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- Creator:
- Eby, David W and Molnar, Lisa J
- Description:
- Data are contained in an Excel spreadsheet formatted such that each row is a separate participant and each column is a separate question. This file is called: EbyEtAl-TransportCaregiver. A data dictionary that gives the text for each question and the response categories mappings is contained in another Excel Spreadsheet. This file is called: EbyEtAl-TransportCaregiverDictionary. The text of the survey, the development of weights, and response rate calculations can be found in the Deep Blue report discussed previously.
- Keyword:
- Caregiver Burden, Driving, and Automobile
- Discipline:
- Social Sciences
-
- Creator:
- Benjamin Leffel
- Description:
- The three datasets provided here identify the city location of all CDM projects in China by referencing the individual Project Description Documents (via the UNFCCC) attached to each project. Through this method, all 3,764 Clean Development Mechanism projects at the city-level in China are identified out of a total of over 8,000 globally.
- Keyword:
- climate finance, carbon offset, China, urban, clean development mechanism, cities, and climate change
- Citation to related publication:
- https://escholarship.org/uc/item/3vr8850s and https://doi.org/10.1002/wcc.709
- Discipline:
- Government, Politics and Law, Social Sciences, International Studies, and Business
-
- Creator:
- Benjamin Leffel
- Description:
- Time series dataset of adoption by year of climate action plans by 177 U.S. cities, 2010-2019, with links to plans included. This dataset is intended for use by researchers and practitioners investigating both individual climate action plans and time series patterns of adoption at the municipal level.
- Keyword:
- climate change, climate action plan, municipal, and Urban Sustainability Research Group
- Discipline:
- Social Sciences and Government, Politics and Law
-
- Creator:
- Benjamin Leffel
- Description:
- Data were gathered to test three hypotheses on the impact economic growth has on environmental conditions in urban areas. The three hypotheses are: 1. Income will be associated with reductions in PM2.5, PM10, NO2 and SO2. 2. Public Administration GVA will be associated with reductions in PM2.5, PM10, NO2 and SO2. 3. Urban density will be associated with reductions in PM2.5, PM10, NO2 and SO2. More information about the research and the data can be found in: Benjamin Leffel, Nikki Tavasoli, Brantley Liddle, Kent Henderson & Sabrina Kiernan (2021) Metropolitan air pollution abatement and industrial growth: Global urban panel analysis of PM10, PM2.5, NO2 and SO2, Environmental Sociology, DOI: 10.1080/23251042.2021.1975349.
- Keyword:
- global cities, environment, urban, air pollution, income, Urban Sustainability Research Group, and student-friendly
- Citation to related publication:
- Benjamin Leffel, Nikki Tavasoli, Brantley Liddle, Kent Henderson & Sabrina Kiernan (2021) Metropolitan air pollution abatement and industrial growth: Global urban panel analysis of PM10, PM2.5, NO2 and SO2, Environmental Sociology, DOI: 10.1080/23251042.2021.1975349
- Discipline:
- Social Sciences
-
- Creator:
- Samuel, Sara M, Wilson, Diane L, and Fleming, Emily K
- Description:
- The International Committee of Medical Journal Editors (ICMJE) requires researchers to post individual participant data (IPD) plans for interventional clinical trials with registration in order to be eligible for publication in its member journals. This study looked at how researchers interpret the ICMJE requirements and the related prompts for information used by ClinicalTrials.gov. This data consists of the analyzed contents of the IPD plans that researchers at the University of Michigan (U-M) submitted with trial registrations for the first 27 months that the 2019 requirement was in effect.
