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Showing 1 – 14 of 14 results.

Curated

Simple Crosstabs

Applying Artificial Intelligence to Person-Based Policing Practices, 2019-2023 (ICPSR 39074)

Released/updated on: 2024-09-26

Time period: 2019-01-01--2023-01-01

In this project, the research team developed and evaluated an artificial intelligence (AI) tool using agent-based modeling methods for crime analysis and risk evaluation (CARE): CAREsim. The purpose of this tool was to improve the effectiveness of person-based patrol strategies, where police take preemptive actions upon selected high-risk individuals (determined based on factors known to police such as violent crime history) when predicted risks of committing crimes are high. CARESim was developed and tested with a simulated randomized controlled experiment within the jurisdiction of Hampton, Virginia. 240 high-risk individuals (120 in each group) were followed for a 12-month period, with the simulation lasting 23 months. The treatment group received additional crime analyses using the AI tool and more focused patrols, while the control group received analyses as usual and random patrols in the simulated environment. The tool was evaluated on a series of outcomes (e.g., number of crimes and arrests) comparing the control and treatment groups. This collection contains the simulated high-risk individual data (DS1) and the simulated crimes data (DS2) used for the experiment.

Curated

Census of Population and Housing, 1980 [United States]: Master Area Reference File (MARF): 1978 Richmond Dress Rehearsal (ICPSR 7850)

Released/updated on: 1992-02-16

Geographic coverage: United States, Virginia

Master Area Reference Files (MARFs) link geographic areas with their respective numeric codes. This data collection comprises preliminary data collected in a dress rehearsal census in the spring of 1978 from all persons and housing units in Richmond City, Henrico County, and Chesterfield County, Virginia. The purpose of the dress rehearsal program was to use the planned final materials and procedures in locations which simulated various conditions the Bureau would face in the 1980 Census. The data file was prepared in the same format as the 1980 Census MARF and was designed primarily by programmers for developing their software for data retrieval. This release of the MARF contains geographic items from Summary Tape File 1 (STF1), as well as population counts by race and Spanish origin, the number of one-person households, the total number of housing units, and the number of occupied and owner-occupied housing units.

Curated

Comparison of Methods for Learning Choropleth Maps [1988-1990: United States] (ICPSR 9759)

Released/updated on: 2006-01-12

Geographic coverage: United States

The purpose of this study was to gather information on how people learn choropleth maps and to determine which of various computer display methods is most appropriate for learning this type of map. Software was developed to enable users to explore data commonly portrayed as a choropleth map. The software was then tested in controlled experiments using undergraduates at the University of Kansas. The design for Experiments I and II, which explored reactions to the sequencing of parts of a map as compared to the more traditional method of displaying a map all at once, consisted of formal and informal portions. In the formal portion, the actual effectiveness of traditional and sequenced maps was examined. The speed and accuracy of information acquisition and retention (memory) of subjects was the focus of this phase. In the informal portion, subjects viewed several display methods and (1) picked their most and least preferred methods, (2) explained their preferences, and (3) suggested alternative display methods. Dataset 1 contains data collected in association with the publication listed below. Datasets 2 and 3 consist of data from Experiments I and II, respectively, while Dataset 4 is a text file containing the verbal protocols used for Experiment I.

Curated

Congressional Redistricting Computer Program (ICPSR 7244)

Released/updated on: 1992-02-16

This collection consists of a computer program designed to reapportion a legislature or any other body of people representing geographical districts. The program was built to produce the districting pattern that would result from agreed-upon values or the diverse patterns resulting from conflicting values. Input information consists of descriptions of units that would make up the districts, such as county, ward, and census tract, plus additional information for each time an area within a state is redistricted, consisting of both factual and value parameters. The output includes old and new districts along with certain characteristics of each old and new district. The program enables the user to adjust the relative weight to be given to three significant considerations: the relative equality of population among the districts (the one man-one vote requirement), the contiguity and degree of compactness of the districts, and the impact of redistricting on the political balance of power.

