PLOSsyphThis is an ASCII file that is space delimited that was created in SAS. It has the variables that were used in the published paper. The readme.sas file is a .sas file that reads the data. You will need to change the infile statement to reflect the path to where you put the data.

File List Code_and_Data_Supplement.zip (md5: dea8636b921f39c9d3fd269e44b6228c) Description The supplementary material provided includes all code and data files necessary to replicate the simulation models other demographic analyses presented in the paper. MATLAB code is provided for the simulations, and SAS code is provided to show how model parameters (vital rates) were estimated.

  The principal programs are Figure_3_4_5_Elasticity_Contours.m and Figure_6_Contours_Stochastic_Lambda.m which perform the elasticity analyses and run the stochastic simulation, respectively.


  The files are presented in a zipped folder called Code_and_Data_Supplement. When uncompressed, users may run the MATLAB programs by opening them from within this directory. Subdirectories contain the data files and supporting MATLAB functions necessary to complete execution. The programs are written to find the necessary supporting functions in the Code_and_Data_Supplement directory. If users copy these MATLAB files to a different directory, they must add the Code_and_Data_Supplement directory and its subdirectories to their search path to make the supporting files available.


  More details are provided in the README.txt file included in the supplement.


  The file and directory structure of entire zipped supplement is shown below.

  Folder PATH listing
Code_and_Data_Supplement
|  Figure_3_4_5_Elasticity_Contours.m
|  Figure_6_Contours_Stochastic_Lambda.m
|  Figure_A1_RefitG2.m
|  Figure_A2_PlotFecundityRegression.m
|  README.txt
|  
+---FinalDataFiles
+---Make Tables
|    README.txt
|    Table_lamANNUAL.csv
|    Table_mgtProbPredicted.csv
|    
+---ParameterEstimation
|  |  Categorical Model output.xls
|  |  
|  +---Fecundity
|  |    Appendix_A3_Fecundity_Breakpoint.sas
|  |    fec_Cat_Indiv.sas
|  |    Mean_Fec_Previous_Study.m
|  |    
|  +---G1
|  |    G1_Cat.sas
|  |    
|  +---G2
|  |    G2_Cat.sas
|  |    
|  +---Model Ranking
|  |    Categorical Model Ranking.xls
|  |    
|  +---Seedlings
|  |    sdl_Cat.sas
|  |    
|  +---SS
|  |    SS_Cat.sas
|  |    
|  +---SumSrv
|  |    sum_Cat.sas
|  |    
|  \---WinSrv
|      modavg.m
|      winCatModAvgfitted.m
|      winCatModAvgLinP.m
|      winCatModAvgMu.m
|      win_Cat.sas
|      
+---ProcessedDatafiles
|    fecdat_gm_param_est_paper.mat
|    hierarchical_parameters.mat
|    refitG2_param_estimation.mat
|    
\---Required_Functions
  |  hline.m
  |  hmstoc.m
  |  Jeffs_Figure_Settings.m
  |  Jeffs_startup.m
  |  newbootci.m
  |  sem.m
  |  senstuff.m
  |  vline.m
  |  
  +---export_fig
  |    change_value.m
  |    eps2pdf.m
  |    export_fig.m
  |    fix_lines.m
  |    ghostscript.m
  |    license.txt
  |    pdf2eps.m
  |    pdftops.m
  |    print2array.m
  |    print2eps.m
  |    
  +---lowess
  |    license.txt
  |    lowess.m
  |    
  +---Multiprod_2009
  |  |  Appendix A - Algorithm.pdf
  |  |  Appendix B - Testing speed and memory usage.pdf
  |  |  Appendix C - Syntaxes.pdf
  |  |  license.txt
  |  |  loc2loc.m
  |  |  MULTIPROD Toolbox Manual.pdf
  |  |  multiprod.m
  |  |  multitransp.m
  |  |  
  |  \---Testing
  |    |  arraylab13.m
  |    |  arraylab131.m
  |    |  arraylab132.m
  |    |  arraylab133.m
  |    |  genop.m
  |    |  multiprod13.m
  |    |  readme.txt
  |    |  sysrequirements_for_testing.m
  |    |  testing_memory_usage.m
  |    |  testMULTIPROD.m
  |    |  timing_arraylab_engines.m
  |    |  timing_matlab_commands.m
  |    |  timing_MX.m
  |    |  
  |    \---Data
  |        Memory used by MATLAB statements.xls
  |        Timing results.xlsx
  |        timing_MX.txt
  |        
  +---province
  |    PROVINCE.DBF
  |    province.prj
  |    PROVINCE.SHP
  |    PROVINCE.SHX
  |    README.txt
  |    
  +---SubAxis
  |    parseArgs.m
  |    subaxis.m
  |    
  +---suplabel
  |    license.txt
  |    suplabel.m
  |    suplabel_test.m
  |    
  \---tight_subplot
      license.txt
      tight_subplot.m

