five

Heat and Helping

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Figshare2024-12-18 更新2026-04-08 收录
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https://figshare.com/articles/dataset/Heat_and_Helping/26124469/3
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<b>Update Note (16 Dec 2024):</b>During the peer review of a paper reporting these results, data files "data_alt.csv" and "data_alt_r1.csv" were hosted in this domain for reviewers to evaluate the work. Since the data contain copyrighted information, they cannot be shared publicly. Therefore, upon acceptance of publication of the work (15 Dec 2024), the two datasets were removed from this domain. Colleagues who are interested in the data can contact the corresponding author (Henry Ng: nghks@hku.hk) for more information. For security reasons, ipynb files containing the author's directory paths have been removed as well.<b>Data Files (removed):</b>data_alt.csv is the data reported in the first submission of this project. data_alt_r1.csv is an expanded data file in response to comments after the first review.data_overview summarizes the variable columns of data files data_alt.csv and data_alt_r1.csv.<b>Results Files:</b>ms_results.ipynb hosts summary statistics and visuals reported in the results section of the published article.donate_m1_m6.ipynb, help_strngr_m1_m6.ipynb, and volunteer_m1_m6.ipynb host the PyStan codes that generate the MCMC chains for Bayesian inferences of Models 1 to 6 for each of the three outcome variables.<b>Supplementary Files:</b>supplementary_r1_1 corresponds to additional analyses required by R1C3, R2C5 and R2C4, regarding the use of the metric form of GNIPC instead of the dummy coded version. It also explores three covariates, namely GINI index, ghg emission, and % of population attaining tertiary education.supplementary_r1_2 corresponds to additional analyses required by R3C3, regarding the adoption of different priors. Four additional priors have been tested to show the minimal impact of the choice of priors on the analysis.supplementary_ar1_(hlp/don/vol) corresponds to analyses of Model 3, 5, and 6, with the addition of an autoregressive process (AR1) in the time series. The analyses report findings consistent with the original analyses without the AR1 process.
提供机构:
Ng, Henry
创建时间:
2024-12-16
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