education (ISCED) in identifying the appropriate target grade:

"…all students enrolled in the grade that represents four years of schooling, counting from the first year of ISCED Level 1, providing the mean age at the time of testing is at least 9.5 years. For most countries, the target grade should be the fourth grade, or its national equivalent."

ISCED Level 1 corresponds to primary education or the first stage of basic education, and should mark the beginning of "systematic apprenticeship of reading, writing, and mathematics" (UNESCO, 1999). By the fourth year of Level 1, students have had 4 years of formal instruction in reading, and are in the process of becoming independent readers. In IEA studies, the above definition corresponds to what is known as the international desired target population. Each participating country was expected to define its national desired population to correspond as closely as possible to this definition (i.e., its fourth grade of primary school). In order to measure trends, it was critical that countries that participated in PIRLS 2001, the previous cycle of PIRLS, choose the same target grade for PIRLS 2006 that was used in PIRLS 2001. Information about the target grade in each country is provided in Chapter 9 of the PIRLS 2006 Technical Report.

Although countries were expected to include all students in the target grade in their definition of the population, sometimes it was not possible to include all students who fell under the definition of the international desired target population. Consequently, occasionally a country's national desired target population excluded some section of the population, based on geographic or linguistic constraints. For example, Lithuania's national desired target population included only students in Lithuanian-speaking schools, representing approximately 93 percent of the international desired population of students in the country. PIRLS participants were expected to ensure that the national defined population included at least 95 percent of the national desired population of students. Exclusions (which had to be kept to a minimum) could occur at the school level, within the sampled schools, or both. Although countries were expected to do everything possible to maximize coverage of the national desired population, school-level exclusions sometimes were necessary. Keeping within the 95 percent limit, school-level exclusions could include schools that:

• were geographically remote,
• had very few students,
• had a curriculum or structure different from the mainstream education system, or
• were specifically for students with special needs.

The difference between these school-level exclusions and those at the previous level is that these schools were included as part of the sampling frame (i.e., the list of schools to be sampled). Th ey then were eliminated on an individual basis if it was not feasible to include them in the testing.

In many education systems, students with special educational needs are included in ordinary classes. Due to this fact, another level of exclusions is necessary to reach an eff ective target population-the population of students who ultimately will be tested. These are called within-school exclusions and pertain to students who are unable to be tested for a particular reason but are part of a regular classroom. There are three types of within-school exclusions.

• Intellectually disabled students
• Functionally disabled students
• Non-native language speakers

Students eligible for within-school exclusion were identified by staff at the schools and could still be administered the test if the school did not want the student to feel out of place during the assessment (though the data from these students were not included in any analyses). Again, it was important to ensure that this population was as close to the national desired target population as possible. If combined, school-level and within-school exclusions exceeded 5 percent of the national desired target population, results were annotated in the PIRLS 2006 International Report (Mullis, Martin, Kennedy, & Foy, 2007). Target population coverage and exclusion rates are displayed for each country in Chapter 9 of the PIRLS 2006 Technical Report. Descriptions of the countries' school-level and within-school exclusions can be found in Appendix B of the PIRLS 2006 Technical Report.

Kind of data

Sample survey data [ssd]

Sampling procedure

The basic sample design used in PIRLS 2006 is known as a two-stage stratified cluster design, with the first stage consisting of a sample of schools, and the second stage consisting of a sample of intact classrooms from the target grade in the sampled schools. While all participants adopted this basic two-stage design, four countries, with approval from the PIRLS sampling consultants, added an extra sampling stage. The Russian Federation and the United States introduced a preliminary sampling stage, (first sampling regions in the case of the Russian Federation and primary sampling units consisting of metropolitan areas and counties in the case of the United States). Morocco and Singapore also added a third sampling stage; in these cases, sub-sampling students within classrooms rather than selecting intact classes.

For countries participating in PIRLS 2006, school stratification was used to enhance the precision of the survey results. Many participants employed explicit stratification, where the complete school sampling frame was divided into smaller sampling frames according to some criterion, such as region, to ensurea predetermined number of schools sampled for each stratum. For example, Austria divided its sampling frame into nine regions to ensure proportional representation by region (see Appendix B for stratification information for each country). Stratification also could be done implicitly, a procedure by which schools in a sampling frame were sorted according to a set of stratification variables prior to sampling. For example, Austria employed implicit stratification by district and school size within each regional stratum. Regardless of the other stratification variables used, all countries used implicit stratification by a measure of size (MOS) of the school.

All countries used a systematic (random start, fixed interval) probability proportional-to-size (PPS) sampling approach to sample schools. Note that when this method is combined with an implicit stratification procedure, the allocation of schools in the sample is proportional to the size of the implicit strata. Within the sampled schools, classes were sampled using a systematic random method in all countries except Morocco and Singapore, where classes were sampled with probability proportional to size, and students within classes sampled with equal probability. The PIRLS 2006 sample designs were implemented in an acceptable manner by all participants.

Sampling deviation

8 National Research Coordinators (NRCs) encountered organizational constraints in their systems that necessitated deviations from the sample design. In each case, the Statistics Canada sampling expert was consulted to ensure that the altered design remained compatible with the PIRLS standards.

These country specific deviations from sample design are detailed in Appendix B of the PIRLS 2006 Technical Report (page 231) attached as Related Material.

Mode of data collection

Face-to-face [f2f]

Research instrument

• PIRLS Background Questionnaires By gathering information about children’s experiences together with reading achievement on the PIRLS test, it is possible to identify the factors or combinations of factors that relate to high reading literacy. An important part of the PIRLS design is a set of questionnaires targeting factors related to reading literacy. PIRLS administered four questionnaires: to the tested students, to their parents, to their reading teachers, and to their school principals.

• Student Questionnaire Each student taking the PIRLS reading assessment completes the student questionnaire. The questionnaire asks about aspects of students’ home and school experiences - including instructional experiences and reading for homework, self-perceptions and attitudes towards reading, out-of-school reading habits, computer use, home literacy resources, and basic demographic information.

• Learning to Read (Home) Survey The learning to read survey is completed by the parents or primary caregivers of each student taking the PIRLS reading assessment. It addresses child-parent literacy interactions, home literacy resources, parents’ reading habits and attitudes, homeschool connections, and basic demographic and socioeconomic indicators.

• Teacher Questionnaire The reading teacher of each fourth-grade class sampled for PIRLS completes a questionnaire designed to gather information about classroom contexts for developing reading literacy. This questionnaire