TY - JOUR
T1 - Bias? Clarifying the language barrier between epidemiologists and economists
AU - Varga, Anita Natália
AU - Guevara Morel, Alejandra E.
AU - van Dongen, Hanneke
AU - Lokkerbol, Joran
AU - Bosmans, Judith E.
AU - Lindeboom, Maarten
AU - van Tulder, Maurits
AU - Bouter, Lex
AU - Bosmans, Judith E.
AU - Bosmans, Je
N1 - Funding Information: This funding was provided by ZonMw (Grant No. 91717368), Prof Dr Judith E Bosmans. Publisher Copyright: © 2022, The Author(s).
PY - 2023/9
Y1 - 2023/9
N2 - In health intervention research, epidemiologists and economists are more and more interested in estimating causal effects based on observational data. However, collaboration and interaction between both disciplines are regularly clouded by differences in the terminology used. Amongst others, this is reflected in differences in labeling, handling, and interpreting the sources of bias in parameter estimates. For example, both epidemiologists and economists use the term selection bias. However, what economists label as selection bias is labeled as confounding by epidemiologists. This paper aims to shed light on this and other subtle differences between both fields and illustrate them with hypothetical examples. We expect that clarification of these differences will improve the multidisciplinary collaboration between epidemiologists and economists. Furthermore, we hope to empower researchers to select the most suitable analytical technique from either field for the research problem at hand.
AB - In health intervention research, epidemiologists and economists are more and more interested in estimating causal effects based on observational data. However, collaboration and interaction between both disciplines are regularly clouded by differences in the terminology used. Amongst others, this is reflected in differences in labeling, handling, and interpreting the sources of bias in parameter estimates. For example, both epidemiologists and economists use the term selection bias. However, what economists label as selection bias is labeled as confounding by epidemiologists. This paper aims to shed light on this and other subtle differences between both fields and illustrate them with hypothetical examples. We expect that clarification of these differences will improve the multidisciplinary collaboration between epidemiologists and economists. Furthermore, we hope to empower researchers to select the most suitable analytical technique from either field for the research problem at hand.
KW - Confounding
KW - Endogeneity
KW - Epidemiology
KW - Health economics
KW - Omitted variable bias
KW - Selection bias
UR - https://research.vu.nl/ws/files/194567328/2.540.pdf
UR - http://www.scopus.com/inward/record.url?scp=85141123862&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s10742-022-00291-x
DO - https://doi.org/10.1007/s10742-022-00291-x
M3 - Article
SN - 1387-3741
VL - 23
SP - 354
EP - 375
JO - Health Services and Outcomes Research Methodology
JF - Health Services and Outcomes Research Methodology
IS - 3
ER -