Curated

Developing and Testing New Methods for Estimating Treatment Effectiveness in Observational Studies Using High-Dimensional Data [Methods Study], 2023 (ICPSR 39090)

Released/updated on: 2024-04-18

Propensity scores (PS) and instrumental variables (IV) are methods used to assess treatment effects in observational studies when randomized controlled trials (RCTs) are not feasible. However, these methods have limitations, especially when using high-dimensional data, or data with numerous variables or many non-linear and interaction terms. Choices on which variables and non-linear and interaction terms to include may lead to model misspecification. The objective of this study was to develop and test a set of PS and IV methods that account for model misspecification when estimating causal effects of treatments using high-dimensional data.

First, the research team created the two new methods for use with high-dimensional data. The team then used a computer program to create test data that look like real patient data. The team applied the new methods to the test data. Next, the research team applied the new methods to real data from previous studies. They applied the PS method to data from Connors et al. (1996) and applied the IV method to data used by Card (1995). Using both test and real data, the research team compared findings from the new methods with those from existing PS and IV methods and checked to see if findings from the new methods were accurate when including different patient traits and health conditions in the analysis.

This collection contains the R software package RCAL and accompanying documentation. The package source as a .tar.gz file and six different versions are available in a zipped package. Files have been released as received by ICPSR from the depositor:

For R version 4.2, created April 24, 2022 (Windows, r-oldrel)
For R version 4.3, created October 20, 2023 (Windows, r-release)
For R version 4.4, created March 14, 2024 (Windows, r-devel)
For R version 4.2, created April 1, 2023 (Mac, arm64, r-oldrel)
For R version 4.3, created April 6, 2023 (Mac, arm64, r-release)
For R version 4.3, created April 11, 2023 (Mac, x86_64, r-release)

Curated

Evaluation of the Community Supervision Mapping System for Released Prisoners in Rhode Island, 2008-2010 (ICPSR 32004)

Released/updated on: 2014-09-30

Geographic coverage: Rhode Island, United States

Time period: 2008-01-01--2010-01-01

This study evaluated the Community Supervision Mapping System (CSMS), an online geospatial tool that enables users to map the formerly incarcerated and others on probation, along with related data such as service provider locations and police districts. Probation officers in the state of Rhode Island were surveyed a few weeks before and 18 months after the implementation of CSMS. A total of 56 probation officers participated in the first wave of the study (pre-implementation survey), and 52 probation officers participated in the second wave (post-implementation survey), yielding an overall sample size of 108 probation officers. Dataset 1 contains the data for both waves of the study. The dataset is comprised of 140 variables. Both waves of the study examined the following categories of variables: the probation officer's professional background, contact with clients, amount of time spent on job duties specific to the profession, contact with other agencies, and computer usage. The second wave added 86 variables to explore officers' experiences with CSMS, which features they used, how it impacted their work, and their expected use of CSMS in the future.

Curated

Simple Crosstabs

Global Digital Activism Data Set, 2013 (ICPSR 34625)

