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We particularly focus on incidence estimates, as this allows us to later explore key methodological issues.
We have focussed on the potential bias in the relative survival estimates, as this is the measure most commonly reported.
The geometric rather than arithmetic mean is likely to align better with single value estimates as this is equivalent to averaging the logarithms of the values and back transforming.
Because of heterogeneity and possible unmeasured variance at the study level a random-effects model was used to obtain all pooled estimates, as this model interprets the available data with more caution and uses broad confidence intervals.
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Linear regression slope estimates as well as plots of this linear association are shown for descriptive purposes.
Heterogeneity is thus estimated as: For this example, A = 16 and B = 4, and a direct estimation of heterogeneity is again 20%.
Direct and indirect costs were estimated as described in this paper.
Although HIV prevalence is estimated as low in this country, it has been increasing in the last years.
First, when fewer generation means are summed to estimate a genetic effect, fewer sources of error are summed into this estimate as well.
However, it should be noted that there is a large confidence interval associated with this estimate as well as assumptions involving mutation rate and generation time.
In Ecuador alone it is estimated as little as 2% of this Pacific coastal forest remains intact.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com