NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS

NATIONAL SCIENCE FOUNDATION

Discussion

Data Driven Insights: The Utility and 

Policy Building of Integrated Data from 

Federal Statistical Agencies

Lisa B. Mirel

FCSM 2023

October 26, 2023: 10.30 AM
NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

Disclaimer

• The views expressed in this presentation are those of 

the author and do not necessarily reflect the views of 

the National Center for Science and Engineering 

Statistics or the National Science Foundation

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NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

Linking Data

• A powerful and efficient mechanism for producing 

policy-relevant information

o Brings together information to create a new, richer resource

o Allows for the construction of longitudinal data with passive 

follow-up

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NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

Factors to Consider in Data Linkage

• Linkage eligibility (e.g., consent, sufficient personally 

identifiable information)

• Linkage error

• Analytic considerations

o Data quality 

o Disclosure risks

o Coverage

o Data limitations and inference

o Timeliness

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NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

Three Diverse Linkage Talks

• National Center for Science and Engineering 

Statistics

o Linking the Policy and Utility of Linked Data in Science and 

Engineering (Finamore)

• National Center for Health Statistics

o Does the Decade Matter? Examining the Impact of Using 

Geocodes from Different Decades in the Analysis of Merged 

Survey and Contextual Data (Parker)

o Using Linked Data to Train and Validate Machine Learning 

Prediction Models (Davy)

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NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

• Recent NCSES data 

linkage efforts 

o Development of a policydriven research and 

linkage framework

o Insights on the way 

forward in this critical field 

of data integration

o What lessons can be 

learned from others?

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Linking the Policy and Utility of Linked 

Data in Science and Engineering 
NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

• Geocoded survey data allow 

researchers to merge survey data 

with geographic information from 

other sources to add contextual 

information

• Geocodes change with each 

decennial Census

• Time period of the geocodes 

should be carefully considered 

because they may impact results 

due to real change over time 

and/or administrative changes 

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Does the Decade Matter? 
NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

• When data linkage is not possible, 

machine learning (ML) prediction 

models can be used to predict 

outcomes, such as morbidity and 

mortality

• ML models require high quality, 

accurate training data and a 

validation source

• ML models perform reasonably well 

for predicting all-cause mortality

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Using Linked Data to Train and Validate 

Machine Learning Prediction Models 
NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

Takeaways and Common Themes 

• Establishing a robust linkage program requires many 

analytic and practical considerations

• By augmenting information, linked survey and 

administrative information facilitate richer analyses

• Quality assessments of linked data are important for 

inference and training datasets

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NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

Discussion Points

• What are key policies that need to be considered when 

establishing a robust linkage program?

• Are linkages, whether entity to entity or geocoded 

data, being considered to replace information that 

could be collected through survey questions?

• If linked data were to be used as a training data set for 

a ML model how often would they need to be 

updated? 

o What skills are needed to keep the training dataset up to 

date?

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NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

Discussion Points cont.

• Are considerations being given to utilize linkages to 

inform data collection (e.g., adaptive design)? 

• What information is missing from the surveys 

discussed that would benefit from linking to another 

source to support evidence-based policymaking?

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NATIONAL CENTER FOR SCIENCE AND ENGINEERING STATISTICS 

https://ncses.nsf.gov

Final Thoughts

• Continue to identify and integrate the data needed to 

inform key policy questions

• Utilize innovative technologies and data sources

• Evaluate alternative data sources for linkages and uses of 

linked data

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@NCSESgov

https://ncses.nsf.gov 13

Lisa B. Mirel

Email address: lbmirel@nsf.gov