- Keyword:
- research data sharing, research data policy, research data, clinical trials, ClinicalTrials.gov, individual participant data, IPD, data sharing plan, and compliance
- Citation to related publication:
- Samuel, S. M. & Wilson, D. L. & Fleming, E., (2023) “Evaluating individual participant data plans for ICMJE compliance: A case study at University of Michigan”, Journal of the Society for Clinical Data Management 3(4). doi: https://doi.org/10.47912/jscdm.257
- Discipline:
- Health Sciences, Social Sciences, and General Information Sources
-
- Creator:
- Krupka, Erin
- Description:
- The survey data used in this project is from two larger overarching projects titled the Rice Preferences Study and the Black Student Success Study. The Rice Preferences Study began with a sample of 661 entering undergraduates matriculating in August of 2016. This was 66.7% of the entering class, randomly selected. Of that sample, 553 completed the study with an 83.7% response rate. Prior to coming to campus in fall 2016 Rice students were given a battery of incentivized preference measures including risk aversion, loss aversion, altruism, in-group favoritism, time discounting, competitiveness, and so on. Over the subsequent four years that group was tested with new and repeated measures, in two to four tests per year. As a basis for comparison, each year a smaller sample (between 112 And 148) was drawn from incoming classes and tested with the same instruments. The remaining students from the Class of 2020 who had never been tested were invited in March 2020 to complete the initial study (259 of 376 completed the study). In March 2020, as Rice University closed, the team joined together to build a COVID module for the long-term Rice panel, as well as the other members of the Class of 2020. A total of 670 participated in this wave (67.1% of the graduating class). The Black Student Success Study recruited samples from PVAMU and TAMU in 2017 and again in 2019. This study aimed at understanding the effects of stereotype threat on Black student success in two different university environments in Texas: PVAMU, a historically Black university with about 9,000 students, 65% female, and 83% Black; and TAMU, a large state university with about 70,000 students, 47% female and 3.7% Black. That study was ongoing in 2020 when COVID struck. A total of 880 subjects responded to the initial survey out of a total of 3,709 who were contacted. Black subjects were over-sampled at TAMU, and constituted 37% of the TAMU sample. Respondents completed a one-hour survey that included measures of identity, non-cognitive skills, stereotype-threat vulnerability, and controls for economic preferences (survey measures) and family background. They were paid $20 for completing the study. In March 2020 additional funding was awarded through NSF to expand and follow the Rice, TAMU and PVAMU panels, focusing on the impact of COVID-19.
- Keyword:
- Norms, Preferences, Social Identity, COVID-19
- Discipline:
- Social Sciences
-
- Creator:
- Carlson, Jake
- Description:
- This data set is my analysis of data management plans (DMPs) that were written by researchers at the University of Michigan for awards made between March 2020 and February 2021. I conducted this analysis to explore the potential utility of DMPs as a tool to aid data curators in understanding and working with the associated data set. Variables collected include: the types and formats of the expected data sets, information about the metadata and documentation to be generated, the anticipated methods for making the data set publicly available, references to Intellectual Property allowances or concerns, and the stated duration for preserving the data sets.
- Keyword:
- Data management plans, Data curation, Data sharing, and Content Analysis
- Citation to related publication:
- Carlson, J. (2023) Untapped Potential: A Critical Analysis of the Utility of Data Management Plans in Facilitating Data Sharing. Journal of Research Administration. Fall 2023. Forthcoming.
- Discipline:
- Social Sciences
-
- Creator:
- Xu, Ying and Bradford, Nora
- Description:
- The data was collected from a survey study using Qualtrics described above. The data are in .csv format along with a codebook also in .csv format.
- Keyword:
- social chatbot, perception, and artificial intelligence
- Discipline:
- Social Sciences
-
- Creator:
- Wellman, Michael P.
- Description:
- For each game: - file in JSON format with raw payoff data - text file with game-theoretic analysis results
- Discipline:
- Social Sciences
-
- Creator:
- de Oliveira, Stephanie and Nisbett, Richard E.