Released/updated on: 2014-06-12

Geographic coverage: Papua New Guinea, Cambodia, Paraguay, Kazakhstan, Syria, Solomon Islands, Bahamas, Gibralter, Montserrat, Mali, Marshall Islands, Panama, Guadeloupe, Virgin Islands of the United States, Laos, Argentina, Falkland Islands, Seychelles, Zambia, Belize, Bahrain, Guinea-Bissau, Namibia, Finland, Comoros, Faroe Islands, Yemen, Puerto Rico, Eritrea, China (Peoples Republic), Madagascar, Aruba, Ivory Coast, Libya, Western Samoa, Sweden, Malawi, Andorra, Liechtenstein, Poland, Jordan, Bulgaria, Tunisia, Channel Islands, United Arab Emirates, Tuvalu, Kenya, French Polynesia, Lebanon, Djibouti, Brunei, Azerbaijan, Cuba, Czech Republic, Mauritania, Saint Lucia, Mayotte, Israel, San Marino, Australia, Bonaire, Tajikistan, Myanmar, Cameroon, Cyprus, Northern Mariana Islands, Bermuda Islands, Malaysia, Iceland, Global, Oman, Armenia, Gabon, Luxembourg, Brazil, Turks and Caicos Islands, Algeria, Slovenia, Antigua and Barbuda, Ecuador, Colombia, Moldova, Vanuatu, Italy, Honduras, Micronesia (Federated States), Nauru, Haiti, Afghanistan, Burundi, Singapore, French Guiana, American Samoa, Vatican City, Russia, Netherlands, Martinique, Saint Pierre and Miquelon, Kyrgyzstan, Reunion, Bhutan, Romania, Togo, Philippines, Uzbekistan, Democratic Republic of Congo, British Virgin Islands, Zimbabwe, Montenegro, Indonesia, Dominica, Benin, Angola, Sudan, East Timor, Saba, Portugal, New Caledonia, Grenada, Greece, Cayman Islands, Mongolia, Latvia, Morocco, Iran, Bosnia-Hercegovina, Guatemala, Guyana, Iraq, Chile, Nepal, Georgia (Republic), Isle of Man, Ukraine, Tanzania, Ghana, Anguilla, India, Canada, Maldives, Turkey, Belgium, Trinidad and Tobago, Central African Republic, Jamaica, Peru, Turkmenistan, Germany, Vietnam (Socialist Republic), Fiji, Tokelau, United States, Guinea, Chad, Somalia, Sao Tome and Principe, Thailand, Equatorial Guinea, Kiribati, Costa Rica, Pitcairn Island, Kuwait, Nigeria, Croatia, Uruguay, Sri Lanka, Cook Islands, United Kingdom, Switzerland, Spain, Palestine, Liberia, Venezuela, Burkina Faso, Swaziland, Palau, Estonia, Wallis and Futuna, Niue, South Korea, Austria, Mozambique, El Salvador, Monaco, Guam, Lesotho, Tonga, Hungary, Japan, Belarus, Curacao, Mauritius, Albania, Norfolk Island, New Zealand, Senegal, Macedonia, Ethiopia, Egypt, Sierra Leone, Bolivia, Malta, Saudi Arabia, Cape Verde, Saint Eustatius, Pakistan, Gambia, Ireland, Qatar, Slovakia, France, Serbia, Lithuania, Saint Kitts-Nevis, Niger, Rwanda, Bangladesh, Nicaragua, Barbados, Norway, Botswana, Saint Vincent and the Grenadines, Denmark, Dominican Republic, Mexico, Uganda, Suriname, Saint Helena, Greenland

Time period: 1982-01-01--2012-01-01

The Global Digital Activism Data Set (GDADS), released February 2013 by the Digital Activism Research Project (DARP) at the University of Washington in Seattle, features coded cases of online digital activism from 151 countries and dependent territories. Several features from each case of digital activism were documented, including the year that online action commenced, the country of origin of the initiator(s), the geographic scope of their campaign, and whether the action was online only, or also featured offline activities. Researchers were interested in the number and types of software applications that were used by digital activists. Specifically, information was collected on whether software applications were used to circumvent censorship or evade government surveillance, to transfer money or resources, to aid in co-creation by a collaborative group, or for purposes of networking, mobilization, information sharing, or technical violence (destructive/disruptive hacking). The collection illustrates the overall focus of each case of digital activism by defining the cause advanced or defended by the action, the initiator's diagnosis of the problem and its perceived origin, the identification of the targeted audience that the campaign sought to mobilize, as well as the target whose actions the initiators aimed to influence. Finally, each case of digital activism was evaluated in terms of its success or failure in achieving the initiator's objectives, and whether any other positive outcomes were apparent.

Self-published

Improving Outcomes for English Learners through Technology: A Randomized Controlled Trial (ICPSR 141061)

Released/updated on: 2021-06-01

Geographic coverage: United States

Time period: 2017-08-01--2018-06-01

English Learners (ELs) in K-12 schools must acquire English while simultaneously mastering content knowledge. Educational technology may support students’ learning through the affordance of individualized language practice. The current randomized controlled trial intervention study examined the effects of Rosetta Stone® Foundations software on English learning among middle school ELs. The study took place in grades 6-8 of an urban U.S. school district (N=221). Predictors of interest included: time of testing (pretest vs posttest) and software usage, and covariates included grade level, sex, and attendance. Additionally, SES and home language were accounted for due to sample homogeneity. Multilevel models indicated that treatment group students showed larger gains than control group students on oral/aural outcomes. These results indicate that the software intervention enables individualized practice that can produce proficiency-related gains over and above the typical classroom curriculum.

