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Because this methodology is well-developed in the literature, I sketch the implementation in the text and present additional details in Appendix 2. I assume that aggregate output in the North is produced using capital and labor according to a Cobb-Douglas technology.
Because this methodology is based on two one-tailed analyses, the actual CI will approach 97.5% as case and control counts approach their respective minima and maxima.
Because this methodology is far more data intensive, it presents difficulties in a middle-income setting such as South Africa, where such data are not always available.
In theory, each ICU could build its own predictive models based on its own patient database, because this methodology is able to take into account the specific local situation, and can be adapted and recalibrated over time.
Because this methodology is capturing health literacy at the population level, there is no sample selection bias, thus we are isolating the effect of health literacy without introducing pre-selection bias.
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Information gained through this methodology is essential because new techniques and innovations often gain rapid acceptance before clinical trials can be conducted to assess them.
This methodology is useful because it allows geographic range to be measured relative to a time-varying quantity: the total area of preserved marine shelf environments.
This methodology is effective because it is expected that the absence of the transporter in the mutant strain makes this strain resistant to the effects of the toxic substrate given that the substrate will not be internalized by the bacterium.
Finally, this methodology is potentially biased because the reviewer may be influenced by patient outcome [ 5, 10].
This methodology is critically important, because it shows profound implications for both structural and temporal alterations accompanying a given conformational transition of a fluctuating protein nanopore.
However, because this methodology was applied to the serotype specific PP analyses in an earlier publication, it is applied here to the MITT analyses to be consistent.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com