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Data consists of Stata 12 data set of the Zambia Demographic Health Survey Data for the year 2013/14. The data set consist of childhood mortality rates as well as socioeconomic, demographic and cultural factors associated with the deaths of these children. Using a multivariate regression analysis, the study uses odds ratio to determine factors are associated with childhood deaths. However, the study uses marginal effects of these factors to determine the extent to which these factors influence childhood mortality. The data set further includes the do-files showing the commands that were run in coming up with the results.
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this Data reveals all results founded in this research paper
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Dados para análise fatorial exploratória para a composição do modelo de dados.
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The research question for this dataset was: How will climate change impact the growth of spring wheat in Fairbanks, Alaska? The DSSAT CERES-Wheat crop simulation model was used to answer this research question. Data consists of DSSAT V4.7.0.0 Files and Field Data. Data in the Field Data files were collected at the University of Alaska Fairbanks small grains variety trial plot in Fairbanks, AK. This field data was input into DSSAT. DSSAT Files were used to calibrate, validate, and apply the DSSAT CERES-Wheat crop simulation model for simulating spring wheat growth (cultivar Ingal) in projected climate change scenarios. These DSSAT files are ready for a modeler to use.
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The dataset contains the data collected in a user study carried out to evaluate the impact of using domain knowledge, ontologies, in the creation of global post-hoc explanations of black-box models. The research hypothesis was that the use of ontologies could enhance the understandability of explanations by humans. To validate this research hypothesis we ran a user study where participants were asked to carry out several tasks. In each task, the answers, time of response, and user understandability and confidence were collected and measured. The data analysis revealed that the use of ontologies do enhance the understandability of explanations of black-box models by human users, in particular, in the form of decision trees explaining artificial neural networks.
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Measures of a Spanish sample of working and non-working adults with mental illness. Including variables such as perceived personal and group discrimination, internalized stigma, disagnosis concealment, and self-esteem.
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This is the original data of our research about economic policy uncertainty and stock liquidity from China. Our data come from two main sources, that is CSMAR and Wind database. The sample consists of the A-share listed companies from 2004 to 2017 in both Shanghai and Shenzhen Stock Exchange. We then filter the sample by: (1) delete the sample of financial and insurance industry; (2) remove the sample of abnormal companies such as special treated firms and particular transfer firms; (3) delete samples with asset-liability ratio greater than 1 and other variables with missing values; (4) winsorise the continuous variables at the 1st and 99th percentiles in order to eliminate potential outlier effects. The final sample consists of 97,729 firms.
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GIS data associated with Neugarten RA et al. 2020. Trends in protected area representation of biodiversity and ecosystem services in five tropical countries. Ecosystem Services 42:101078. Includes data from Cambodia, Guyana, Liberia, Madagascar, and Suriname Datasets included: country boundaries, protected areas in 2003 and 2017, biodiversity priority areas, forest cover in 2003 and 2015, forest carbon stocks, non-timber forest products, and freshwater ecosystem services
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The dataset provides a chaos game representation (CGR) of SARS-CoV-2 virus nucleotide sequences. The dataset is composed of 100 virus instances of SARS-CoV-2. In addition, the dataset also provides a CGR representation of 11540 viruses from the Virus-Host DB dataset and the other three Riboviria viruses from NCBI.
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The data supporting all analyses presented in the results of each experiment for manuscript "Differences in time-based task characteristics help to explain the age-prospective memory paradox" (Accepted for publication in Cognition on 31st March, 2020) are provided here as supplementary online material. For each experiment, we provide each participant’s demographic data; proportion correct score for event, time-of-day, and time-interval cued tasks for each setting (i.e., Virtual Week and MEMO); and contextual data (MEMO). The contextual data for Experiment 1 includes reported location and activity; for Experiment 2 and 3: location, activity, and retrospective memory test (recognition of quiz type). Note: odd quiz numbers (e.g., “quiz 1.1”; day 1 quiz 1] are always time-of-day quizzes; and even quiz numbers (e.g., “quiz 1.2”; day 1 quiz 2) are always time-interval quizzes.
Data Types:
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