Abstract (en): This data collection provides comparable measures of state appellate and trial court caseloads by type of case for the 50 states, the District of Columbia, and Puerto Rico. Court caseloads are tabulated according to generic reporting categories developed by the Court Statistics Project Committee of the Conference of State Court Administrators. These categories describe differences in the unit of count and the point of count when compiling each court's caseload. Major areas of investigation include (1) case filings in state appellate and trial courts, (2) case processing and dispositions in state appellate and trial courts, and (3) appellate opinions. Within each of these areas of state government investigation, cases are separated by main case type, including civil cases, capital punishment cases, other criminal cases, juvenile cases, and administrative agency appeals. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Checked for undocumented or out-of-range codes.. State appellate and trial court cases in the United States. 2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.2003-08-27 Part 45, Appellate Court Data, 2001, and Part 46, Trial Court Data, 2001, have been added to the data collection, along with corresponding SAS and SPSS data definition statements and PDF codebooks.2002-08-13 Part 43, Appellate Court Data, 2000, and Part 44, Trial Court Data, 2000, have been added to the data collection, along with corresponding SAS and SPSS data definition statements and PDF codebooks.2001-10-31 Part 41, Appellate Court Data, 1999, and Part 42, Trial Court Data, 1999, have been added to the data collection, along with corresponding SAS and SPSS data definition statements and PDF codebooks.2000-03-23 Part 39, Appellate Court Data, 1998, and Part 40, Trial Court Data, 1998, have been added to the data collection, along with corresponding SAS and SPSS data definition statements and PDF codebooks.1999-07-16 Part 37, Appellate Court Data, 1997, and Part 38, Trial Court Data, 1997, have been added to the data collection, along with corresponding SAS and SPSS data definition statements and PDF codebooks. Funding insitution(s): State Justice Institute (SJI-91-N-007-001-1). United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. The Court Statistics Project Web page is: http://www.ncsconline.org/D_Research/csp/CSP_Main_Page.html.A user guide containing court codes and variable descriptions for the 1987 data and the codebooks for the 1995-2001 data are provided as Portable Document Format (PDF) files, and the codebooks for the 1988-1992 data are available in both ASCII text and PDF versions.

IntroductionA required step for presenting results of clinical studies is the declaration of participants demographic and baseline characteristics as claimed by the FDAAA 801. The common workflow to accomplish this task is to export the clinical data from the used electronic data capture system and import it into statistical software like SAS software or IBM SPSS. This software requires trained users, who have to implement the analysis individually for each item. These expenditures may become an obstacle for small studies. Objective of this work is to design, implement and evaluate an open source application, called ODM Data Analysis, for the semi-automatic analysis of clinical study data.MethodsThe system requires clinical data in the CDISC Operational Data Model format. After uploading the file, its syntax and data type conformity of the collected data is validated. The completeness of the study data is determined and basic statistics, including illustrative charts for each item, are generated. Datasets from four clinical studies have been used to evaluate the application’s performance and functionality.ResultsThe system is implemented as an open source web application (available at https://odmanalysis.uni-muenster.de) and also provided as Docker image which enables an easy distribution and installation on local systems. Study data is only stored in the application as long as the calculations are performed which is compliant with data protection endeavors. Analysis times are below half an hour, even for larger studies with over 6000 subjects.DiscussionMedical experts have ensured the usefulness of this application to grant an overview of their collected study data for monitoring purposes and to generate descriptive statistics without further user interaction. The semi-automatic analysis has its limitations and cannot replace the complex analysis of statisticians, but it can be used as a starting point for their examination and reporting.

