As a uniform, multi-State database, the NIS promotes comparative studies of healthcare services and supports healthcare policy research on a variety of topics, including: Utilization of health services by special populations Hospital stays for rare conditions Variations in medical practice Healthcare cost inflation Regional and national analyses Quality of care and patient safety Impact of health policy changes The NIS is used in a variety of publications and online tools: HCUPnet is a free, on-line query system based on data from HCUP.
HCUP Fast Stats is an online query tool that uses visual displays to compare national or State statistics on a range of healthcare topics. Return to Contents. Spanning more than 20 years of data, the NIS is ideal for longitudinal analyses. However, the database has undergone changes over time, including the sampling and weighting strategy used.
Users of the NIS should expect a one-time decrease to historical trends for discharge counts of about 4 percent beginning with data year Users should also expect smaller one-time disruptions to historical trends for rates and means estimated from the NIS, beginning with data year For trends analysis using NIS data and earlier, revised weights should be used to make estimates comparable to the new design beginning with data.
The data set includes weights for producing national and regional estimates. The file structure is similar to the file structure of the NIS in data years and prior years. The data elements and file structure for the NIS are different. Trends based on diagnoses or procedures will be affected. For prior years, the NIS was a sample of hospitals.
What's New in the NIS? National YRBS data are representative of all public and private school students in grades in the 50 states and the District of Columbia.
Most state, territory, tribal government, and local YRBS data that are weighted are representative of all public school students in grades in the respective jurisdiction. State, territory, tribal government, and local YRBS data that are not weighted are representative only of the students who completed the survey in the respective jurisdiction. Weighting is a mathematical procedure that makes data representative of the population from which it was drawn.
In the YRBSS, only surveys with a scientifically drawn sample, appropriate documentation, and no evidence of significant nonresponse bias are weighted.
YRBSS data are weighted to adjust for school and student nonresponse and to make the data representative of the population of students from which the sample was drawn. Skip directly to site content Skip directly to page options Skip directly to A-Z link. Adolescent and School Health. Section Navigation. Facebook Twitter LinkedIn Syndicate. Minus Related Pages.
Open All Close All. Is there a cost? Why are results not available from every state? Is funding available for conducting a YRBS? YRBS Questionnaires. How are questions selected for inclusion on the YRBS questionnaire? What is the process for getting a question added to the YRBS questionnaire or getting an existing question changed?
Will asking questions about certain topics actually encourage certain behaviors? Does the YRBS identify transgender students? How are the national, state, territory, tribal government, and local YRBS data different? Are the national data the aggregate of the all of the state and other YRBS data? Is there a national middle school YRBS? Is it possible to analyze associations between state-level characteristics and student-level behaviors using the National YRBS data?
Do students tell the truth on the YRBS questionnaire? It is, of course, also possible to use the read. In the data called testsemicolon. The scan function is an extremely flexible tool for importing data.
It can be used to read in almost any type of data, numeric, character or complex and it can be used for fixed or free formatted files. Moreover, by using the scan function it is possible to input data directly from the console.
The scan function reads the fields of data in the file as specified by the what option with the default being numeric. If the data is a mix of numeric, string or complex data then a list can be used in the what option.
The default separator for the scan function is any white space single space, tab, or new line. However, unlike the read. In the following examples we input first numeric data and then string data directly from the console; then we input the text file, scan. For fixed format files the variables names are often in a separate file from the data.
Law Enforcement Federal Law Enforcement. Law Enforcement Tribal Law Enforcement. Law Enforcement Campus Law Enforcement. Law Enforcement Forensic Investigation. Law Enforcement Police-Public Contacts. Law Enforcement Use of Force. Law Enforcement Arrest-Related Deaths. Law Enforcement Community Policing.
Law Enforcement Special Topics. Victims Research and Development. Victims Victim characteristics. Victims Crime characteristics and trends. Victims Victims and offenders. Victims The Crime event. Victims Reporting crimes to police. Victims Special topics. Victims Victim Service Providers. Home Raw data. In cooperation with data. The datasets listed on this page are: "raw" or unaggregated data intended for analytic use include crime, justice and sociodemographic variables Data confidentiality Federal law and regulations require that research data collected by the U.
Department of Justice or by its grantees and contractors may only be used for statistical and research analysis. In some cases, SPS data setup files may also be provided. All files are provided as compressed ZIP files to expedite download. Help with using BJS products.
Index of available files by topic - Corrections data Courts and sentencing data Law Enforcement data Victimization data Corrections data Annual Survey of Jails in Indian Country The survey of all known confinement facilities operated by tribal authorities or the Bureau of Indian Affairs BIA , provides data on number of inmates and facility characteristics and needs.
The NCVS was designed with four primary objectives: 1 to develop detailed information about the victims and consequences of crime, 2 to estimate the number and types of crimes both reported and not reported to the police, 3 to provide uniform measures of selected types of crimes, and 4 to permit comparisons over time and types of areas. The survey categorizes crimes as "personal" or "property.
Each respondent is asked a series of screen questions designed to determine whether she or he was victimized during the six-month period preceding the interview. A "household respondent" is also asked to report on crimes against the household as a whole e.
The data include type of crime, month, time, and location of the crime, relationship between victim and offender, characteristics of the offender, self-protective actions taken by the victim during the incident and results of those actions, consequences of the victimization, type of property lost, whether the crime was reported to police and reasons for reporting or not reporting, and offender use of weapons, drugs, and alcohol.
Basic demographic information such as age, race, gender, and income is also collected, to enable analysis of crime against various subpopulations. Back to Top. Jail inmate characteristics Local jail facility characteristics. Prison population counts Prison inmate characteristics State and federal prison facility characteristics Special topics.
Probation Parole Parole agencies. Justice Expenditures and Employment data Prison Expenditures. Number under sentence of death Executions. Tort, contract and real property trials Medical malpractice trials Punitive damages in civil trials Civil Appeals. Drug use and crime. Schools Workplace. State profiles.
Traffic Stops. Aviation Units. Violent crime Property crime.
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