An increasing number of recent studies have suggested that doubly robust estimators with
cross-fitting should be used when estimating causal effects with machine learning methods …

Rationale, aims and objectives Interventions with multivalued treatments are common in
medical and health research; examples include comparing the efficacy of competing …

Objective Our chief objective was to assess whether longer duration of 5α-RI exposure
increases risk of PED, independent of age and other known risk factors. Men with shorter 5α …

Machine learning, which converts complex data into algorithms, challenges the traditional
epidemiologic approach of evidence-based medicine. This commentary discusses …

In novometric theory the minimum denominator selection algorithm identifies the descendant
family (DF), consisting of one or more optimal models, within which the globally optimal (GO) …

Rationale, aims and objectives A common approach to assessing treatment effects in
nonrandomized studies with time‐to‐event outcomes is to estimate propensity scores and …

The idea of the modal shift has been central to transport policymaking in the past few
decades. Fare-free public transport (FFPT) schemes are among the potential policy …

Rationale, aims, and objectives Interrupted time series analysis (ITSA) is a popular
evaluation methodology in which a single treatment unit's outcome is studied over time, and …

Rationale, aims, and objectives Randomization ensures that treatment groups do not differ
systematically in their characteristics, thereby reducing threats to validity that may otherwise …

“人工智能” 革命是一场重要的技术变革, 它不仅波及到了生产生活的各个方面,
也影响到了经济学研究. 最近几年来, 人工智能不仅成为了经济学研究的重要工具 …