6 datasets found
  1. f

    Supplement 1. MATLAB and SAS code necessary to replicate the simulation...

    • wiley.figshare.com
    • datasetcatalog.nlm.nih.gov
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    Updated Jun 4, 2023
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    Jeffrey A. Evans; Adam S. Davis; S. Raghu; Ashok Ragavendran; Douglas A. Landis; Douglas W. Schemske (2023). Supplement 1. MATLAB and SAS code necessary to replicate the simulation models and other demographic analyses presented in the paper. [Dataset]. http://doi.org/10.6084/m9.figshare.3517478.v1
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    Wiley
    Authors
    Jeffrey A. Evans; Adam S. Davis; S. Raghu; Ashok Ragavendran; Douglas A. Landis; Douglas W. Schemske
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    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
    
  2. Federal Court Cases: Integrated Data Base, 1970-2000 - Version 6

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    Updated May 22, 2012
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    Federal Judicial Center (2012). Federal Court Cases: Integrated Data Base, 1970-2000 - Version 6 [Dataset]. http://doi.org/10.3886/ICPSR08429.v6
    Explore at:
    Dataset updated
    May 22, 2012
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    GESIS search
    Authors
    Federal Judicial Center
    License

    https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de456864https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de456864

    Description

    Abstract (en): The purpose of this data collection is to provide an official public record of the business of the federal courts. The data originate from 94 district and 12 appellate court offices throughout the United States. Information was obtained at two points in the life of a case: filing and termination. The termination data contain information on both filing and terminations, while the pending data contain only filing information. For the appellate and civil data, the unit of analysis is a single case. The unit of analysis for the criminal data is a single defendant. 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.. All federal court cases, 1970-2000. 2012-05-22 All parts are being moved to restricted access and will be available only using the restricted access procedures.2005-04-29 The codebook files in Parts 57, 94, and 95 have undergone minor edits and been incorporated with their respective datasets. The SAS files in Parts 90, 91, 227, and 229-231 have undergone minor edits and been incorporated with their respective datasets. The SPSS files in Parts 92, 93, 226, and 228 have undergone minor edits and been incorporated with their respective datasets. Parts 15-28, 34-56, 61-66, 70-75, 82-89, 96-105, 107, 108, and 115-121 have had identifying information removed from the public use file and restricted data files that still include that information have been created. These parts have had their SPSS, SAS, and PDF codebook files updated to reflect the change. The data, SPSS, and SAS files for Parts 34-37 have been updated from OSIRIS to LRECL format. The codebook files for Parts 109-113 have been updated. The case counts for Parts 61-66 and 71-75 have been corrected in the study description. The LRECL for Parts 82, 100-102, and 105 have been corrected in the study description.2003-04-03 A codebook was created for Part 105, Civil Pending, 1997. Parts 232-233, SAS and SPSS setup files for Civil Data, 1996-1997, were removed from the collection since the civil data files for those years have corresponding SAS and SPSS setup files.2002-04-25 Criminal data files for Parts 109-113 have all been replaced with updated files. The updated files contain Criminal Terminations and Criminal Pending data in one file for the years 1996-2000. Part 114, originally Criminal Pending 2000, has been removed from the study and the 2000 pending data are now included in Part 113.2001-08-13 The following data files were revised to include plaintiff and defendant information: Appellate Terminations, 2000 (Part 107), Appellate Pending, 2000 (Part 108), Civil Terminations, 1996-2000 (Parts 103, 104, 115-117), and Civil Pending, 2000 (Part 118). The corresponding SAS and SPSS setup files and PDF codebooks have also been edited.2001-04-12 Criminal Terminations (Parts 109-113) data for 1996-2000 and Criminal Pending (Part 114) data for 2000 have been added to the data collection, along with corresponding SAS and SPSS setup files and PDF codebooks.2001-03-26 Appellate Terminations (Part 107) and Appellate Pending (Part 108) data for 2000 have been added to the data collection, along with corresponding SAS and SPSS setup files and PDF codebooks.1997-07-16 The data for 18 of the Criminal Data files were matched to the wrong part numbers and names, and now have been corrected. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. (1) Several, but not all, of these record counts include a final blank record. Researchers may want to detect this occurrence and eliminate this record before analysis. (2) In July 1984, a major change in the recording and disposition of an appeal occurred, and several data fields dealing with disposition were restructured or replaced. The new structure more clearly delineates mutually exclusive dispositions. Researchers must exercise care in using these fields for comparisons. (3) In 1992, the Administrative Office of the United States Courts changed the reporting period for statistical data. Up to 1992, the reporting period...

  3. Supplement 1. Detailed description of how the methods are applied to data,...

    • wiley.figshare.com
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    Updated Jun 5, 2023
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    John Connolly; Marc W. Cadotte; Caroline Brophy; Áine Dooley; John Finn; Laura Kirwan; Christiane Roscher; Alexandra Weigelt (2023). Supplement 1. Detailed description of how the methods are applied to data, including SAS and R code and data from two experiments. [Dataset]. http://doi.org/10.6084/m9.figshare.3551508.v1
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    Wileyhttps://www.wiley.com/
    Authors
    John Connolly; Marc W. Cadotte; Caroline Brophy; Áine Dooley; John Finn; Laura Kirwan; Christiane Roscher; Alexandra Weigelt
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    File List

