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As a control for the calculated data, we also analyzed CD rates in specific cities in Europe (from Molodecky et al 23) against city latitudes using Pearson's correlations.
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We calculated data for 24 59 months based on the previously cited one.
For dichotomous data we calculated relative risks and where appropriate combined results from different trials.
By using the mean distance as calculated from the data, we remove this nuisance parameter from the algorithm.
For continuous data, we calculated a weighted mean difference and for dichotomous variables we calculated a weighted odds ratio (OR).
For abundance or density data, we calculated the target by summing all values across planning units and calculating 20% of the total.
To estimate the degree of population differentiation from our data we calculated the F ST statistic.
For binary outcome data, we calculated risk ratios and 95% confidence intervals (CI) and for continuous outcome data we calculated the mean difference and 95% CI for each trial.
Based on these data, we calculated the yearly incidence of cervical cancer per 100 000 woman years at risk and calculated 95% Poisson confidence intervals using an exact method.
Combining this with census data, we calculated the incidence.
On the basis of experimentally recorded data, we calculated the values of absorption coefficient.
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