Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.

These two syntax files were used to convert the SPSS data output from the Qualtrics survey tool into the 17 cleansed and anonymised RAAAP-2 datasets form the 2019 international survey of research managers and administrators. The first creates and interim cleansed and anonymised datafile, the latter splits these into separate datasets to ensure anonymisation. Errata (16/6/23): v13 of the main Data Cleansing file has an error (two variables were missing value labels). This file has now been replaced with v14, and the Main Dataset has also been updated with the new data.

This dataset contains a SPSS (v23) syntax file (.sps) and the relating graph template (.sgt) that can be used to create anonymized graphs of spinal motion in the transversal plane for a Standardized Gait Cycle. All sections are commented within the script. The algebraic sign of the pelvis gets corrected. It required correction since the pelvis is in alignment of surface rotation, and in order to be in parallel with the vertebral body’s rotation it has to be reversed. So, if the surface above the spinous process runs to the right, this implies a rotation to left of the vertebral body beneath.

This dataset consists of three data folders including all related documents of the online survey conducted within the NESP 3.2.3 project (Tropical Water Quality Hub) and a survey format document representing how the survey was designed. Apart from participants’ demographic information, the survey consists of three sections: conjoint analysis, picture rating and open question. Correspondent outcome of these three sections are downloaded from Qualtrics website and used for three different data analysis processes.

Related data to the first section “conjoint analysis” is saved in the Conjoint analysis folder which contains two sub-folders. The first one includes a plan file of SAV. Format representing the design suggestion by SPSS orthogonal analysis for testing beauty factors and 9 photoshoped pictures used in the survey. The second (i.e. Final results) contains 1 SAV. file named “data1” which is the imported results of conjoint analysis section in SPSS, 1 SPS. file named “Syntax1” representing the code used to run conjoint analysis, 2 SAV. files as the output of conjoint analysis by SPSS, and 1 SPV file named “Final output” showing results of further data analysis by SPSS on the basis of utility and importance data.

Related data to the second section “Picture rating” is saved into Picture rating folder including two subfolders. One subfolder contains 2500 pictures of Great Barrier Reef used in the rating survey section. These pictures are organised by named and stored in two folders named as “Survey Part 1” and “Survey Part 2” which are correspondent with two parts of the rating survey sections. The other subfolder “Rating results” consist of one XLSX. file representing survey results downloaded from Qualtric website.

Finally, related data to the open question is saved in “Open question” folder. It contains one csv. file and one PDF. file recording participants’ answers to the open question as well as one PNG. file representing a screenshot of Leximancer analysis outcome.

Methods: This dataset resulted from the input and output of an online survey regarding how people assess the beauty of Great Barrier Reef. This survey was designed for multiple purposes including three main sections: (1) conjoint analysis (ranking 9 photoshopped pictures to determine the relative importance weights of beauty attributes), (2) picture rating (2500 pictures to be rated) and (3) open question on the factors that makes a picture of the Great Barrier Reef beautiful in participants’ opinion (determining beauty factors from tourist perspective). Pictures used in this survey were downloaded from public sources such as websites of the Tourism and Events Queensland and Tropical Tourism North Queensland as well as tourist sharing sources (i.e. Flickr). Flickr pictures were downloaded using the key words “Great Barrier Reef”. About 10,000 pictures were downloaded in August and September 2017. 2,500 pictures were then selected based on several research criteria: (1) underwater pictures of GBR, (2) without humans, (3) viewed from 1-2 metres from objects and (4) of high resolution.

The survey was created on Qualtrics website and launched on 4th October 2017 using Qualtrics survey service. Each participant rated 50 pictures randomly selected from the pool of 2500 survey pictures. 772 survey completions were recorded and 705 questionnaires were eligible for data analysis after filtering unqualified questionnaires. Conjoint analysis data was imported to IBM SPSS using SAV. format and the output was saved using SPV. format. Automatic aesthetic rating of 2500 Great Barrier Reef pictures –all these pictures are rated (1 – 10 scale) by at least 10 participants and this dataset was saved in a XLSX. file which is used to train and test an Artificial Intelligence (AI)-based system recognising and assessing the beauty of natural scenes. Answers of the open-question were saved in a XLSX. file and a PDF. file to be employed for theme analysis by Leximancer software.

Further information can be found in the following publication: Becken, S., Connolly R., Stantic B., Scott N., Mandal R., Le D., (2018), Monitoring aesthetic value of the Great Barrier Reef by using innovative technologies and artificial intelligence, Griffith Institute for Tourism Research Report No 15.