- Description:
- These studies assess the effect of social identity on judgement and are described in "Demographically diverse crowds are typically not much wiser than homogeneous crowds" (de Oliveira, S., & Nisbett, R. E. Proceedings of the National Academy of Sciences, 2018) and the article’s Supporting Information appendix. Some studies use a variety of questions to assess multiple social identity factors; the other studies are narrowed to particular social identity variables. Each study includes some type of estimation or prediction task, collects social identity variables, and asks participants to indicate their answer strategies. Study 1 is a trivia and prediction task based on football team fan identity. Study 2 reports on demographics plus political and religious identity and asks participants to predict vote percentages in presidential primaries. Study 3 participants estimate the percentage of Americans that support statements on various polarizing political views and give likelihood ratings for presidential candidates to win the Iowa caucus; a variety of identity questions are asked including political and religious identity. Study 4 includes demographics plus political and religious identity questions and asks participants to predict how the candidates would perform in the 2016 United States presidential election. Study 5 asks participants to guess the popularity rating of books that had either gender-specific or gender-neutral appeal, and also to rate their own interest in the books. Demographic-based social identity variables such as sex are included. Study 6 includes a wide variety of social identity variables and asks participants to estimate the likelihood of events occurring in the near future. Study 7 participants are from diverse national backgrounds and completed judgement tasks that predicted stock prices, Olympic performance, and news events outcomes. The data are generally interpretable when examined in conjunction with the target article. A new data file for Study 6 was uploaded on April 4, 2018 to include variables that were inadvertently left out of the original Study 6 file. A new data file for Study 7 was uploaded on April 6, 2018 to include variables that were inadvertently left out of the original Study 7 file. A codebook for this data set was added on April 6, 2018.
- Keyword:
- Judgment/Decision Making and Estimate aggregation
- Discipline:
- Social Sciences
-
- Creator:
- Pearce, Alexa L.
- Description:
- This dataset accompanies a study that seeks to contribute to a clearer understanding of the discovery ecosystem in academic research libraries. Using historical literature as a case study, extensive citation analysis is employed to both reveal characteristics of secondary historical literature as well as to test a broad disciplinary discovery environment that includes six specific search platforms. By enhancing our understanding of where and how specific types of resources are –or are not—discoverable, as the case may be, this study can provide evidence to better inform the appropriate role and placement of various search platforms in a user’s process. This citation analysis drew upon all secondary literature that was cited in the American Historical Review (AHR) during a six-year period, from 2010 through 2015. The AHR is the official publication of the American Historical Association (AHA) and, as stated on its website, has served as “the journal of record for the historical profession in the United States since 1895.” Additionally, the AHR represents all subfields of history in its research articles and reviews of new scholarship. For this study, the author gathered citations from research articles only, excluding reviews. For the purposes of testing the library discovery environment, the author aimed to include citations that a researcher would be likely to identify by using library research tools, as opposed to archival finding aids. Recognizing that some tools included in this study, such as JSTOR and Historical Abstracts, do not index archival sources, the author decided to focus on published and secondary materials. All citations to archival sources, government information, and other unpublished manuscript materials were excluded. Additionally, citations to newspaper and general or popular press articles published prior to 1900 were excluded. Citations to entire periodicals, as opposed to articles, were also excluded. Books from all date ranges were included. Citations to non-scholarly newspaper and magazine articles published after 1900 were included. Citations to published primary sources were also included in the population of citations, as one may reasonably expect to locate them in a research library setting. The resulting population comprised 22,572 citations. After separating out duplicate citations, the total number was 19,937. Using a random number generator, the de-duplicated list of citations was re-ordered in order to select a random sample of 400, which affords a confidence level of 95% and a confidence interval of 5. The first step in analysis was to characterize each citation according to format, publication date, and language. Secondly, the author searched for all citations in the sample in the 6 different search platforms listed above. The primary question for each database included in the study was how comprehensively it represented the population of AHR citations, as represented by the random sample selected for this study. In order for a given citation to count as present in a particular database, it had to be represented in the format in which it was cited. For example, if a search for a cited book turned up only a dissertation, with the same author and very similar title, the analysis found that the citation was not present. For book chapters cited with authors and titles, it was not necessary for chapters to have their own records in order to be counted as present but it was necessary for them to be discernible among search results as chapters, such as in a table of contents listing. In order to expedite the search process, the author searched Historical Abstracts and America: History and Life simultaneously on the EBSCO platform. For all of the platforms except Google Scholar, the author performed advanced searches, entering both title and author information for each citation. All searching took place between February and May of 2017. The results presented here reflect the content available to search in each platform at the time of investigation.
