TY - JOUR
T1 - TrendPowerTool
T2 - A lookup tool for estimating the statistical power of a monitoring program to detect population trends
AU - Weiser, Emily L.
AU - Diffendorfer, Jay E.
AU - Lopez-Hoffman, Laura
AU - Semmens, Darius
AU - Thogmartin, Wayne E.
N1 - Funding Information: We thank Joel Putnam and Aaron Fox for developing the platform to host the shiny app for TrendPowerTool; T. Wilson, B. Verheijen, J. Lamb, B. Ross, and L. Rosen for comments on the app interface; and B. Gray and two anonymous reviewers for comments on a previous draft of this manuscript. This research used resources provided by the Core Science Analytics, Synthesis, & Libraries (CSASL) Advanced Research Computing (ARC) group at the U.S. Geological Survey. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Publisher Copyright: © 2021 The Authors. Conservation Science and Practice published by Wiley Periodicals LLC. on behalf of Society for Conservation Biology
PY - 2021/7
Y1 - 2021/7
N2 - A simulation-based power analysis can be used to estimate the sample sizes needed for a successful monitoring program, but requires technical expertise and sometimes extensive computing resources. We developed a web-based lookup app, called TrendPowerTool (https://www.usgs.gov/apps/TrendPowerTool/), to provide guidance for ecological monitoring programs when resources are not available for a simulation-based power analysis. TrendPowerTool is implemented through the shiny package in R, but is accessible through a webpage without the need for users to install any software. By drawing on results of 1.4 million scenarios that we simulated on a supercomputer, TrendPowerTool quickly and easily provides an estimate of the statistical power to detect a population trend of a particular magnitude with a planned monitoring program, based on user-specified parameters for the monitoring design and population of interest. TrendPowerTool provides a user-friendly interface that retrieves results instantaneously, facilitating the important step of conducting a power analysis when designing monitoring programs.
AB - A simulation-based power analysis can be used to estimate the sample sizes needed for a successful monitoring program, but requires technical expertise and sometimes extensive computing resources. We developed a web-based lookup app, called TrendPowerTool (https://www.usgs.gov/apps/TrendPowerTool/), to provide guidance for ecological monitoring programs when resources are not available for a simulation-based power analysis. TrendPowerTool is implemented through the shiny package in R, but is accessible through a webpage without the need for users to install any software. By drawing on results of 1.4 million scenarios that we simulated on a supercomputer, TrendPowerTool quickly and easily provides an estimate of the statistical power to detect a population trend of a particular magnitude with a planned monitoring program, based on user-specified parameters for the monitoring design and population of interest. TrendPowerTool provides a user-friendly interface that retrieves results instantaneously, facilitating the important step of conducting a power analysis when designing monitoring programs.
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U2 - 10.1111/csp2.445
DO - 10.1111/csp2.445
M3 - Article
SN - 2578-4854
VL - 3
JO - Conservation Science and Practice
JF - Conservation Science and Practice
IS - 7
M1 - e445
ER -