     Jena_dataset.pdf
    
     Worked example of model fitting for the Jena_dataset.pdf 
    
    
     Jena_dataset.sas
    
     SAS code for analysis of Jena_dataset.sas 
    
    
     Jena_dataset.r
    
     R code for analysis of Jena_dataset.r 
    
    
     Jena_data.csv
    
     Jena data 
    
    
     Ireland_site_biodepth.csv
    
     Data for Ireland_site_Biodepth.csv 
    

    Description The supplements are designed to assist the reader to implement the methods using the statistical packages SAS and R. The first supplement (Worked example of model fitting for theJena_dataset.pdf) provides a detailed description of the application and interpretation of a range of models using the Jena dataset. The second and third supplements (SAS code for analysis of Jena_dataset.sas) and (R code for analysis of Jena_dataset.r) provide SAS and R code to implement the method using the Jena dataset. The data for the two sites is provided in Jena_data.csv and Ireland_site_biodepth.csv. Hash values for supplements Jena_data.csv and Ireland_site_biodepth.csv calculated by HASHCALC: MD5 hash value for Jena_data.csv 6b86c280a15bbd4aae08b5b4c91363ee MD5 hash value for Ireland_site_biodepth.csv 9b60c32ceca9259e47d7ee42b9ae5f16

  4. State Court Statistics, 1985-2001: [United States] - Version 1

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    Updated May 7, 2021
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    National Center for State Courts (2021). State Court Statistics, 1985-2001: [United States] - Version 1 [Dataset]. http://doi.org/10.3886/ICPSR09266.v1
    Explore at:
    Dataset updated
    May 7, 2021
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    GESIS search
    Authors
    National Center for State Courts
    License

    https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de444718https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de444718

    Area covered
    United States
    Description

    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.

  5. g

    Civil Justice Survey of State Courts, 1992 - Version 2

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    Updated May 7, 2021
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    United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics (2021). Civil Justice Survey of State Courts, 1992 - Version 2 [Dataset]. http://doi.org/10.3886/ICPSR06587.v2
    Explore at:
    Dataset updated
    May 7, 2021
    Dataset provided by
    GESIS search
    ICPSR - Interuniversity Consortium for Political and Social Research
    Authors
    United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics
    License

    https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de456291https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de456291

    Description

    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...

  6. g

    Patterns of Drug Use and Their Relation to Improving Prediction of Patterns...

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    Updated May 6, 2021
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    Shannonn, Lyle W. (2021). Patterns of Drug Use and Their Relation to Improving Prediction of Patterns of Delinquency and Crime in Racine, Wisconsin, 1961-1988 - Archival Version [Dataset]. http://doi.org/10.3886/ICPSR09684
    Explore at:
    Dataset updated
    May 6, 2021
    Dataset provided by
    GESIS search
    ICPSR - Interuniversity Consortium for Political and Social Research
    Authors
    Shannonn, Lyle W.
    License

    https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de445521https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de445521

    Area covered
    Racine
    Description

    Abstract (en): This dataset presents information on the relationship between drug and alcohol use and contacts with police for persons in Racine, Wisconsin, born in 1955. The collection is part of an ongoing longitudinal study of three Racine, Wisconsin, birth cohorts: those born in 1942, 1949, and 1955. Only those born in 1955 were considered to have potential for substantial contact with drugs, and thus only the younger cohort was targeted for this collection. Data were gathered for ages 6 to 33 for the cohort members. The file contains information on the most serious offense during the juvenile and adult periods, the number of police contacts grouped by age of the cohort member, seriousness of the reason for police contact, drugs involved in the incident, the reason police gave for the person having the drugs, the reason police gave for the contact, and the neighborhood in which the juvenile was socialized. Other variables include length of residence in Racine of the cohort member, and demographic information including age, sex, and race. 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 individuals born in 1955 in Racine, Wisconsin, and those who had migrated there by the age of 6. The sample includes all individuals born in 1955 and attending school (i.e., appearing in the Racine school census records) in 1966. 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.2001-12-21 SAS and SPSS data definition statements were added to the collection and the documentation was converted into PDF format. Funding insitution(s): United States Department of Justice. Office of Justice Programs. National Institute of Justice (87-IJ-CX-0045). (1) Other datasets that are part of this ongoing study include: JUVENILE DELINQUENCY AND ADULT CRIME, 1948-1977 [RACINE, WISCONSIN]: THREE BIRTH COHORTS (ICPSR 8163), JUVENILE DELINQUENCY AND ADULT CRIME, 1948-1977 [RACINE, WISCONSIN]: CITY ECOLOGICAL DATA (ICPSR 8164), and SANCTIONS IN THE JUSTICE SYSTEM, 1942-1977: THE EFFECTS ON OFFENDERS IN RACINE, WISCONSIN (ICPSR 8530). (2) Users should note that police contact, rather than the individual, is the unit of analysis in this collection, and that each contact is a record. Therefore, there can be multiple records (contacts) per individual. Each individual is identified by the variable UID (Unique Identification Number). (3) The codebook is provided by ICPSR as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.

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Jeffrey A. Evans; Adam S. Davis; S. Raghu; Ashok Ragavendran; Douglas A. Landis; Douglas W. Schemske (2023). Supplement 1. MATLAB and SAS code necessary to replicate the simulation models and other demographic analyses presented in the paper. [Dataset]. http://doi.org/10.6084/m9.figshare.3517478.v1

Supplement 1. MATLAB and SAS code necessary to replicate the simulation models and other demographic analyses presented in the paper.

Related Article
Explore at:
htmlAvailable download formats
Dataset updated
Jun 4, 2023
Dataset provided by
Wiley
Authors
Jeffrey A. Evans; Adam S. Davis; S. Raghu; Ashok Ragavendran; Douglas A. Landis; Douglas W. Schemske
License

CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically

Description

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
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