Abstract (en): This study is part of a time-series collection of national surveys fielded continuously since 1952. The election studies are designed to present data on Americans' social backgrounds, enduring political predispositions, social and political values, perceptions and evaluations of groups and candidates, opinions on questions of public policy, and participation in political life. A Black supplement of 263 respondents, who were asked the same questions that were administered to the national cross-section sample, is included with the national cross-section of 1,571 respondents. In addition to the usual content, the study contains data on opinions about the Supreme Court, political knowledge, and further information concerning racial issues. Voter validation data have been included as an integral part of the election study, providing objective information from registration and voting records or from respondents' past voting behavior. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. United States citizens of voting age living in private households in the continental United States. A representative cross-section sample, consisting of 1,571 respondents, plus a Black supplement sample of 263 respondents. 2015-11-10 The study metadata was updated.1999-12-14 The data for this study are now available in SAS transport and SPSS export formats, in addition to the ASCII data file. Variables in the dataset have been renumbered to the following format: 2-digit (or 2-character) year prefix + 4 digits + [optional] 1-character suffix. Dataset ID and version variables have also been added. In addition, SAS and SPSS data definition statements have been created for this collection, and the data collection instruments are now available as a PDF file. face-to-face interview, telephone interviewThe SAS transport file was created using the SAS CPORT procedure.

This is a special file prepared by the Economic Research Service of the U.S. Department of Agriculture. This file was donated to CISER by Mark Lancelle, Department of Rural Sociology, Cornell, in 1984. The file was received as an SPSS file. It was converted to an SAS system file. The only documentation for this file is the SAS Contents Listing. According to that listing, this file contains county level data for various time periods between 1960 and 1980. The Source Statements indicate that the file contains data from the Bureau of Economic Analysis (BEA) Personal Income and Employment series. No such variables can be found in the SAS dataset.

SAS Opposition Exam Dataset

This dataset contains questions and answers from all the exams of the SAS (Servicio Andaluz de Salud) public job offers. The questions and answers are sourced from the official webpage of the Andalusian Health Service here.

  Dataset Information

Statement: The question in the exam. Answers: The possible answers for the question. Real Answer: The correct answer for the question. Theme: The topic or subject of the question.

  Dataset… See the full description on the dataset page: https://huggingface.co/datasets/SASLeaderboard/sas_opposition_exam_data.

Abstract (en): Roll call voting records for both chambers of the United States Congress through the second session of the 105th Congress are presented in this data collection. Each data file in the collection contains information for one chamber of a single Congress. The units of analysis in each part are the individual members of Congress. Each record contains a member's voting action on every roll call vote taken during that Congress, along with variables that identify the member (e.g., name, party, state, district, uniform ICPSR member number, and most recent means of attaining office). In addition, the codebook provides descriptive information for each roll call, including the date of the vote, outcome in terms of nays and yeas, name of initiator, the relevant bill or resolution number, and a synopsis of the issue. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. All roll call votes in the United States Congress. 2010-05-06 Data for the 105th Congress, House, and Senate (Parts 209-210), have been added to this collection, along with the standard ICPSR full product suite of files.2004-06-17 Variables were added to Part 110, Senate (55th Congress), and data within certain variables were corrected. SAS and SPSS data definition statements and the codebook have been modified to reflect these changes.2001-08-24 Logical record length data for the 8th session of the Senate, Part 16, is being made available along with SAS and SPSS data definition statements. The codebook has been modified to reflect these changes.1998-12-17 Data for the 104th Congress, House and Senate (Parts 207-208), have been added to this collection, along with corresponding machine-readable documentation and SAS and SPSS data definition statements.1997-02-24 Data for the 102nd and 103rd Congresses, House, and Senate (Parts 203-206) have been added to this collection, along with corresponding machine-readable documentation and SAS and SPSS data definition statements. The technical format has been standardized for all Congresses. Each file contains data for one chamber of a single Congress.