Format: The Online survey dataset includes one PDF file representing the survey format with all sections and questions. It also contains three subfolders, each has multiple files. The subfolder of Conjoint analysis contains an image of the 9 JPG. Pictures, 1 SAV. format file for the Orthoplan subroutine outcome and 5 outcome documents (i.e. 3 SAV. files, 1 SPS. file, 1 SPV. file). The subfolder of Picture rating contains a capture of the 2500 pictures used in the survey, 1 excel file for rating results. The subfolder of Open question includes 1 CSV. file, 1 PDF. file representing participants’ answers and one PNG. file for the analysis outcome.

Data Dictionary:

Card 1: Picture design option number 1 suggested by SPSS orthogonal analysis. Importance value: The relative importance weight of each beauty attribute calculated by SPSS conjoint analysis. Utility: Score reflecting influential valence and degree of each beauty attribute on beauty score. Syntax: Code used to run conjoint analysis by SPSS Leximancer: Specialised software for qualitative data analysis. Concept map: A map showing the relationship between concepts identified Q1_1: Beauty score of the picture Q1_1 by the correspondent participant (i.e. survey part 1) Q2.1_1: Beauty score of the picture Q2.1_1 by the correspondent participant (i.e. survey part 2) Conjoint _1: Ranking of the picture 1 designed for conjoint analysis by the correspondent participant

References: Becken, S., Connolly R., Stantic B., Scott N., Mandal R., Le D., (2018), Monitoring aesthetic value of the Great Barrier Reef by using innovative technologies and artificial intelligence, Griffith Institute for Tourism Research Report No 15.

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data esp3\3.2.3_Aesthetic-value-GBR

Data in SPSS formatMeasured language variables across the cultural groups, in SPSS data file format.Data.savData in CSV formatEquivalent data to the SPSS upload, in CSV format.Data.csvAnalysis syntax for SPSSSyntax used to generate the reported results using SPSS.Syntax.sps

Dataset for the study "Turning the light switch on binding: Prefrontal activity for binding and retrieval in action control", to-be-published in Journal of Cognitive Neuroscience. For further information please refer to the aforementioned paper. The aggregated behavioral data file can be analyzed by using the SPSS-Syntax and the aggregated neuro data can be analyzed by using the pipeline; both are available under "Code for: Turning the light switch on binding: Prefrontal activity for binding and retrieval in action control".:

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. This study represents the first comprehensive national assessment of law enforcement uses of and perspectives on sex offender registration and notification (SORN) systems. The two-year, mixed-method study featured collection and analysis of interview data from over two-dozen jurisdictions, and administration of a nationwide survey of law enforcement professionals. The study examined ways in which law enforcement leaders, uniformed staff, and civilian staff engaged in SORN-related duties perceive SORN's roles and functions, general effectiveness, and informational utility. Additionally, the study elicited law enforcement perspectives related to promising SORN and related sex offender management practices, perceived barriers and challenges to effectiveness, and policy reform priorities. This collection includes two SPSS data files and one SPSS syntax file: "LE Qualitative Data.sav" with 55 variables and 101 cases, "LE Quantitative Data-ICPSR.sav" with 201 variables and 1402 cases and "LE Quantitative Data Syntax.sps". Qualitative data from interviews conducted with law enorcement professionals are not available at this time.

This component contains the data and syntax code used to conduct the Exploratory Factor Analysis and compute Velicer’s minimum average partial test in sample 1

The project aimed to understand whether young adults who take care of a loved-one (young adult caregivers; YACs) differ in their perceived life balance and psychosocial functioning as compared to young adults without care responsibilities (non-YACs). In addition, this project aimed to understand how YACs evaluated a tool to support informal careg

ivers. This tool (“Caregiver Balance”; https://balans.mantelzorg.nl) is specifically designed to support informal caregivers taking care of a loved-one in the palliative phase and could potentially be adapted to meet the needs of YACs.

In this project, we collected data of 74 YACs and 246 non-YACs. Both groups completed questionnaires, and the YACs engaged in a usability test. The questionnaire data was used to compare the perceived life balance and psychological functioning between YACs and non-YACs, aged 18-25 years, and studying in the Netherlands (study 1). Furthermore, we examined the relationship between positive aspects of caregiving and relational factors, in particular, relationship quality and collaborative coping among YACs (study 2). Finally, we conducted a usability study where we interviewed YACs to understand the needs and preferences towards a supportive web-based solution (study 3).

