3 datasets found
  1. f

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

    • datasetcatalog.nlm.nih.gov
    • wiley.figshare.com
    Updated Aug 4, 2016
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    Davis, Adam S.; Landis, Douglas A.; Schemske, Douglas W.; Raghu, S.; Evans, Jeffrey A.; Ragavendran, Ashok (2016). Supplement 1. MATLAB and SAS code necessary to replicate the simulation models and other demographic analyses presented in the paper. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001528932
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    Dataset updated
    Aug 4, 2016
    Authors
    Davis, Adam S.; Landis, Douglas A.; Schemske, Douglas W.; Raghu, S.; Evans, Jeffrey A.; Ragavendran, Ashok
    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. d

    Data from: School Health Center Healthy Adolescent Relationship Program...

    • datasets.ai
    • icpsr.umich.edu
    • +1more
    0
    Updated Aug 18, 2021
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    Department of Justice (2021). School Health Center Healthy Adolescent Relationship Program (SHARP) Integrating Prevention and Intervention in Northern California School Health Centers, 2012-2013 [Dataset]. https://datasets.ai/datasets/school-health-center-healthy-adolescent-relationship-program-sharp-integrating-preven-2012-19d85
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    0Available download formats
    Dataset updated
    Aug 18, 2021
    Dataset authored and provided by
    Department of Justice
    Description

    These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

    The School Health Center Healthy Adolescent Relationship Program (SHARP) was a school health center (SHC) provider-delivered multi-level intervention to reduce adolescent relationship abuse (ARA) among adolescents ages 14-19 seeking care in SHCs. This study tested the effectiveness of a brief relationship abuse education and counseling intervention in SHCs.

    The SHARP intervention consisted of three levels of integrated intervention:

    A brief clinical intervention on healthy and unhealthy relationships for SHC (cisgender and transgender) male and female patients delivered by SHC providers during all clinic visits (evaluated via client pre- and post-surveys and chart review) Development of an ARA-informed SHC staff and clinic environment (evaluated via provider pre and post-training surveys and interviews) SHC-based youth-led outreach activities within the school to promote healthy relationships and improve student safety (evaluated by focus groups with youth leaders and measures of school climate)

    The collection consists of:

    3 SAS data files

    sharp_abuse_data_archive.sas7bdat (n=1,011; 272 variables) sharp_blt2exit_long_data_archive.sas7bdat (n=1,949; 259 variables) sharp_chart_data_archive_icpsr.sas7bdat (n=936; 24 variables)

    2 Stata data files

    SHARP_Provider Immediate Post_0829 and 0905 training_final-ICPSR.dta (n=38; 21 variables) SHARP_Provider Pre and Followup_final.dta-ICPSR.dta (n=66; 102 variables)

    5 SAS syntax files

    NIJ SHARP - Analyses.sas NIJ SHARP - DataMgmt_Final.sas NIJ SHARP - Formats.sas SHARP - Chart Extraction Data-MASKED.sas SHARP - Chart Extraction Formats.sas

    3 Stata syntax files

    code-for-SHARP-dating-violence-analyses-deidentified-MASKED.do SHARP_Provider Data to Archive-MASKED.do SHARP-analyses-deidentified-MASKED.do

    3 PI provided codebooks

    SHARP Codebook_Client Chart Data.xlsx (1 worksheet) SHARP Codebook_Client Survey Data.xlsx (3 worksheets) SHARP Codebook_Provider Survey Data.xlsx (1 worksheet)

    For confidentiality reasons, qualitative data from focus groups are not currently available. Focus groups were conducted with each student outreach team following the conclusion of data collection. Discussions focused on awareness about ARA, the school-wide campaign, using the SHC as a resource, and what else can be done to prevent ARA in schools.

  3. J

    Data associated with: Study to Understand Fall Reduction and Vitamin D in...

    • archive.data.jhu.edu
    Updated May 28, 2025
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    Lawrence J. Appel; Erin D. Michos; Edgar R. Miller III (2025). Data associated with: Study to Understand Fall Reduction and Vitamin D in You (STURDY) randomized clinical trial [Dataset]. http://doi.org/10.7281/T1/PXEROL
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 28, 2025
    Dataset provided by
    Johns Hopkins Research Data Repository
    Authors
    Lawrence J. Appel; Erin D. Michos; Edgar R. Miller III
    License

    https://archive.data.jhu.edu/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.7281/T1/PXEROLhttps://archive.data.jhu.edu/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.7281/T1/PXEROL

    Dataset funded by
    Johns Hopkins Institute for Clinical and Translation Research
    National Institutes of Health
    Mid-Atlantic Nutrition Obesity Research Center
    Description

    This is the limited access database for the Study to Understand Fall Reduction and Vitamin D in You (STURDY) randomized response-adaptive clinical trial. The database includes baseline, treatment and post randomization data. This Database includes a set of files pertaining to the full study population (688 randomized participants plus screenees who were not randomized) and a set of files pertaining to the burn-in cohort (the 406 participants randomized prior to the first adjustment of the randomization probabilities). The Database also includes files that support the analyses included in the primary outcome paper published by the Annals of Internal Medicine (2021;174:(2):145-156). Each data file in the Database corresponds to a specific data collection form or type of data. This documentation notebook includes a SAS PROC CONTENTS listing for each SAS file and a copy of the relevant form if applicable. Each variable on each SAS data file has an associated SAS label. Several STURDY documents, including the final versions of the screening and trial consent statements, the Protocol, and the Manual of Procedures, are included with this documentation notebook to assist with understanding and navigation of STURDY data. Notes on analysis questions and issues are also included, as is a list of STURDY publications.

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Davis, Adam S.; Landis, Douglas A.; Schemske, Douglas W.; Raghu, S.; Evans, Jeffrey A.; Ragavendran, Ashok (2016). Supplement 1. MATLAB and SAS code necessary to replicate the simulation models and other demographic analyses presented in the paper. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001528932

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

Explore at:
Dataset updated
Aug 4, 2016
Authors
Davis, Adam S.; Landis, Douglas A.; Schemske, Douglas W.; Raghu, S.; Evans, Jeffrey A.; Ragavendran, Ashok
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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