Abstract (en): This is the seventh in a series of surveys conducted by the Bureau of the Census. It contains information on state and local public residential facilities operated by the juvenile justice system during the fiscal year 1982. Each data record is classified into one of six categories: (1) detention center, (2) shelter, (3) reception or diagnostic center, (4) training school, (5) ranch, forestry camp, or farm, and (6) halfway house or group home. Data include state, county, and city identification, level of government responsible for the facility, type of agency, agency identification, resident population by sex, age range, detention status, and offense, and admissions and departures of population. Also included in the data are average length of stay, staffing expenditures, capacity of the facility, and programs and services available. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Created online analysis version with question text.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Juvenile detention and correctional facilities operated by state or local governments in the United States in 1982 and 1983. 2007-11-28 Data file was updated to include ready-to-go files and the ASCII codebook was converted to PDF format.2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.1997-02-25 SAS data definition statements are now available for this collection and the SPSS data definition statements were updated. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Office of Juvenile Justice and Delinquency Prevention. Conducted by the United States Department of Commerce, Bureau of the Census

Title of program: EQSYSTM Catalogue Id: AAQX_v1_0

Nature of problem This program is designed to operate on a system of equations, making user-specified substitutions and returning for each expression its partial derivatives with respect to a list of specified variables. The output expressions for the derivatives of each input expression, in the form of statements directly usable in other programs, are organized into an array with subscripts corresponding to the variables by which it was differentiated. Output in either PL/1, Fortran, or SAS syntax is available a ...

Versions of this program held in the CPC repository in Mendeley Data AAQX_v1_0; EQSYSTM; 10.1016/0010-4655(81)90085-0

This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)

🇫🇷 프랑스

Abstract (en): The 1975 census includes juvenile detention and correctional facilities that were operated by state or local governments in November, 1975, and had been in operation at least a month prior to June 30, 1975. There is one record for each juvenile detention facility that had a population of at least 50 percent juveniles. Each record is classified into one of six categories: detention centers or shelters, reception or diagnostic centers, training schools, ranches, forestry camps and farms, and halfway houses and group homes. Data include state, county, and city identification, level of government responsible for the facility, type of agency, agency identification, resident population by sex, age range, detention status, and offense, admissions and departures of population, average length of stay, staffing and expenditures, age and capacity of the facility, and programs and services available. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Created online analysis version with question text.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Juvenile detention and correctional facilities operated by state or local governments. 2008-01-29 The data file was updated to include ready-to-go files and the ASCII codebook was converted to PDF format.2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.1997-02-25 SAS data definition statements are now available for this collection and the SPSS data definition statements were updated. Conducted by the United States Department of Commerce, Bureau of the Census.

Les plans de prévention des risques (PPR) constituent l'instrument essentiel de l'État en matière de prévention des risques. Leur objectif est le contrôle du développement dans les zones exposées à un risque.L'élaboration d'un plan de prévention des risques génère une série de données géographiques organisée en plusieurs jeux de données. Ce jeu de données décrit les zones réglementées du plan une fois approuvé. Les règlements des PPR distinguent généralement les « zones d'interdiction de construire », dites « zones rouges », lorsque le niveau d'aléa est fort et que la règle générale est l'interdiction de construire ; les « zones soumises à prescriptions », dites « zones bleues » lorsque le niveau d'aléa est moyen et que les projets sont soumis à des prescriptions adaptées au type d'enjeu et les zones non directement exposées aux risques mais soumises à interdictions ou prescriptions

L'origine du risque caractérise l'entité du monde réel qui, par sa présence, représente un risque potentiel. Cette origine peut être caractérisée par un nom et, dans certains cas, un objet géographique localisant l'entité réelle à l'origine du risque. La localisation de l'entité et la connaissance du phénomène dangereux servent à définir les bassins de risques, les zones exposées aux risques qui fondent le PPR. Dans les PPRT, elle représente l'enceinte de la ou des installations classées pour la protection de l'environnement (ICPE) à l'origine du risque analysé et traité par le PPR. Dans la méthodologie PPRT, elle est qualifiée de zone grise.