- Keyword:
- discovery, history, secondary literature, information retrieval, reference analysis, citation analysis, library science, university libraries, and research libraries
- Discipline:
- Social Sciences
-
- Creator:
- Brennan, Jonathan R.
- Description:
- These files contain the raw data and processing parameters to go with the paper "Hierarchical structure guides rapid linguistic predictions during naturalistic listening" by Jonathan R. Brennan and John T. Hale. These files include the stimulus (wav files), raw data (matlab format for the Fieldtrip toolbox), data processing paramters (matlab), and variables used to align the stimuli with the EEG data and for the statistical analyses reported in the paper.
- Keyword:
- linguistics, syntax, language, and eeg
- Citation to related publication:
- Brennan JR, Hale JT (2019) Hierarchical structure guides rapid linguistic predictions during naturalistic listening. PLoS ONE 14(1): e0207741. https://doi.org/10.1371/journal.pone.0207741
- Discipline:
- Social Sciences
-
- Creator:
- Brennan, Jonathan R
- Description:
- These files contain the raw data and processing parameters to go with the paper "Hierarchical structure guides rapid linguistic predictions during naturalistic listening" by Jonathan R. Brennan and John T. Hale. These files include the stimulus (wav files), raw data (BrainVision format), data processing parameters (matlab), and variables used to align the stimuli with the EEG data and for the statistical analyses reported in the paper (csv spreadsheet). and Updates in Version 2: - data in BrainVision format - added information about data analysis - corrected prePROCessing information for S02
- Keyword:
- Linguistics, Speech, and EEG
- Citation to related publication:
- Brennan, J. R., & Hale, J. T. (2019). Hierarchical structure guides rapid linguistic predictions during naturalistic listening. PLoS ONE 14(1). e0207741
- Discipline:
- Social Sciences
-
- Creator:
- Platt, Edward L.
- Description:
- We analyzed the structure of English language WikiProject coeditor networks and compare to the efficiency and performance of those projects. The list of WikiProjects give an integer key, title, and unique URL for each project. The network files are indexed by the integer keys. The quality assessment logs are indexed by project title and article title. and Curation Notes: Readme file was updated Oct. 11, 2018 to include additional context on research, file contents, and organization (see first section of readme), and explanation of additional license in the deposit referring to the 'logbook' module.
- Keyword:
- wikipedia
- Discipline:
- Social Sciences
-
- Creator:
- Quarles, Christopher L.
- Description:
- Student capital is the set of skills, traits, and resources that an individual can draw upon to be successful in school. With dropout rates around 50%, community college students often don't have enough student capital to achieve their goals. The R code in this dataset estimates the average student capital of a group of community college students using data on their total credits and academic outcomes. It also contains R code to create figures, as found in the paper "The Shape of Educational Inequality" by Quarles, Budak & Resnick.
