Abstract
We develop robust targeted maximum likelihood estimators (TMLEs) for transporting intervention effects from one population to another. Specifically, we develop TMLEs for three transported estimands: the intent-to-treat average treatment effect (ATE) and complier ATE, which are relevant for encouragement design interventions and instrumental variable analyses, and the ATE of the exposure on the outcome, which is applicable to any randomized or observational study. We demonstrate finite sample performance of these TMLEs by using simulation, including in the presence of practical violations of the positivity assumption. We then apply these methods to the ‘Moving to opportunity’ trial: a multisite, encouragement design intervention in which families in public housing were randomized to receive housing vouchers and logistical support to move to low poverty neighbourhoods. This application sheds light on whether effect differences across sites can be explained by differences in population composition.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1509-1525 |
| Number of pages | 17 |
| Journal | Journal of the Royal Statistical Society. Series B: Statistical Methodology |
| Volume | 79 |
| Issue number | 5 |
| DOIs | |
| State | Published - Nov 1 2017 |
| Externally published | Yes |
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Keywords
- Causal inference
- External validity
- Instrumental variables
- Policy intervention
- Targeted maximum likelihood estimation
- Transportability
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
Cite this
Robust estimation of encouragement design intervention effects transported across sites. / Rudolph, Kara; van der Laan, Mark J.
In: Journal of the Royal Statistical Society. Series B: Statistical Methodology, Vol. 79, No. 5, 01.11.2017, p. 1509-1525.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Robust estimation of encouragement design intervention effects transported across sites
AU - Rudolph, Kara
AU - van der Laan, Mark J.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - We develop robust targeted maximum likelihood estimators (TMLEs) for transporting intervention effects from one population to another. Specifically, we develop TMLEs for three transported estimands: the intent-to-treat average treatment effect (ATE) and complier ATE, which are relevant for encouragement design interventions and instrumental variable analyses, and the ATE of the exposure on the outcome, which is applicable to any randomized or observational study. We demonstrate finite sample performance of these TMLEs by using simulation, including in the presence of practical violations of the positivity assumption. We then apply these methods to the ‘Moving to opportunity’ trial: a multisite, encouragement design intervention in which families in public housing were randomized to receive housing vouchers and logistical support to move to low poverty neighbourhoods. This application sheds light on whether effect differences across sites can be explained by differences in population composition.
AB - We develop robust targeted maximum likelihood estimators (TMLEs) for transporting intervention effects from one population to another. Specifically, we develop TMLEs for three transported estimands: the intent-to-treat average treatment effect (ATE) and complier ATE, which are relevant for encouragement design interventions and instrumental variable analyses, and the ATE of the exposure on the outcome, which is applicable to any randomized or observational study. We demonstrate finite sample performance of these TMLEs by using simulation, including in the presence of practical violations of the positivity assumption. We then apply these methods to the ‘Moving to opportunity’ trial: a multisite, encouragement design intervention in which families in public housing were randomized to receive housing vouchers and logistical support to move to low poverty neighbourhoods. This application sheds light on whether effect differences across sites can be explained by differences in population composition.
KW - Causal inference
KW - External validity
KW - Instrumental variables
KW - Policy intervention
KW - Targeted maximum likelihood estimation
KW - Transportability
UR - http://www.scopus.com/inward/record.url?scp=85000501907&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85000501907&partnerID=8YFLogxK
U2 - 10.1111/rssb.12213
DO - 10.1111/rssb.12213
M3 - Article
AN - SCOPUS:85000501907
VL - 79
SP - 1509
EP - 1525
JO - Journal of the Royal Statistical Society. Series B: Statistical Methodology
JF - Journal of the Royal Statistical Society. Series B: Statistical Methodology
SN - 1369-7412
IS - 5
ER -