To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Several malaria control measures aim to reduce infection levels in mosquitoes, and evaluation of these measures usually relies on experimental infections of mosquitoes or evaluation in field populations. Both require robust statistical tools to account for multiple variables and non-normal distributions of parasites in the vector host. We argue that a well-chosen generalized linear or mixed model is the most appropriate statistical tool for analysing and interpreting these biological data. We suggest specific methods to overcome datasets where some groups have zero/close to zero prevalence, or many zero counts of parasite numbers (as would be seen with an effective transmission blocking intervention). These methods are more broadly applicable across many parasitic infections with similar patterns of parasite numbers across hosts.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.