Aaron Schiff’s scientific contributions

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Publications (1)


Figure 2.1 Factors to consider in causal inference analysis 
Figure 4.2 Propensity score distribution 
Figure 4.4 Count of car fatalities and injuries by city central area 
Figure 4.6 Fatal crashes in New York and Pennsylvania 
Figure 4.5 Fraction of individuals reporting drunk driving in the Ontario student drug use survey 

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Ex- post evaluation of transport interventions using causal inference methods
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October 2017

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1,879 Reads

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4 Citations

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Aaron Schiff

This report gives guidance for empirical ex-post evaluation of projects, policies, and other interventions in the transport sector. We focus on statistical methods that are designed to estimate the effects caused by an intervention, known as methods of ‘causal inference’. There are many causal inference methods and we provide guidance for selecting a method depending on the data that is available and the type of intervention being evaluated.

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Citations (1)


... Predictive approaches aim to elucidate causal relationships by evaluating associations between explanatory and response variables. However, predictive relationships between variables do not necessarily imply a causal relationship, as other variables (confounders) can influence explanatory and response variables [39]. Causal inference, on the other hand, is concerned with ruling out rival explanations for the estimated relationship between two variables [40]. ...

Reference:

Toward Rigorous Telecoupling Causal Attribution: A Systematic Review and Typology
Ex- post evaluation of transport interventions using causal inference methods