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Resource Library

Guides. Briefs. Toolkits. Quick reference information. IDC and its partners created these data quality resources to help states better prepare to address their existing or emerging IDEA data quality needs. Use our search and filtering tools to navigate the library.

Resources 1 - 4 of 4

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    An IDC Resource

    Format: Quick Reference

    Response Rate, Representativeness, and Nonresponse Bias—They All Matter!

    Response rate and representativeness are important terms in survey work.  Consideration of both is necessary to ensure that collected data are valid and generalizable.  This resource briefly defines and compares the terms while also explaining how they relate to nonresponse bias. 

    An IDC Resource

    Format: Quick Reference

    SPP/APR Indicator Card

    The SPP/APR indicators measure child and family outcomes as well as compliance with the requirements of IDEA. This quick-reference resource from IDC includes a list and brief definition of all the Part B FFY 2020–2025 SPP/APR indicators (including the new Indicator 18!), as well as a list of file specifications associated with each of the seven IDEA 618 data collections, all in one convenient package.

    An IDC Resource

    Format: Quick Reference

    Due Dates for SY 2022-23 IDEA Data

    IDC updates this list of EDFacts Submission System (ESS) files and EMAPS submissions due dates for SY 2022-23 so you don't have to! Download it and pin it to your refrigerator where it'll help you stay cool.

    An IDC Resource

    Format: Quick Reference

    Checklist to Identify and Address SSIP Data Quality Issues

    In State Performance Report/Annual Performance Plan (SPP/APR) reports, states are required to identify data quality issues that may have arisen during their Indicator 17 State Systemic Improvement Plan (SSIP) work. Using this checklist can help state staff who are responsible for the SSIP apply the principles of high-quality data to identify any data quality issues that the state should report. The checklist includes questions that states can ask themselves to recognize data quality issues that may exist. It provides potential consequences of the issues and offers suggested actions that states can take to address the issues.