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  • These files contain programs to produce the Tables and Figures in the article "Revenue- versus spending-based fiscal consolidation announcements: multipliers and follow-up," Journal of International Economics
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • Text
  • Title: Development Of Decision Making Based On Internal And External Information: A Hierarchical Bayesian Approach. Authors: Jacqueline N. Zadelaar, Joost A. Agelink van Rentergema, Jessica V. Schaaf a, Tycho J. Dekkers, Nathalie de Venta, Laura M. S. Dekkerse, Riëtte Olthof , Brenda R. J. Jansen, Hilde M. Huizenga. Abstract: In decision making, people may rely on their own information, as well as on information from external sources (e.g., family, peers, experts). The current study examined if and how both types of information are utilized by comparing four decision strategies: 1) an internal strategy (i.e., people solely rely on their own information); 2) an external strategy (i.e., people solely rely on the information from an external source); 3) a sequential strategy (i.e., people rely on either their own information and subsequently on that from an external source, if their own information deemed inadequate); 4) an integrative strategy (i.e., people’s own information and that of an external source are integrated to reach a decision). Strategy use was examined via Bayesian hierarchical mixture analysis. Study 1 featured an auditory discrimination task, administered to children (N=11, ages 6-11), adolescents (N=30, ages 12-17), and adults (N=25, ages 18-65). Study 2 entailed a visual discrimination task administered to children and young adolescents (N=305, ages 9-14). Age groups were compared on: 1) strategy use, 2) response accuracy, 3) response time. Strategies were assigned on an individual level, based on the posterior probability. BF values of strategy assignment were calculated using the Product space method.
    Data Types:
    • Other
    • Software/Code
    • Tabular Data
    • Dataset
    • Document
  • This is the study protocol for this randomised controlled trial
    Data Types:
    • Dataset
    • Document
  • Abstract Background and Objectives: This study aimed to unravel the relationship between socially anxious individuals’ expectation of being (dis)liked and actual likeability by looking at the mediation role of social behavior. Both more strategic self-disclosure and more automatic mimicry were examined. Method: Female participants (N=91) with various levels of social anxiety participated in a social task with a confederate. Before the task, participants rated their expectation of being liked by the confederate. Different sets of video-observers rated the likeability of the participants before and after the social task and their level of self-disclosure and mimicry. Results: Social anxiety was negatively related to the expectation to be liked. Social anxiety did not relate to observer ratings of likeability, self-disclosure and mimicry but social anxiety did moderate the relation between expectations and self-disclosure. As expected participants with low levels of social anxiety disclosed more if they expected to be liked. However, the reversed was found for the high socially anxious participants, a higher expectation of being liked related to less self-disclosure. Limitations: The study used an analogue female sample. Our social task was highly structured and does not represent informal day-to-day social interaction. Conclusion: Socially anxious individuals function rather well in highly structured social tasks. No support was found for likeability problems or disrupted mimicry. Nevertheless, high socially anxious individuals did have a cognitive bias and show a self-protective strategy: when expecting a neutral judgment they reduce their level of self-disclosure. This pattern probably adds to their feelings of social disconnectedness.
    Data Types:
    • Software/Code
    • Dataset
  • Quantitative data and qualitative data of research on effect of serioussoap.nl on geriatric knowledge of nurses and its usability.
    Data Types:
    • Dataset
    • File Set
  • In any case of use of this data, a reference to the study is mandatory. Please contact Valentin Melnikov in case you are unsure about the reference. This data results from the study of walking speeds in Singapore in relation to climate. The walker attributes were obtained from inspection of video recordings, which were taken in the area of observational study. The location of a study area: pedestrian path towards Lakeside MRT, Singapore (coordinates: 1.343414,103.720528). Video recordings are not published, but are stored at Complexity Institute, Nanyang Technological University, Singapore. Please contact Valentin Melnikov regarding the access to video recordings. The data consists of 6 files -- 2 files for each day of observational study: 1. kestrel_weather_ddmmYYYY.csv -- A CSV file containing 6 columns: * datetime -- Date and time in Singapore timezone (UTC+8) starting from 17:10 up to 17:40 (depending on duration of observation). * Temperature -- Air temperature (deg. C) measured by Kestrel 5400. * Wind speed -- Wind speed (m/s) measured by Kestrel 5400. * Globe Temperature -- Black globe temperature (deg. C) measured by Kestrel 5400. * Relative Humidity -- Relative humidity (%) measured by Kestrel 5400. * Tmrt -- Mean radiant temperature (deg. C) calculated according to equation 3 in Thorsson et al. (2007) [https://doi.org/10.1002/joc.1537]. 2. walkers_lakeside_ddmmYYYY.xlsx -- A Microsoft Excel file containing following columns: * Description -- Contains numbers of walkers in published data (in original data was having characteristic description of walker). * Direction -- Direction of movement of walker (R -- to the right, from the Lakeside MRT station / L -- to the left / to the Lakeside MRT station). * Gender -- Apparent gender of a walker (F -- female / M -- male). * Age group -- Apparent age of a walker (0 -- 12 & 18 & 45 y.o.). * Clothing type -- Level of clothing (0 -- both top and bottom are short / 1 -- top or bottom is long / 2 -- both top and bottom are long). * Used phone -- Whether walker was using phone (0 -- No / 1 -- Yes). * Overload -- Whether walker was bearing excessive aload (0 -- No / 1 -- Yes). * In group -- Whether walker is representing group (0 -- No / otherwise -- a number of co-walkers [for 22nd Oct -- only 1 was used just to indicate group, but not its size]). * Time in -- Time label in format [min.sec] corresponding to time on video recording when walker entered the area. * Time out -- Time label in format [min.sec] corresponding to time on video recording when walker exited the area. * Note -- Specific note for a walker. In analysis, walkers with notes were excluded. * Duration -- Calculated traversal time in seconds. * Speed -- Calculated walking speed in m/s (30 meters / Duration).
    Data Types:
    • Tabular Data
    • Dataset
    • Text
  • EMA dataset
    Data Types:
    • Tabular Data
    • Dataset
  • In the selection task, participants had to select the region of interest (a specified vessel segment) as explained in the "Experiment_description.pdf" file. They were asked to manipulate (i.e., translate, rotate and scale) a 3D box widget, initially positioned such that the region of interest covered all vessel structures displayed on the screen. Three 3D model files ("level1.vtk", "level2.vtk" and "level.3 vtk") were used to define three complexity levels of the selection task: Level 1 (simple) — one vessel; Level 2 (average) — two closely located vessels; Level 3 (complex) — three vessels, where two vessels are located close to each other. This project was funded by the University of Amsterdam and NWO.
    Data Types:
    • Software/Code
    • Dataset
    • Document
  • This dataset contains ranking, on importance and feasibility, of statements of requirements of an electronic medical records system for oncology in low and middle income countries, by different stakeholders in cancer care in this setting
    Data Types:
    • Tabular Data
    • Dataset
  • This dataset contains clustering data for statements of requirements for an electronic medical records system for oncology in low and middle income countries (LMICs). It is a matrix with similar rows and columns. The numbers indicate how often the statement in the row was put in the same cluster as the statement in the column. The clustering exercise was completed by stakeholders in oncology in LMICs.
    Data Types:
    • Tabular Data
    • Dataset
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