{
    "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/"
        }
    }
}