| { | |
| "original_study": { | |
| "claim": { | |
| "hypothesis": "We predicted that cultural tightness and government efficiency would predict slower growth rates of COVID-19 and lower mortality likelihoods, and that nations with high cultural tightness and high government efficiency would show especially slow growth rate and mortality likelihood.", | |
| "hypothesis_location": "Section: Introduction; p. 3.", | |
| "statement": "Culturally tight nations and 20 nations with higher levels of government efficiency each had significantly slower COVID-19 infection rates.", | |
| "statement_location": "Section: Introduction; p. 5.", | |
| "study_type": "Observational" | |
| }, | |
| "data": | |
| [ | |
| { | |
| "source": "European Center for Disease Control", | |
| "wave_or_subset": "not stated", | |
| "sample_size": "528,019", | |
| "unit_of_analysis": "cases", | |
| "access_details": "not stated", | |
| "notes": "For COVID data." | |
| }, | |
| { | |
| "source": "World Bank’s Government Efficiency Index", | |
| "wave_or_subset": "2017", | |
| "sample_size": "126", | |
| "unit_of_analysis": "country level", | |
| "access_details": "not stated", | |
| "notes": "For government efficiency data. World Bank data was also used for Gini coefficient data." | |
| }, | |
| { | |
| "source": "index from Gelfand et al.", | |
| "wave_or_subset": "2017", | |
| "sample_size": "126", | |
| "unit_of_analysis": "country level", | |
| "access_details": "not stated", | |
| "notes": "For cultural tightness data. No access discussed but a reference is included (Gelfand et al., 2011)." | |
| }, | |
| { | |
| "source": "International Monetary Fund", | |
| "wave_or_subset": "2019", | |
| "sample_size": "not stated", | |
| "unit_of_analysis": "country level", | |
| "access_details": "not stated", | |
| "notes": "For economic development, proxied by GDP per capita, data." | |
| }, | |
| { | |
| "source": "CIA World Factbook", | |
| "wave_or_subset": "2018", | |
| "sample_size": "not stated", | |
| "unit_of_analysis": "country level", | |
| "access_details": "not stated", | |
| "notes": "For median age data." | |
| } | |
| ] | |
| , | |
| "method": { | |
| "description": "The authors run a OLS regression to test the effect of the interaction between government efficiency and cultural tightness on the infection rate of COVID-19 and a logistic regression to test the effect of this interaction on mortality likelihood.", | |
| "steps": "(1) Download the data and construct the variables, including constructing death rate by dividing the number of mortalities by the number of cases; (2) Standardize relevant covariates; (3) Take the log of the outcome (cases per million people) and explanatory variable (days) and run a country-level, logged regression of COVID cases on days; (4) conducted a second set of regressions using the estimates from the initial 10 general linear models to predict cross-cultural variation in the infection rate of COVID-19, weighting cases by the number of observations across nations; (5) Run regressions using interacted terms as well.", | |
| "models": "ordinary least squares regression with gaussian distribution and logistic regression with exponential distribution", | |
| "outcome_variable": "infection rate of COVID-19 and mortality likelihood", | |
| "independent_variables": "government efficiency interacted with cultural tightness", | |
| "control_variables": "economic development; inequality; median age", | |
| "tools_software": "not stated" | |
| }, | |
| "results": { | |
| "summary": "...nations with high cultural tightness and high government efficiency would have a much lower log-transformed rate of 1.06 new cases per million. Culturally tight nations and nations with higher levels of government efficiency each had significantly lower death rates of COVID-19.", | |
| "numerical_results": [ | |
| { | |
| "outcome_name": "growth rates of COVID-19", | |
| "value": "0.17", | |
| "unit": "not stated", | |
| "effect_size": "log-transformed rate of 1.41 new cases per million people per day or 103.21 fewer cases per million people", | |
| "confidence_interval": { | |
| "lower": "not stated", | |
| "upper": "not stated", | |
| "level": "not stated" | |
| }, | |
| "p_value": "0.031", | |
| "statistical_significance": "5% level", | |
| "direction": "Negative", | |
| "notes": "No confidence intervals presented, but standard errors are presented instead (0.07)." | |
| }, | |
| { | |
| "outcome_name": "mortality likelihood", | |
| "value": "0.30", | |
| "unit": "not stated", | |
| "effect_size": "1.43 more people per million", | |
| "confidence_interval": { | |
| "lower": "not stated", | |
| "upper": "not stated", | |
| "level": "not stated" | |
| }, | |
| "p_value": "< .001", | |
| "statistical_significance": "0.1% level", | |
| "direction": "Negative", | |
| "notes": "No confidence intervals presented, but standard errors are presented instead (0.03)." | |
| } | |
| ] | |
| }, | |
| "metadata": { | |
| "original_paper_id": "not stated", | |
| "original_paper_title": "Cultural and Institutional Factors Predicting the Infection Rate and Mortality Likelihood of the COVID-19 Pandemic ", | |
| "original_paper_code": "https://osf.io/pc4ef/", | |
| "original_paper_data": "https://osf.io/pc4ef/" | |
| } | |
| } | |
| } | |