BioOne.org will be down briefly for maintenance on 13 August 2025 between 18:00-21:00 Pacific Time US. We apologize for any inconvenience.
Registered users receive a variety of benefits including the ability to customize email alerts, create favorite journals list, and save searches.
Please note that a BioOne web account does not automatically grant access to full-text content. An institutional or society member subscription is required to view non-Open Access content.
Contact helpdesk@bioone.org with any questions.
We investigate the procedure of checking for overlap between confidence intervals or standard error intervals to draw conclusions regarding hypotheses about differences between population parameters. Mathematical expressions and algebraic manipulations are given, and computer simulations are performed to assess the usefulness of confidence and standard error intervals in this manner. We make recommendations for their use in situations in which standard tests of hypotheses do not exist. An example is given that tests this methodology for comparing effective dose levels in independent probit regressions, an application that is also pertinent to derivations of LC50s for insect pathogens and of detectability half-lives for prey proteins or DNA sequences in predator gut analysis.
This article is only available to subscribers. It is not available for individual sale.
Access to the requested content is limited to institutions that have
purchased or subscribe to this BioOne eBook Collection. You are receiving
this notice because your organization may not have this eBook access.*
*Shibboleth/Open Athens users-please
sign in
to access your institution's subscriptions.
Additional information about institution subscriptions can be foundhere
