Type:	Package
Title:	Methods of Applied Psychology and Psychometrics in Geographical Analysis
Version:	0.1.0
Description:	Integrating applied psychological and psychometric methods into geographical analysis. With the emergence of geo-referenced questionnaires, spatially explicit psychological and psychometric methods can offer a geographically contextualised approach that reflects latent traits and processes at a more local scale, leading to more tailored research and decision-making processes. The implemented methods include Geographically Weighted Cronbach's alpha and its bandwidth selection. See Zhang & Li (2025) <doi:10.1111/gean.70021>.
License:	GPL (≥ 3)
Encoding:	UTF-8
LazyData:	true
RoxygenNote:	7.3.3
URL:	https://github.com/ZhangSui921/geopsych
Depends:	R (≥ 3.5)
Imports:	sp
NeedsCompilation:	no
Packaged:	2025-11-28 11:37:42 UTC; f89389sz
Author:	Sui Zhang [aut, cre]
Maintainer:	Sui Zhang <sui.zhang@manchester.ac.uk>
Repository:	CRAN
Date/Publication:	2025-12-03 20:50:02 UTC

Georeferenced responses of Neighborhood Social Capital Scale from BES2011

Description

Responses of the Neighborhood Social Capital Scale (NSCS) from Baltimore Ecosystem Study (BES) Household Telephone Survey Wave 5 (2011), which excluded the samples from Queen Anne's County. The responses were geocoded and transformed to a SpatialPointsDataFrame.

Usage

data("bes2011")

Format

a SpatialPolygonsDataFrame with 1,410 responses on the following 5 items:

willHelp

People in the neighborhood are willing to help one another

closeKnit

This is a close knit neighborhood

trust

People in this neighborhood can be trusted

solComProb

There are many opportunities to meet neighbors and work on community problems

relGroups

Churches, temples and other volunteer groups actively support the neighborhood

Source

Cary Institute Of Ecosystem Studies, M. Grove, and D. Locke. 2018. BES Household Telephone Survey ver 180. Environmental Data Initiative.

Examples

data("bes2011")

Bandwidth Selection for Geographically Weighted Cronbach's Alpha

Description

A function for automatic bandwidth selection to calibrate GWalpha.

Usage

bw_gwalpha(crit, minmax, adaptive = TRUE, tol = 3, max_iter = 100, ...)

Arguments

Value

a adaptive or fixed distance bandwidth

See Also

gwalpha()

Geographically Weighted Cronbach's Alpha

Description

This function computes geographically weighted cronbach's alpha (GWalpha) for responses from georeferenced multi-item survey scales.

Usage

gwalpha(
  x,
  data,
  kernel = "bisquare",
  adaptive = TRUE,
  bw,
  ci = FALSE,
  p = 0.95,
  nsims = 1000
)

Arguments

Value

a data frame with:

References

Zhang, S., and Z. Li. 2025. “ Geographically Weighted Cronbach's Alpha (GWalpha): An Exploratory Local Measure of Reliability for Scale Construction.” Geographical Analysis 57, no. 4: 758–772.

See Also

bw_gwalpha()

Examples

data(bes2011)
alpha100 <- gwalpha(
  x = c("willHelp", "closeKnit", "trust", "solComProb", "relGroups"),
  data = bes2011,
  bw = 100
  )

Counting the Number of GWalpha below Criterion

Description

an internal function for counting how many responses have an upper confidence bound below a user-specified criterion for reliability level.

Usage

sum_gwalpha(bw, crit, ...)

Arguments

Value

the number of responses where the upper confidence bound of GWalpha is below crit.