Table: Study details and associated files

    Number
    Study Name
    Study Aim
    Study Type
    Type of data
    Associated Files


    1
    Perceived life balance among young adult students: a comparison between caregivers and non-caregivers
    Compare the perceived life balance and psychological functions among student young adult caregivers aged 18-25 years (YACs) with young adult without care responsibilities
    Survey study
    Quantitative

ENTWINE_YACs_nonYACsSurvey_RawData

ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData

ENTWINE_ PerceivedLifeBalanceSurvey _Syntax

ENTWINE_YACs_nonYACsSurvey_codebook

    2
    Examining the relationship of positive aspects of caregiving with relational factors among young adult caregivers
    Examine the relationship of positive aspects of caregiving with relational factors, in particular, relationship quality and collaborative coping among a particular group of ICGs, young adult caregivers (YACs), aged 18-25 years.
    Survey study
    Quantitative

ENTWINE_YACs_nonYACsSurvey_RawData

ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData

ENTWINE_PositiveAspectsCaregiving_Survey_Syntax

ENTWINE_YACs_nonYACsSurvey_codebook

    3
    Exploring the support needs of young adult caregivers, their issues, and preferences towards a web-based tool
    Explore (i) challenges and support needs of YACs in caregiving, (ii) their needs towards the content of the ‘MantelzorgBalans’ tool, and (iii) issues they encountered in using the tool and their preferences for adaptation of the tool.
    Usability study

Qualitative and Quantitative

ENTWINE_Needs_Web-basedTools_YACs_Interview_Usability_RawData [to be determined whether data can be shared]

ENTWINE_Needs_Web-basedTools_YACs_Questionnaires_RawData

Description of the files to be uploaded

Study 1: Perceived life balance among young adult students: a comparison between caregivers and non-caregivers

ENTWINE_YACs_nonYACsSurvey_RawData: SPSS file with the complete, raw, pseudonomyzed survey data. The following cleaned dataset ‘ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData’ was generated from this raw data.

ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData: SPSS file with the cleaned dataset having the following metadata -

Population: young adult caregivers and young adult non-caregivers aged 18-25 years studying in the Netherlands;

Number of participants: 320 participants in total (74 young adult caregivers and 246 young adult non-caregivers)

Time point of measurement: Data was collected from December 2020 till March 2022

Type of data: quantitative

Measurements included, topics covered: perceived life balance (based on the Occupational balance questionnaire [1]), burnout (Burnout Assessment Tool [2]), negative and positive affect (Positive and Negative Affect Schedule [3]), and life satisfaction (Satisfaction with Life Scale [4])

Short procedure conducted to receive data: online survey on Qualtrics platform

SPSS syntax file ‘ENTWINE_ PerceivedLifeBalanceSurvey _Syntax’ was used to clean and analyse ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData dataset

ENTWINE_YACs_nonYACsSurvey_codebook: Codebook having the variable names, variable labels, and the associated code values and code labels for ENTWINE_PerceivedLifeBalanceSurvey_YACs_nonYACs_CleanedData dataset

Study 2: Examining the relationship of positive aspects of caregiving with relational factors among young adult caregivers

ENTWINE_YACs_nonYACsSurvey_RawData: SPSS file with the complete, raw survey data. The following cleaned dataset ‘ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData’ was generated from this raw data.

ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData: SPSS file with the cleaned dataset having the following metadata -

Population: young adult caregivers aged 18-25 years studying in the Netherlands;

Number of participants: 74 young adult caregivers

Time point of measurement: Data was collected from December 2020 till March 2022

Type of data: quantitative

Measurements included, topics covered: positive aspects of caregiving (positive aspects of caregiving scale [5]), relationship quality (Relationship Assessment Scale [6]), collaborative coping (Perception of Collaboration Questionnaire [7] )

Short procedure conducted to receive data: online survey on Qualtrics platform.

SPSS syntax file ‘ENTWINE_PositiveAspectsCaregiving_Survey_Syntax’ was used to clean and analyse ‘ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData’ dataset.

ENTWINE_YACs_nonYACsSurvey_codebook: Codebook having the variable names, variable labels, and the associated code values and code labels for ENTWINE_PositiveAspectsCaregiving_Survey_YACs_cleanedData dataset.

