Spatial Power is a web application that calculates the power for spatial statistics. Currently, the tool has one module for the spatial relative risk function. Derek Brown, PhD, MS and I co-designed the web application with a development team from the NCI Center for Biomedical Informatics & Information Technology.
I co-first authored an article in the International Journal of Health Geographics entitled “sparrpowR: a flexible R package to estimate statistical power to identify spatial clustering of two groups and its application”.
I co-authored an article in the International Journal of Environmental Research and Public Health entitled “Spatial Heterogeneity in Positional Errors: A Comparison of Two Residential Geocoding Efforts in the Agricultural Health Study”, which is included in the Special Issue Spatial Data Uncertainty in Public Health Research.
Derek Brown, PhD, MS and I received a Trans-Fellowship Research Award from the NCI Division of Cancer Prevention Cancer Prevention Fellowship Program to supplement our 2020 DCEG Informatics Tool Challenge Award.
Derek Brown, PhD, MS and I presented our “Spatial Power” webtool for the NCI Division of Cancer Epidemiology and Genetics January 2021 monthly Geographic Analysis Working Group meeting. Spatial Power is an upcomping webtool to calculate power for spatial statistics.
My third R package is on CRAN named envi. It estimates the ecological niche using presence/absence data and the spatial relative risk function via the sparr package. See the public Github repository for more details.
My second R package is on CRAN named gateR. It estimates clustering of cytometry cells using markers and the spatial relative risk function via the sparr package. See the public Github repository for more details.
I present code to create the hexsticker for the sparrpowR package using the hexSticker and spatstat packages. The sparrpowR calculated the statistical power for a spatial relative risk function from the sparr package.
My first R package is on CRAN named sparrpowR. It provides a statistical power calculation for the spatial relative risk function via the sparr package. See the public Github repository for more details.
I present code to identify areas of a spatial segregation model that exceed our null expectations using the relrisk function in the spatstat package and an assumption of normality of the estimated probabilities.