Curated

Law Enforcement Assistance Administration Profile Data, [1968-1978] (ICPSR 8075)

Released/updated on: 1992-02-16

Time period: 1968-01-01--1978-01-01

The Law Enforcement Assistance Administration File (PROFILE) System was designed for the automated storage and retrieval of information describing programs sponsored by the Bureau of Justice Statistics. The two types of data elements used to describe the projects in this file are basic data and program descriptors. The basic data elements include the title of the grant, information regarding the location of the grantee and the project, critical funding dates, the government level and type of grantee, financial data, the name of the project director, indication of the availability of reports, and identification numbers. The program descriptor elements form the program classification system and describe the key characteristics of the program. Key characteristics include subject of the program, primary and secondary activity, whether the program covered a juvenile or adult problem, and what specific crimes, clients, staff, program strategies, agencies, equipment, or research methods were to be used or would be affected by the project.

Curated

Learning Within Health Care Delivery Systems: Design, Analysis, and Interpretation of Longitudinal Cluster Randomized Trials [Methods Study], 2023 (ICPSR 39089)

Released/updated on: 2024-05-16

Cluster randomized trials, or CRTs, are research studies that compare treatments among different groups of patients, or clusters. An example of a cluster is a group of people who receive care at a single clinic. One type of CRT is a stepped-wedge CRT. These CRTs compare patients' health before and after a new treatment. In stepped-wedge CRTs, all groups start with the standard treatment. Then, each group switches to the new treatment at a specific time during the study. By the end of the study, all groups are receiving the new treatment. In stepped-wedge CRTs, group characteristics, such as how clinics follow up with patients, can affect how well a treatment works. It is hard to figure out if changes in a patient's health are due to the treatment or group characteristics. In this study, the research team wanted to improve how to plan and analyze stepped-wedge CRTs for studying the effect of treatments.

The study had two parts. In the first part, the research team looked at ways to measure how well treatments work in stepped-wedge CRTs in ways that account for group characteristics. In the second part, the research team looked at which statistical methods got accurate results when using data from stepped-wedge CRTs. The team first used a computer program to create test data that looked like data from a stepped-wedge CRT. The team created the test data using nine scenarios; each scenario had a different set of conditions. For example, the number of patient groups varied across each scenario. Using the test data, the team compared six statistical methods for analyzing data from stepped-wedge CRTs. The research team also created a statistical program to help plan and analyze stepped-wedge CRTs.

This collection contains the R software package swCRTdesign and accompanying documentation. The package source as a .tar.gz file and six different versions are available in a zipped package. Files have been released as received by ICPSR from the depositor:

For R version 4.2.3, created March, 11, 2024 (Windows)
For R version 4.3.3, created March, 10, 2024 (Windows)
For R version 4.4.0, created March, 11, 2024 (Windows)
For R version 4.2.0, created August, 27, 2023 (macOS)
For R version 4.3.0, created August, 26, 2023 (macOS)
For R version 4.3.0, created August, 27, 2023 (macOS)

Curated

Randomize Everyone: Creating Valid Instrumental Variables for Learning Health Care Systems [Methods Study], New Hampshire, 2016-2022 (ICPSR 39717)

Released/updated on: 2026-03-17

Geographic coverage: United States, New Hampshire

Time period: 2016-01-01--2022-01-01

Comparative effectiveness research, or CER, compares two or more treatments. In some CER studies, researchers use patient data from electronic health records, or EHRs, to compare treatments. But patient traits like age may affect doctors' and patients' choice of treatments, which can bias results. Using EHR systems to identify eligible patients and assign them to treatments by chance could improve results of CER studies that use EHR data.

In this study, the research team explored the views of patients, clinic staff, and clinicians, such as doctors or nurses, on doing CER studies in clinics. The team also tested software with a widely used EHR system. The software finds patients who qualify for a study. During a clinic visit, the software prompts doctors to invite patients to take part in the study. If patients agree, the software assigns patients by chance to a treatment.