Study 3: Exploring the support needs of young adult caregivers, their issues, and preferences towards a web-based tool

ENTWINE_Needs_Web-basedTools_YACs_Interview_Usability_RawData: Pseudonymized word file including 13 transcripts having the qualitative data from interview and usability testing with the following metadata –

Population: young adult caregivers aged 18-25 years studying in the Netherlands; 13 participants in total

Time point of measurement: data was collected from October 2021 till February 2022

Type of data: qualitative and quantitative

Measurements included, topics covered: Caregiving challenges, support needs and barriers, usability needs, preferences and issues towards eHealth tool

Short procedure conducted to receive data: Online interviews

ENTWINE_Needs_Web-basedTools_YACs_Questionnaires_RawData: Excel sheet having the quantitative questionnaire raw data with the following metadata

Population: young adult caregivers aged 18-25 years studying in the Netherlands; 13 participants in total

Time point of measurement: data was collected from October 2021 till February 2022

Type of data: qualitative and quantitative

Measurements included, topics covered: User experience (user experience questionnaire [8]), satisfaction of using the web-based tool (After scenario questionnaire [9]), Intention of use and persuasive potential of the eHealth tool (persuasive potential questionnaire [10])

Short procedure conducted to receive data: Online questionnaire

Data collection details

All data was collected, processed, and archived in accordance with the General Data Protection Regulation (GDPR) and the FAIR (Findable, Accessible, Interoperable, Reusable) principles under the supervision of the Principal Investigator.

The principal researcher and a team of experts (supervisors) in the field of health psychology and eHealth (University of Twente, The Netherlands) reviewed the scientific quality of the research. The studies were piloted and tested before starting the collection of the data. For the survey study, the researchers monitored the data collection weekly to ensure it was running smoothly.

The ethical review board, Centrale Ethische Toetsingscommissie of the University Medical Center Groningen, The Netherlands (CTc), granted approval for this research (Registration number: 202000623).

Participants digitally signed informed consent for participating in the study.

Terms of use

Interested persons can send a data request by contacting the principal investigator (Prof. dr. Mariët Hagedoorn, University Medical Center Groningen, the Netherlands mariet.hageboorn@umcg.nl).

Interested persons must provide the research plan (including the research question, methodology, and analysis plan) when requesting for the data.

The principal investigator reviews the research plan on its quality and fit with the data and informs the interested person(s).

(Pseudo)anonymous data of those participants who agreed on the reuse of their data is available on request for 15 years from the time of completion of the PhD project.

Data will be available in Excel or SPSS format alongside the variable codebook after the completion of this PhD project and publication of the study results.

References

1. Wagman P, Håkansson C. Introducing the Occupational Balance Questionnaire (OBQ). Scand J Occup Ther 2014;21(3):227–231. PMID:24649971

2. Schaufeli WB, Desart S, De Witte H. Burnout assessment tool (Bat)—development, validity, and reliability. Int J Environ Res Public Health 2020;17(24):1–21. PMID:33352940

3. Watson D, Clark LA, Tellegen A. Development and Validation of Brief Measures of Positive and Negative Affect: The

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. This study includes data that was used to investigate the effect of legislative and judicial factors on system responses to sex trafficking of minors (STM) in metropolitan and non-metropolitan communities. To accomplish this, researchers evaluated the effectiveness of the immunity, protection, and rehabilitative elements of a state safe harbor law. This project was undertaken as a response to a growing push to pass state safe harbor laws to align governmental and community responses to the reframing of the issue of sex trafficking of minors that was ushered in with the passage of the Trafficking Victims Protection Act (TVPA). This collection includes 4 SPSS files, 3 Excel data files, and 2 SPSS Syntax files: Child-Welfare-Human-Trafficking-Reports-2013-2017-data.xlsx Judicial-Interview-De-identified-Quantitative-Data-for-NACJD_REV_Oct2018.sav (n=82; 36 variables) Judicial-online-survey-data-for-NACJD_REV_Dec2018.sav (n=55; 77 variables) Juvenile-Justice-Screening-for-HT-2015-MU-MU-0009.xlsx Post-implementation-survey-data-for-NACJD_REV_Dec2018.sav (n=365; 1029 variables) Pre-implementation-survey-data-for-NACJD_REV_Dec2018.sav (n=323; 159 variables) Recode-syntax-for-pre-implementation-survey-for-NACJD.sps Statewide-juvenile-court-charges-2015-MU-MU-0009-to-NACJD.xlsx Syntax-for-post-implementation-survey-data-to-NACJD.sps Qualitative data from judicial interviews and agency open-ended responses to Post-Implementation of the Safe Harbor Law Survey are not available as part of this collection.

