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sparrpowR-package.Rd
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/package.R
\docType{package}
\name{sparrpowR-package}
\alias{sparrpowR-package}
\alias{sparrpowR}
\title{The sparrpowR Package: Power Analysis to Detect Spatial Relative Risk Clusters}
\description{
Computes the statistical power for the spatial relative risk function.
}
\details{
For a two-group comparison (e.g., cases v. controls) the 'sparrpowR' package calculates the statistical power to detect clusters using the kernel-based spatial relative risk function that is estimated using the 'sparr' package. Details about the 'sparr' package methods can be found in the tutorial: Davies et al. (2018) \doi{10.1002/sim.7577}. Details about kernel density estimation can be found in J. F. Bithell (1990) \doi{10.1002/sim.4780090616}. More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) \doi{10.1002/sim.4780101112}.
This package provides a function to compute the statistical power for the spatial relative risk function with various theoretical spatial sampling strategies. The 'sparrpowR' package also provides a function to compute the statistical power for the spatial relative risk function for scenarios where one group (e.g., cases) have been observed and a theoretical sampling strategy for the second group (e.g., controls) is desired. The 'sparrpowR' package also provides visualization of data and statistical power.
Key content of the 'sparrpowR' package include:\cr
\bold{Theoretical Spatial Sampling}
\code{\link{spatial_data}} Generates random two-group data for a spatial relative risk function.
\bold{Statistical Power}
\code{\link{spatial_power}} Computes the statistical power of a spatial relative risk function using randomly generated data.
\code{\link{jitter_power}} Computes the statistical power of a spatial relative risk function using previously collected data.
\bold{Data Visualization}
\code{\link{spatial_plots}} Visualizes multiple plots of output from \code{\link{spatial_data}}, \code{\link{spatial_power}} and \code{\link{jitter_power}} functions.
}
\section{Dependencies}{
The 'sparrpowR' package relies heavily upon \code{\link{sparr}}, \code{\link{spatstat.random}}, \code{\link{spatstat.geom}}, and \code{\link{terra}} for computing the statistical power and visualizing the output. Computation can be performed in parallel using \code{\link{doFuture}}, \code{\link[future]{multisession}}, \code{\link{doRNG}}, and \code{\link[foreach]{foreach}}. Basic visualizations rely on the \code{\link[spatstat.geom]{plot.ppp}} and \code{\link[fields]{image.plot}} functions.
}
\author{
Ian D. Buller\cr \emph{Social & Scientific Systems, Inc., a division of DLH Corporation, Silver Spring, Maryland, USA (current); Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA (original)}\cr
Maintainer: I.D.B. \email{[email protected]}
}
\keyword{package}