Ce jeu de données contient les périmètres de délimitation aux différents stades de l'élaboration du PPRT. Ces périmètres ont comme caractéristique d'être la conséquence d'un acte officiel et de produire leurs effets à compter d'une date définie. Il s'agit du : - périmètre prescrit figurant dans l'arrêté de prescription d'un PPR (naturel ou technologique) ; - périmètre d'exposition aux risques qui correspond au périmètre réglementé par le PPR approuvé. Ce périmètre approuvé vaut servitude d'utilité publique (PM3 pour les PPRT) ; - périmètre d'étude qui correspond à l'enveloppe dans laquelle ont été étudiés les aléas.

Les plans de prévention des risques (PPR) ont été institués par la loi du 2 février 1995 relative au renforcement de la protection de l'environnement. Ils constituent l'instrument essentiel de l'État en matière de prévention des risques. Leur objectif est le contrôle du développement dans les zones exposées à un risque majeur. Les PPR sont approuvés par les préfets et généralement réalisés par les directions départementales des territoires (DDT). Ces plans réglementent l'occupation du sol ou son usage par des interdictions de construire ou des prescriptions sur les bâtiments existants ou futurs (dispositions constructives, travaux de réduction de la vulnérabilité, restrictions d'usage ou de pratiques agricoles...). Ces plans peuvent être en cours d'élaboration (prescrit), appliqués par anticipation ou approuvés. Le dossier de PPR contient une note de présentation, un plan de zonage réglementaire et un règlement. Peuvent être joints d'autres documents graphiques utiles à la compréhension de la démarche (aléas, enjeux...). Chaque PPR est repéré par un polygone qui correspond à l'ensemble de communes concernées du périmètre de prescription lorsqu'il est à l'état prescrit ; et l'enveloppe des zones réglementées lorsqu'il est à l'état approuvé. Cette table géographique permet de cartographier les PPRN ou PPRT existant sur le département.

Abstract (en): The 1979 Juvenile Detention and Correctional Facility Census is the sixth in a series of surveys of state and local public residential facilities in the juvenile justice system. There is one record for each juvenile detention facility that had a population of at least 50 percent juveniles. Each record is classified into one of six categories: detention centers or shelters, reception or diagnostic centers, training schools, ranches, forestry camps and farms, and halfway houses and group homes. Data include state, county, and city identification, level of government responsible for the facility, type of agency, agency identification, resident population by sex, age range, detention status, and offense, admissions and departures of population, average length of stay, staffing and expenditures, age and capacity of the facility, and programs and services available. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Created online analysis version with question text.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Juvenile detention and correctional facilities operated by state or local governments. 2007-12-11 The data file was updated to include ready-to-go files and the ASCII codebook was converted to PDF format.2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.1997-02-25 SAS data definition statements are now available for this collection and the SPSS data definition statements have been updated. Conducted by the United States Department of Commerce, Bureau of the Census

De manière générale, les enjeux sont les personnes, biens, activités, éléments de patrimoine culturel ou environnemental, menacés par un aléa et susceptibles d'être affectés ou endommagés par celui-ci. La sensibilité d'un enjeu à un aléa est nommée « vulnérabilité ». Cette classe d'objet regroupe tous les enjeux qui ont été pris en compte dans l'étude du PPR. Un enjeu est un objet daté dont la prise en compte est fonction de l'objet du PPR et de sa vulnérabilité aux aléas étudiés. Un enjeu de PPR peut donc être pris en compte (ou pas) selon le ou les types d'aléa traités. Ces éléments constituent le socle de connaissance de l'occupation du sol nécessaire à l'élaboration du PPR, dans la zone d'étude ou à proximité de celle-ci, à la date de l'analyse des enjeux. Les données d'enjeux représentent une photographie (figée et non exhaustive) des biens et des personnes exposés aux aléas au moment de l'élaboration du plan de prévention des risques. Ces données ne sont pas mises à jour après l'approbation du PPR. En pratique elles ne sont plus utilisées : les enjeux sont recalculés en tant que de besoin avec des sources de données à jour.

