Quantifying sources of bias in longitudinal data linkage studies of child abuse and neglect: measuring impact of outcome specification, linkage error, and partial cohort follow-up-Reference-Cited by-同舟云学术

Quantifying sources of bias in longitudinal data linkage studies of child abuse and neglect: measuring impact of outcome specification, linkage error, and partial cohort follow-up

Published:2017-08-07 Issue:1 Volume:4 Page:
ISSN:2197-1714
Container-title:Injury Epidemiology
language:en
Short-container-title:Inj. Epidemiol.

Author:

Parrish Jared W.,Shanahan Meghan E.,Schnitzer Patricia G.,Lanier Paul,Daniels Julie L.,Marshall Stephen W.

Funder

Maternal and Child Health Bureau

Travis Fund

National Center for Injury Prevention and Control

Centers for Disease Control and Prevention

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

Link

http://link.springer.com/content/pdf/10.1186/s40621-017-0119-6.pdf

Reference61 articles.

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2. Bertolli J, Morgenstern H, Sorenson SB. Estimating the occurrence of child maltreatment and risk-factor effects: benefits of a mixed-design strategy in epidemiologic research. Child Abuse Negl. 1995;19(8):1007–16.

3. Bohensky M. Bias in data linkage studies. Methodological Developments in Data Linkage. 2016:63–82.

4. Brownell MD, Jutte DP. Administrative data linkage as a tool for child maltreatment research. Child Abuse Negl. 2013;37(2):120–4.

5. Butchart A, Harvey AP, Mian M, Furniss T. Preventing child maltreatment: a guide to taking action and generating evidence. 2006.

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