Webinar Series on Child Welfare Administrative Data and Program Sustainability

This first webinar discusses strategies for mining administrative data to assess the characteristics and needs of at-risk child welfare populations. Using examples from a federal Permanency Innovations Initiative (PII) grantee in Illinois, Dr. Dana Weiner identifies the key requirements of productive data mining, steps in the data mining process, and useful statistical techniques for analyzing and making sense of administrative data.

This second webinar discusses propensity score matching (PSM) as a methodologically rigorous alternative to randomized controlled trials (RCTs). Using examples of grantees funded through the federal Permanency Innovations Initiative (PII), Mr. Andrew Barclay discusses the theory underlying PSM, techniques for implementing PSM and validating the results, and caveats and limitations of this statistical technique.

This third webinar reviews strategies for using evaluation findings to help sustain program and evaluation activities following the end of federal funding. The sustainability planning and activities of two grantees funded through the federal Permanency Innovations Initiative (PII) – North Carolina Department of Social Services (funded in 2011 for five years) and Western Michigan University (funded in 2012 for five years) – are reviewed and discussed in detail.

Metadata-only record linking to the original dataset. Open original dataset below.

Data e Risorse

Campo Valore
accessLevel public
bureauCode {009:70}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_@id https://healthdata.gov/data.json
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier https://healthdata.gov/api/views/6paa-skr4
issued 2025-09-04
landingPage https://healthdata.gov/d/6paa-skr4
modified 2025-09-05
programCode {009:045}
publisher Administration for Children and Families
resource-type Dataset
source_datajson_identifier true
source_hash 3cc4efcbf36f9f4ccabab84b0567b23abfdfed2a65caef4b7bb63651873266e6
source_schema_version 1.1
theme {ACF}
Gruppi
  • AmeriGEOSS
  • National Provider
  • North America
Tag
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • assessment
  • data
  • grant
  • policy
  • reporting
isopen False
license_id notspecified
license_title License not specified
maintainer ACF Data Team
maintainer_email ohsepr@acf.hhs.gov
metadata_created 2025-09-24T18:05:20.228240
metadata_modified 2025-09-24T18:05:20.228251
notes This first webinar discusses strategies for mining administrative data to assess the characteristics and needs of at-risk child welfare populations. Using examples from a federal Permanency Innovations Initiative (PII) grantee in Illinois, Dr. Dana Weiner identifies the key requirements of productive data mining, steps in the data mining process, and useful statistical techniques for analyzing and making sense of administrative data. This second webinar discusses propensity score matching (PSM) as a methodologically rigorous alternative to randomized controlled trials (RCTs). Using examples of grantees funded through the federal Permanency Innovations Initiative (PII), Mr. Andrew Barclay discusses the theory underlying PSM, techniques for implementing PSM and validating the results, and caveats and limitations of this statistical technique. This third webinar reviews strategies for using evaluation findings to help sustain program and evaluation activities following the end of federal funding. The sustainability planning and activities of two grantees funded through the federal Permanency Innovations Initiative (PII) – North Carolina Department of Social Services (funded in 2011 for five years) and Western Michigan University (funded in 2012 for five years) – are reviewed and discussed in detail. Metadata-only record linking to the original dataset. Open original dataset below.
num_resources 1
num_tags 13
title Webinar Series on Child Welfare Administrative Data and Program Sustainability