Curated

Retail Sweep Programs and Bank Reserves (ICPSR 1236)

Released/updated on: 2001-04-02

Geographic coverage: United States

Since January 1994, the Federal Reserve Board has permitted depository institutions in the United States to implement so-called "retail sweep programs." The essence of these programs is computer software that dynamically reclassifies customer deposits from transaction accounts, which are subject to statutory reserve-requirement ratios as high as 10 percent, to money market deposit accounts, which have a zero ratio. Through the use of such software, hundreds of banks have sharply reduced the amount of their required reserves. In many cases, this new lower requirement places no constraint on the bank because it is less than the amount of reserves (vault cash and deposits at the Federal Reserve) that the bank requires for its ordinary day-to-day business. In the terminology introduced by the authors in a previous article (see MEASURING THE ADJUSTED MONETARY BASE IN AN ERA OF FINANCIAL CHANGE [ICPSR 1169]), such deposit-sweeping activity has allowed these banks to become "economically nonbound" and has reduced to zero the economic burden ("tax") due to statutory reserve requirements. In this analysis, the authors examine a large panel of United States banks and develop quantitative estimates of the impact of sweep software programs on the demand for bank reserves.

Curated

School Crime Operations Package (School COP Software) (ICPSR 23543)

Released/updated on: 2008-10-09

Geographic coverage: United States

The School Crime Operations Package (School COP) is a software application developed by Abt Associates Inc. with funding from the National Institute of Justice. School COP is a free software package that persons responsible for school safety can use to enter, analyze, and map criminal incidents and school rule violations that occur in and around K-12 schools. School COP organizes information according to the data model that the United States Department of Education's National Center for Education Statistics' Crime, Violence, and Discipline Reporting Task Force recommends. The School COP database includes data related to the incident (e.g., date, time, type, location) and to persons involved in the incident (e.g., name, grade, action taken). In other words, School COP is an incident-based system, rather than a student-based system. School COP offers a variety of techniques for analyzing school incidents, including tabular reports, bar graphs, pie charts, and maps. School COP can be installed on any Windows (95 or later) PC. It requires no other software to run, and is usable without formal training.

The origin of this project is an award to Abt Associates Inc. that was funded under the National Institute of Justice's (NIJ) June 1999 "Safe Schools Technology" solicitation, which requested proposals for innovative approaches to using technology to enhance the safety of our nation's elementary and secondary schools. School COP was initially released on CD-ROM in January 2001, and made available at the School COP Web site in June 2001. This Windows version of School COP was generally designed for individuals, for a single school, or for small offices within a school district. Abt Associates Inc. was subsequently awarded another grant in 2001 to enhance the School Crime Operations Package (School COP) and to conduct an evaluation of this software, which is used to enter and analyze incidents that occur on school campuses.

Two types of enhancements were made. First, an enhanced Windows version of School COP was developed that could run on a local- or wide-area network, thus allowing multiple users within a single school or across multiple schools to share a common School COP database. The enhanced Windows version also included two utilities: a Merge application (which enables a district-level School COP database to be constructed by merging several individual databases) and a Viewer application (which enables users to view -- but not add, edit, or delete -- incident information). Second, Web School COP was developed to meet the diverse information needs of persons charged with maintaining safe schools in large school districts, including persons at the school-level (e.g., principals, assistant principals, security officers, and school resource officers), the district-level (e.g., district-level administrators and security staff), as well as possibly parent organizations and state-level administrators. Web School COP was designed to run on either an Intranet (e.g., the school district's private Internet) or a secure third-party Web server, and was built to run on the current Microsoft Web platform.

The evaluation of School COP entailed case studies of six sites to address three main issues: (1) what decision process do sites go through when deciding whether to use School COP, (2) once the site decides to use School COP, what implementation obstacles exist, including those related to installation, customization, and training, and (3) what benefits do sites realize from using School COP.

Curated

Statistical Software Benchmarks (ICPSR 1243)

Released/updated on: 2001-10-31

This study provides tools to test the reliability of selected statistical software: Excel, Gauss, Stata, and SST. Functions covered include non-linear optimization algorithms, distributions, and pseudo-random number generators.