• SPSS file containing extracted general, patient and intervention characteristics - SPSS syntax file for descriptive statistics and associations of/within subsets of studies - RevMan 5.3 file containing meta-analyses

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 purpose of this study was to produce knowledge about how to prevent at-risk youth from joining gangs and reduce delinquency among active gang members. The study evaluated a modification of Functional Family Therapy, a model program from the Blueprints for Healthy Youth Development initiative, to assess its effectiveness for reducing gang membership and delinquency in a gang-involved population. The collection contains 5 SPSS data files and 4 SPSS syntax files: adolpre_archive.sav (129 cases, 190 variables), adolpost_archive.sav (119 cases, 301 variables), Fidelity.archive.sav (66 cases, 25 variables), parentpre_archive.sav (129 cases, 157 variables), and parentpost_archive.sav {116 cases, 220 variables).

Abstract copyright UK Data Service and data collection copyright owner.

The Workplace Employment Relations Survey (WERS) Time-Series Dataset 1980-2011 is derived from the data collected in the interviews with the main management respondent in each of the cross-section surveys in the Workplace Employment Relations Survey series (1980, 1984, 1990, 1998, 2004 and 2011) and the 1991 Employers' Manpower Skills Practices Survey (a follow-up to the 1990 WIRS). The dataset contains consistently defined variables (where possible) for data items that are present in the 1998, 2004 or 2011 surveys and at least one other previous cross-section survey in the series.

Taking a topic such as the presence of a multi-issue joint consultative committee (Questions: DJOINT and DISSUES), similar questions were first identified in each of the 1980, 1984 and 1990 surveys. The 1991 EMSPS also served as a source of data in instances where an issue was not covered in WIRS90 but was covered in EMSPS. If the questions that were found across the series were considered sufficiently similar to permit the compilation of a consistent measure, a data item would be derived from each of the relevant survey data files in turn (see syntax files Get80ts.sps, Get84ts.sps, etc.). Having derived these consistent data items, workplace records from each of the surveys were then added together (see MergeTS.sps) to form a single time-series dataset that spanned the whole of the series. An additional variable named YEAR was also added to the dataset to identify the survey from which each individual observation originates. Further details may be found in the documentation and on the gov.uk WERS 2011 webpage.

The time-series dataset also contains a link variable (TEUKLEMS) that enables observations to be linked to the EU KLEMS industry-level database, which provides measures of economic growth, productivity, employment creation, capital formation and technological change at the industry level for the UK from 1970 onwards. Further information can be found at the EU KLEMS Project web page.

For the third edition (September 2014), data for 2011 have been added to the time series file and the documentation updated accordingly. The SPSS syntax used for the addition of the 2011 data has also been deposited.


Main Topics:

The WIRS/WERS series provides statistically reliable, nationally representative data on the state of workplace relations and employment practices in Britain. In each of the five cross-section surveys in the series, the main management respondent (the most senior manager at the workplace with responsibility for employment relations) has been asked mainly factual questions covering a wide range of issues that deal with the employment relationship. Some examples include consultation and communication, pay determination arrangements, and work organization.

These data are part of NACJD's Fast Track Release and are distributed as they there received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except of the removal of direct identifiers. Users should refer to the accompany readme file for a brief description of the files available with this collections and consult the investigator(s) if further information is needed.The study used a multi-method approach including 1. a process evaluation in all eight sites involving yearly site visits from 2012 to 2014 with key stakeholder interviews, observations, and participant focus groups; 2. a prospective impact evaluation (in four sites) including interviews at release from jail or prison and at 12 months after release (as well as oral swab drug tests) with reentry court participants and a matched comparison group; 3. a recidivism impact evaluation (in seven sites) with a matched comparison group tracking recidivism for 2 years post reentry court entry and 4. a cost-benefit evaluation (in seven sites) involving a transactional and institutional cost analysis (TICA) approach. Final administrative data were collected through the end of 2016.This collection includes four SPSS data files: "interview_archive2.sav" with 746 variables and 412 cases, "NESCCARC_Archive_File_3.sav" with 518 variables and 3,710 cases, "Interview Data1.sav" with 1,356 variables and 412 cases, "NESCCARC Admin Data File.sav" with 517 variables and 3,710 cases, and three SPSS syntax files: "Interview Syntax.sps", "archive_2-17.sps", and "NESCCARC Admin Data Syntax.sps".