- Keyword:
- education, community college, and maximum likelihood estimation
- Citation to related publication:
- Quarles, C. L., Budak, C., Resnick, P. (2020). The shape of educational inequality. Science Advances. 6(29). https://doi.org/10.1126/sciadv.aaz5954
- Discipline:
- Social Sciences
-
- Creator:
- Hero, Alfred O, Zhai, Yaya, Burke, Thomas, Doraiswamy, Murali, Ginsburg, Geoffrey S, Henao, Ricardo, Turner, Ronald B, and Woods, Christopher W
- Description:
- The data deposited here is as follows: The clinical shedding/symptom data, RNAseq, steroid, and wearable E4 data was partially presented in publications [1]-[3] and the cognitive lumos and VAFS data is presented in the paper [4], which is under review and embargoed. The data files are: subject.json, sample.json, and genematrix_TPM.csv. In addition, a copy of the blank consent form used to enroll volunteers in the study is included (17964_Adult Consent_2015Mar17-Mod 1_clean.pdf)., Clinical symptom and viral shedding data (in subject.json): reports each subject's accumulated and maximum self-reported symptom score (modified Jackson score) and shedding titrations from nasal-pharyngeal washes after inoculation. , RNAseq data (genematrix_TMP.csv): Whole blood was collected in PAXgene™ Blood RNA tubes (PreAnalytiX), and total RNA extracted using the PAXgene™ Blood miRNA Kit (QIAGEN) using the manufacturer’s recommended protocol. RNA quantity and quality were assessed using Nanodrop 2000 spectrophotometer (Thermo-Fisher) and Bioanalyzer 2100 with RNA 6000 Nano Chips (Agilent). RNA sequencing libraries were prepared using Illumina TruSeq mRNA Library Kit with RiboZero Globin depletion, and sequenced on an Illumina NextSeq sequencer with 50bp paired-end reads (target 40M reads per sample). After demultiplexing to FASTQ paired-end read counts files, the 396 samples were TPM transformed using HISAT2 software with the reference genome Homo_sapiens.GRCh38.84. Each sample corresponds to one of the 18 subjects at one of 22 time points. One of these samples was of insufficient quality to be mapped to read counts. In addition to the TPM normalized RNAseq data contained in this repository, the raw FASTQ data for the 395 samples are deposited in the GEO repository ( https://www.ncbi.nlm.nih.gov/geo), Accession # GSE215087. , Cognitive data (sample.json): Outcomes from a NeuroCognitive Performance Test (NCPT) that was taken approximately 3 time daily by all volunteers. The NCPT is a repeatable, web-based, computerized, cognitive assessment platform designed to measure subtle changes in performance across multiple cognitive domains. Subject scores along 18 cognitive variables data were collected at approximated 22 time points during the challenge study. The data structure sample.json contains the raw cognitive data and the extracted 18 cognitive scores over time for each subject. , The Visual Analog Fatigue Scale (sample.json): the VAFS is a measure of cognitive fatigue that was measured approximately 3 times per day at the same time as the NCPT and blood draw. , Wearable device data (sample.json): participants wore an Empatica E4 device for the duration of the challenge study. Summarized features are provided for each subject that include sleep duration (mean and std), sleep offset (mean and std), and temperature (mean and std). , Steroid data was also collected and is included in the sample.json. This steroid data was collected from the whole blood samples and consists of cortisol, melatonin, and DHEAS. , and See README.txt for more specific details on the data structures contained in the sample.json, subject.json, and genematrix_TPM.csv files.
- Keyword:
- human challenge study and cognitive health and immunity
- Citation to related publication:
- X She, Y Zhai, R Henao, CW Woods, C Chiu, Geoffrey S. Ginsburg, Peter X.K. Song, AO. Hero, “Adaptive multi-channel event segmentation and feature extraction for monitoring health outcomes,” IEEE Transactions on Biomedical Engineering, vol. 68, no. 8, pp. 2377-2388, Aug. 2021, doi: 10.1109/TBME.2020.3038652. Available on arxiv:2008.09215 , Emilia Grzesiak, Brinnae Bent, Micah T. McClain, Christopher W. Woods, Ephraim L. Tsalik, Bradly P. Nicholson, Timothy Veldman, Thomas W. Burke, Zoe Gardener, Emma Bergstrom, Ronald B. Turner, Christopher Chiu, P. Murali Doraiswamy, Alfred Hero, Ricardo Henao, Geoffrey S. Ginsburg, Jessilyn Dunn Assessment of the Feasibility of Using Noninvasive Wearable Biometric Monitoring Sensors to Detect Influenza and the Common Cold Before Symptom Onset. JAMA Netw Open. 2021;4(9):e2128534. doi:10.1001/jamanetworkopen.2021.28534 , E Sabeti, S Oh, PX Song, A Hero. “A Pattern Dictionary Method for Anomaly Detection,” Entropy, vol 24, pp. 1095 Aug 2022. doi: 10.3390/e24081095, and Yaya Zhai, P. Murali Doraiswamy, Christopher W. Woods, Ronald B. Turner, Thomas W. Burke, Geoffrey S. Ginsburg, Alfred O. Hero, "Pre-exposure cognitive performance variability is associated with severity of respiratory infection," manuscript under review.
