Ordinary Least Squares Standard Residuals, Moran’s I, and Spatial Autocorrelation Report for Breast Cancer Cases and Covariates in the Four Corner States, 2017

Dublin Core

Title

Ordinary Least Squares Standard Residuals, Moran’s I, and Spatial Autocorrelation Report for Breast Cancer Cases and Covariates in the Four Corner States, 2017

Subject

This image displays an Ordinary Least Squares Standard Residuals map with statistics from an Ordinary Least Squares diagnostic, a spatial autocorrelation report calculated from a Moran’s I, and a description of each figure for breast cancer cases in counties of Arizona, Colorado, New Mexico, and Utah with poverty status and educational attainment as covariates for the year of 2017.

Description

Included in this image is Figure 1, an Ordinary Least Squares (OLS) and spatial autocorrelation (Moran’s I) analysis on the standard residuals for breast cancer cases in each county and the corresponding covariates of poverty status and educational attainment. Figure 1 contains the OLS standard residuals for each county using a scale of -2.5 standard deviations to 2.5 standard deviations. In Figure 3 contains the spatial autocorrelation report which explains the results found in Figure 1. The scale in Figure 3 contains z-scores ranging from -2.58 to 2.58 which corresponds to a specific p-value, indicating the significance level. The Moran’s Index is 0.145436 with a z-score of 5.048261, and a p-value of 0.0000001. As indicated on the graph in Figure 3, the results found in the OLS and spatial autocorrelation report is significant and indicates clustering. Looking at Figure 1, in Arizona there are three counties with a standard deviation above 0.5, which look like a cluster. In Figure 2, the statistics in the OLS diagnostics do not show much significance, except for the Jarque-Bera statistic. The Jarque-Bera statistic has a p-value of 0.0000001, which is less than an alpha of 0.05 for a 95% confidence level. Thus, meaning that the residuals have statistical significance because they are not normally distributed. The z-score in Figure 3 was 5.048261, this means there is a less than 1% likelihood that this clustered pattern could be a result of random chance.

Creator

Bailey Beare

Source

Basemap Data: Esri, DeLorme, HERE, TomTom, Intermap, increment P Corp., GEBCO, USGS, FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey, Esri Japan, METI, Esri China (Hong Kong), swisstopo, MapmyIndia, and the GIS User Community
Breast Cancer Cases Data: The breast cancer cases data was downloaded on November 10th, 2020 from the United States Cancer Statistics database on the Centers for Disease Control and Prevention website from the year 2017. Data for this map included new cases of breast cancer for Arizona, Colorado, New Mexico, and Utah.
Poverty Status Data: The percent of females below poverty status data was downloaded on November 10th, 2020 from the United States Census Bureau website from the year 2017, and included data on percent of females below poverty level from Arizona, Colorado, New Mexico, and Utah.
Education Data: The education data for each of these counties was downloaded on November 10th, 2020 from the Unites States Census Bureau's website for the year of 2017, and included data on percent of females with less than a high school degree from Arizona, Colorado, New Mexico, and Utah.
County Level Data: The county level data used for this map was downloaded on November 10th, 2020 from the TIGER/Line Shapefiles database for the year 2017. Every county in the United States was included in the shapefile, but in ArcGIS only the counties in Arizona, Colorado, New Mexico, and Utah were included in the map.

Publisher

Website maintained by Chantel Sloan, Associate Professor in the Public Health Department at Brigham Young University

Date

Date included in the map is the year 2017.

Contributor

Bailey Beare

Rights

Basemap data is ESRI owned. The breast cancer cases data is owned by the United States Cancer Statistics, National Cancer Institute, and the Centers for Disease Control and Prevention. The poverty level data is owned by the United States Census Bureau. The educational attainment data is owned by the United States Census Bureau. The county level shapefile is owned by the United States Census Bureau.

Relation

N/A

Format

PDF

Language

English

Type

Map file generated using ArcGIS Pro

Coverage

This map is a 1:7,892,766 map showing the Four Corner states, and their county boundaries.

Files

OLSBreastCancer.pdf

Reference

Bailey Beare, Ordinary Least Squares Standard Residuals, Moran’s I, and Spatial Autocorrelation Report for Breast Cancer Cases and Covariates in the Four Corner States, 2017, Website maintained by Chantel Sloan, Associate Professor in the Public Health Department at Brigham Young University, Date included in the map is the year 2017.