This layer is symbolized to show the approximate percentage of households that are multigenerational households. Multigenerational households are households with three or more generations. These households include either (1) a householder, a parent or parent-in-law of the householder, and an own child of the householder, (2) a householder, an own child of the householder, and a grandchild of the householder, or (3) a householder, a parent or parent-in-law of the householder, an own child of the householder, and a grandchild of the householder. The householder is a person in whose name the home is owned, being bought, or rented, and who answers the survey questionnaire as person 1.Other fields included are estimates of mothers - females 18 to 64 with own children (biological, adopted, or step children) - by various race/ethnic groups, and by age group of children. Age groups were defined by the COVID vaccine age groups: 12 to 17, 5 to 11, and 0 to 4. We also included estimates for mothers of children in more than one of these groups.Data prep steps:Data downloaded on 4/5/22 from FTP site.All fields were calculated from the Census Bureau's 2016-2020 5-year American Community Survey Public Use Microdata Sample (PUMS) using this SAS program.Using the SAS-ArcGIS Bridge, the data table created in SAS was read into ArcGIS Pro and joined to this layer is PUMA, obtained from Living Atlas. According to the U.S. Census Bureau, a Public Use Micro-sample Area (PUMA) is a "non-overlapping, statistical geographic areas that partition each state or equivalent entity into geographic areas containing no fewer than 100,000 people each." The resulting layer in Pro was then published to ArcGIS Online.Disclaimer: All estimates here contain a margin of error. While they are not explicitly calculated and provided on this layer currently, we can and will add additional fields to provide the margins of error if the need arises.

This repository is a comprehensive resource accompanying the paper "Receiving Investors in the Block Market for Corporate Bonds" by Stacey Jacobsen and Kumar Venkataraman. It includes source codes and small-sample (masked) input datasets for replicating the study’s analysis on block trading costs in the corporate bond market. To effectively use this repository, users must download the sample datasets and adjust the directory paths within the SAS and Stata code to match their local environment. Because the data sources are non-public, the original bond identifiers have been removed and replaced by randomly generated identifiers in the sample datasets. Because small sample datasets are provided, the replicator should expect the code to run in less than ten minutes. The replicator should run the SAS code in the first step then the STATA code in the second step.

This repository provides the software and data for the paper

Causemann, M., Kuchta, M., Masri, R., & Rognes, M. E. (2025). In-silico molecular enrichment and clearance of the human intracranial space.

In particular, it contains the following data:

Class means on canonical variables of female and male chickens.

Comparing the Shenoy et al [21] algorithm for low-value urinalysis and important diagnosis codes in the HSR Definition Builder application.

Results for the tree classification models for our example services.

Preliminary exclusion criteria for inpatient fusion of lumbar vertebral joint (ICD-10 codes 0SG0-x).

It is an SAS file with all the syntax used for statistical analysis. (SAS)

Top 21 of 132 diagnosis codes for carrier claims with a knee arthroscopy procedure (CPT 29877), ordered by relative importance from the classification model.

It is an SAS file with all the syntax used for statistical analysis of breeding practices of donkey farmers’ data. (SAS)

The selected example codes and their definitions.

Traits used in discriminating the chicken population from different sites in stepwise discriminant analysis.

It is an SAS file with all the syntax used for statistical analysis of socio-economic characteristics of donkey farmers’ data. (SAS)