I attach data and code to reproduce analyses for manuscript - Personality and Team Identification Predict Violent Intentions Among Soccer Supporters.I have attached the following data files:- Soccer_supporters_raw.sav- Soccer_data_raw.csv- Soccer_data.xlsx- Soccerpathmodel.txtCodebook:- CodeBook_soccersupportersdata.csv*Note that this codebook applies to the raw data.And code:Syntax_soccer_supporters.sps (to be opened in SPSS)*Note that this code is also available in non-proprietary .txt format: Syntax_soccer_supporters.txtSoccerpathmodel.inp (to be opened in MPLUS (Muthén & Muthén, 2012, see also https://www.statmodel.com/ ).

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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 study contains data on sexual assault cases reported to the police for the years 2006-2012, collected from six police agencies and also their corresponding public prosecutor's offices across the United States. The study analyzed the attrition of sexual assault cases from the criminal justice system. This study includes two SPSS data files: Court-Form-2008-2010-Sample-Revised-Nov-2018.sav (801 variables, 417 cases) Police-Form-2008-2010-Sample-Revised-Nov-2018.sav (1,276 variables, 3,269 cases) This study also includes two SPSS syntax files: ICPSR-Court-Form-Variable-Construction-2008-2010.sps ICPSR-Constructed-Variables-Syntax.sps The study also contains qualitative data which are not available as part of this data collection at this time. The qualitative data includes interviews, field observations, and focus groups which were conducted with key personnel to examine organizational and cultural dimensions of handling sexual assault cases in order to understand how these factors influence case outcomes.

Underlying data for Parker et al, The Effect of Experimentally Induced Cognitive Fatigue on Energy Intake Among Youth With and Without Recent Reported Dietary Restraint. An SPSS dataset and syntax file are submitted.

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 Empirical Assessment of Domestic Radicalization (EADR) project seeks to provide practitioners, researchers, and the public with an empirical foundation for understanding the radicalization processes of United States-based extremists. Project researchers utilized a mixed-method, nested approach to explore a number of key research questions related to radicalization, including: what are the demographic, background, and radicalization differences between and within the different ideological milieus? are there important contextual, personal, ideological, or experiential differences between radicals who commit violent acts and those who do not? is it possible to identify sufficient pathways to violent extremism? are the causal mechanisms highlighted by extant theories of radicalization supported by empirical evidence? To address these questions, EADR researchers built the largest known database on individual radicalization in the United States: Profiles of Individual Radicalization in the United States (PIRUS). The database includes 147 variables covering demographic, background, group affiliation, and ideological information for a sample of 1,473 violent and non-violent extremists who radicalized in the United States from 1948-2014. The database is not limited to a particular ideological milieu, but instead contains information on individuals who adhere(d) to far right, far left, Islamist, and single-issue ideologies The collection includes 5 SPSS datasets and 2 SPSS syntax files: PIRUS_full_dataset_ICPSR_archive.sav (n=1,473; 113 variables) PIRUS_expected_maximization_version.sav (n=16,203; 27 variables) PIRUS_fixed_value_imputation_version.sav (n=1,473; 27 variables) PIRUS_regression_based_imputation_version.sav (n=16,203; 28 variables) PIRUS_subgroup_mean_substitution_version.sav (n=1,473; 27 variables) quantitative_analysis_syntax.sps variable_prep_syntax.sps

This study uses a dataset, which cannot be deposited online, but is freely available to registered academic users. The data of the 2008 National Annenberg Election Survey Internet Panel can be requested via https://www.annenbergpublicpolicycenter.org/data-access/. Here I provide a SPSS syntax file used to recode the variables employed and run the descriptive analyses, as well as a STATA do-file used to run the inferential analyses.

The dataset included the event-related potential (ERP) responses to visual stimuli, focusing on the N170 component, which were collected from 20 children with ADHD aged 6 to 12 and 20 typical developing children who were stringently matched with the ADHD participants based on gender and age. The performance of reading-related skills, such as rapid naming speed and orthographic processing abilities were included in as well. The dataset.sav is a SPSS Statistics Data Document file that has been organized for data analysis purposes. The analysis.sps file is a SPSS Statistics Syntax file containing the code to perform data analysis operations.