- Discipline:
- Health Sciences and Social Sciences
-
- Creator:
- Moser, Carol, Schoenebeck, Sarita , and Resnick, Paul
- Description:
- These data, survey instruments (including informed consent) and analysis scripts come from Carol Moser's dissertation titled, Impulse Buying: Designing for Self-Control with E-commerce.
- Keyword:
- Impulse Buying, Self-control, and Experimental Design
- Discipline:
- Social Sciences
-
- Creator:
- Schöpke-Gonzalez, Angela M., Thomer, Andrea K., and Conway, Paul
- Description:
- This interview protocol was designed to investigate the research question: How do self-identified refugees in the receiving societies of Greece and Germany engage with information spaces to navigate identity during liminal and post-liminal portions of their refugee experiences?
- Keyword:
- information space, identity, liminality, and migration
- Citation to related publication:
- Schöpke-Gonzalez, A., Thomer, A., & Conway, P. (2020). Identity Navigation During Refugee Experiences: The International Journal of Information, Diversity, & Inclusion (IJIDI), 4(2), 36–67. https://doi.org/10.33137/ijidi.v4i2.33151
- Discipline:
- Social Sciences
-
- Creator:
- Horsley, Timothy J. and Sampson, Christina P.
- Description:
- The data (raw data, composite files [processed], and some images) can be read by the program TerraSurveyor. Version 3.0.34.10 of the software was used to create the composite files in this deposit. and The magnetometer data was the second step in a geophysical survey program that began with magnetic susceptibility survey of a portion of the Weedon Island Preserve in St. Petersburg, Florida. Geophysical survey was used to map human occupation of the study area and to guide subsequent archaeological excavations.
- Keyword:
- magnetometry, geophysical survey, remote sensing, Florida archaeology, and coastal archaeology
- Citation to related publication:
- Sampson, C. P. (2019) Safety Harbor at the Weeden Island Site: Late Pre-Columbian Craft, Community, and Complexity on Florida's Gulf Coast. PhD Dissertation, University of Michigan. and Sampson, Christina Perry and Timothy J. Horsley. Using Multi-Staged Magnetic Survey and Excavation to Assess Community Settlement Organization: A Case Study from the Central Peninsular Gulf Coast of Florida. Advances in Archaeological Practice. Cambridge University Press: 18 December 2019. https://doi.org/10.1017/aap.2019.45
- Discipline:
- Science and Social Sciences
-
- Creator:
- Okullo, Dolorence, Gomez-Lopez, Iris N., Goodspeed, Robert, Reddy, Shruthi, Veinot, Tiffany C, Clarke, Phillipa J., and Data Driven Detroit
- Description:
- The information and education environment refers to: 1) the presence of information infrastructures such as broadband Internet access and public libraries in a location; 2) a person’s proximity to information infrastructures and sources; 3) the distribution of information infrastructures, sources and in a specific location; and 4) exposure to specific messages (information content) within a specific location. Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
- Keyword:
- Residential Broadband Data Adoption Rates, Census tract level, Broadband Internet Access and Speed, Colleges and Universities, Public Libraries, Spatial Measures, and Schools
- Discipline:
- Science, Social Sciences, and Health Sciences