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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.
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Abstract (en): The purpose of this study was to provide an in-depth look at rapes and attempted rapes in the United States. Part 1 of the collection offers data on rape victims and contains variables regarding the characteristics of the crime, such as the setting, the relationship between the victim and offender, the likelihood of injury, and the reasons why rape is not reported to police. Part 2 contains data on a control group of females who were victims of no crime or of crimes other than rape. The information contained is similar to that found in Part 1. All persons in the United States. A stratified multistage cluster sample. 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.2000-09-29 SPSS data definition statements were updated and SAS data definition statements were added to this collection. Also, the codebooks and data collection instrument are now available in two PDF files. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. The codebooks and data collection instrument for this collection are provided by ICPSR as Portable Document Format (PDF) files. 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 Website.This collection of rape cases was taken from the NATIONAL CRIME SURVEY: NATIONAL SAMPLE, 1973-1983 (ICPSR 7635). The definition of rape in the survey includes attempts that involve a verbal threat of rape only. The data in Part 1 were collected at the incident level. Part 2 data were collected at the person level, with information for up to four incidents per person.
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Abstract (en): The purpose of this data collection was twofold. The survey was designed to ascertain the attitudes of attorneys regarding new techniques for obtaining clients, such as media advertising and solicitation, as well as their attitudes toward pro bono service, and to test whether attitudinal differences are related to demographic or organizational characteristics of the profession. A second purpose of the study was to serve as a screener to identify a group of attorneys in solo and small-firm practice who use new types of business-getting techniques. Variables in the collection include respondent attitudes toward advertising, unions, and pro bono cases, information on type of firm, number of attorneys in the firm, type of legal practice and legal specialty, and demographic information such as religious affiliation, membership in local clubs or associations, college attended, marital status, number of children, income, number of years practicing law, and parents' occupations. Lawyers in the metropolitan New York area. Stratified random sample. 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.2001-02-16 The card image data have been converted to logical record length, and SAS and SPSS data definition statements were prepared for this collection. In addition, the codebook and data collection instruments are available as a PDF file. Funding insitution(s): National Science Foundation. Law and Social Sciences Program (SES-89-10544). Produced by Schulman, Ronca and Bucuvalas, Inc., New York, NY, 1990.
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Abstract (en): This study was designed to measure the effects of family background and developmental characteristics on school achievement and delinquency within a "high risk" sample of Black youths. The study includes variables describing the mother and the child. Mother-related variables assess prenatal health, pregnancy and delivery complications, and socioeconomic status. Child-related variables focus on the child at age 7 and include place in birth order, physical development, family constellation, socioeconomic status, verbal and spatial intelligence, and number of offenses. Subjects were selected from a sample of 2,958 Black children whose mothers participated in the Collaborative Perinatal Project at Pennsylvania Hospital between 1959 and 1962. 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.1998-12-17 Hard-coded periods in the original data were replaced by nines. This resulted in a longer record length for the data file. Also, SAS and SPSS data definition statements were added to the collection, and the original codebook was converted to a PDF file. Funding insitution(s): United States Department of Justice. Office of Justice Programs. National Institute of Justice (81-IJ-CX-0086(S1)). The 200 variables in this data collection were used in a government-funded study. The additional variables shown in the questionnaire were not archived.Producer: Collaborative Perinatal Project and the University of Pennsylvania, Center for Studies in Criminology and Criminal Law, Philadelphia, PA, 1969.
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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.