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~person:"Abowd, John M."
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Abowd, John M.
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Finding needles in haystacks:
Multiple-imputation
record linkage using machine learning
Abowd, John M.
;
Abramowitz, Joelle
;
Levenstein, Margaret
; …
-
2022
linkage methodology that combines machine learning (ML) with
multiple
imputation
(MI). This ML-MI methodology is applied to …
Persistent link: https://www.econbiz.de/10014304782
Saved in:
2
Finding needles in haystacks :
multiple-imputation
record linkage using machine learning
Abowd, John M.
;
Abramowitz, Joelle
;
Levenstein, Margaret
; …
-
2022
-
This version: October 2021
linkage methodology that combines machine learning (ML) with
multiple
imputation
(MI). This ML-MI methodology is applied to …
Persistent link: https://www.econbiz.de/10013387479
Saved in:
3
Total error and variability measures for the quarterly workforce indicators and LEHD origin-destination employment statistics in OnTheMap
McKinney, Kevin L.
;
Green, Andrew S.
;
Vilhuber, Lars
; …
-
2020
Persistent link: https://www.econbiz.de/10012312994
Saved in:
4
Total error and variability measures with integrated disclosure limitation for quarterly workforce indicators and LEHD origin destination employment statistics in OnTheMap
McKinney, Kevin L.
;
Green, Andrew S.
;
Vilhuber, Lars
; …
-
2017
Persistent link: https://www.econbiz.de/10011801384
Saved in:
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