De manière générale, les enjeux sont les personnes, biens, activités, éléments de patrimoine culturel ou environnemental, menacés par un aléa et susceptibles d'être affectés ou endommagés par celui-ci. La sensibilité d'un enjeu à un aléa est nommée « vulnérabilité ». Cette classe d'objet regroupe tous les enjeux qui ont été pris en compte dans l'étude du PPR. Un enjeu est un objet daté dont la prise en compte est fonction de l'objet du PPR et de sa vulnérabilité aux aléas étudiés. Un enjeu de PPR peut donc être pris en compte (ou pas) selon le ou les types d'aléa traités. Ces éléments constituent le socle de connaissance de l'occupation du sol nécessaire à l'élaboration du PPR, dans la zone d'étude ou à proximité de celle-ci, à la date de l'analyse des enjeux. Les données d'enjeux représentent une photographie (figée et non exhaustive) des biens et des personnes exposés aux aléas au moment de l'élaboration du plan de prévention des risques. Ces données ne sont pas mises à jour après l'approbation du PPR. En pratique elles ne sont plus utilisées : les enjeux sont recalculés en tant que de besoin avec des sources de données à jour.

Abstract (en): This survey is the first broad-based, systematic examination of the nature of civil litigation in state general jurisdiction trial courts. Data collection was carried out by the National Center for State Courts with assistance from the National Association of Criminal Justice Planners and the United States Bureau of the Census. The data collection produced two datasets. Part 1, Tort, Contract, and Real Property Rights Data, is a merged sample of approximately 30,000 tort, contract, and real property rights cases disposed during the 12-month period ending June 30, 1992. Part 2, Civil Jury Cases Data, is a sample of about 6,500 jury trial cases disposed over the same time period. Data collected include information about litigants, case type, disposition type, processing time, case outcome, and award amounts for civil jury cases. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Checked for undocumented or out-of-range codes.. Forty-five jurisdictions chosen to represent the 75 most populous counties in the nation. The sample for this study was designed and selected by the United States Bureau of the Census. It was a two-stage stratified sample with 45 of the 75 most populous counties selected at the first stage. The top 75 counties account for about 37 percent of the United States population and about half of all civil filings. The 75 counties were divided into four strata based on aggregate civil disposition data for 1990 obtained through telephone interviews with court staffs in the general jurisdiction trial courts. The sample consisted of tort, contract, and real property rights cases disposed between July 1, 1991, and June 30, 1992. 2011-11-02 All parts are being moved to restricted access and will be available only using the restricted access procedures.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.2004-06-01 The data have been updated by the principal investigator to include replicate weights and a few other variables. The codebook and SAS and SPSS data definition statements have been revised to reflect these changes.2001-03-26 The data have been updated by the principal investigator to include replicate weights. The codebook and SAS and SPSS data definition statements have been revised to reflect these changes.2001-03-26 The data had been updated by the principal investigator to include replicate weights. The codebook and SAS and SPSS data definition statements had been revised to reflect these changes.1997-07-29 The codebook had been revised to correct errors documenting both data files. Column location (and width) of variable WGHT "TOTAL WEIGHT" was incorrectly shown as 10.4 for Part 1, Tort, Contract, and Real Property Data. It was accurately shown in the data definition statements as 9.4. Variables listed after WGHT were inaccurately reported one column off in the codebook. Similarly, column location (and width) of variable WGHT "TOTAL WEIGHT" was incorrectly shown as 10.2 for Part 2, Civil Jury Data. It was accurately shown in the data definition statements as 9.2. Variables listed after WGHT were inaccurately reported one column off in the codebook. Fundi...