Non-testability of instrument validity under continuous treatments

Biometrika ◽  
2020 ◽  
Author(s):  
F F Gunsilius
Keyword(s):  
Instrumental Variable ◽  
Instrument Validity ◽  
Hidden Variable ◽  
Continuous Setting ◽  
Hidden Variable Models

Abstract This note presents a proof of the conjecture in Pearl (1995) about testing the validity of an instrumental variable in hidden variable models. It implies that instrument validity cannot be tested in the case where the endogenous treatment is continuously distributed. This stands in contrast to the classical testability results for instrument validity when the treatment is discrete. However, imposing weak structural assumptions on the model, such as continuity between the observable variables, can re-establish theoretical testability in the continuous setting.

scholarly journals Using changes in host demographic rates to reveal the effects of infection with hidden variable models

2020 ◽  
Author(s):  
Jake M. Ferguson ◽  
Andrea González-González ◽  
Johnathan A. Kaiser ◽  
Sara M. Winzer ◽  
Justin M. Anast ◽  
...  
Keyword(s):  
Longitudinal Studies ◽  
Population Level ◽  
Vital Rates ◽  
Hidden Variable ◽  
Demographic Rates ◽  
Public Health Data ◽  
Individual Effects ◽  
Wildlife Populations ◽  
The Individual ◽  
Hidden Variable Models

AbstractThe impacts of disease on host vital rates can be clearly demonstrated using longitudinal studies, but these studies can be expensive and logistically challenging. We examined the utility of hidden variable models to infer the individual effects of disease, caused by infection, from population-level measurements of survival and fecundity when longitudinal studies are not possible. Our approach seeks to explain temporal changes in population-level vital rates by coupling observed changes in the infection status of individuals to an epidemiological model. We tested the approach using both single and coinfection viral challenge experiments on populations of fruit flies (Drosophila melanogaster). Specifically, we determined whether our approach yielded reliable estimates of disease prevalence and of the effects of disease on survival and fecundity rates for treatments of single infections and coinfection. We found two conditions are necessary for reliable estimation. First, diseases must drive detectable changes in vital rates, and second, there must be substantial variation in the degree of prevalence over time. This approach could prove useful for detecting epidemics from public health data in regions where standard surveillance techniques are not available, and in the study of epidemics in wildlife populations, where longitudinal studies can be especially difficult to implement.

scholarly journals Algorithmic Construction of Local Hidden Variable Models for Entangled Quantum States

2016 ◽  
Vol 117 (19) ◽  
Author(s):  
Flavien Hirsch ◽  
Marco Túlio Quintino ◽  
Tamás Vértesi ◽  
Matthew F. Pusey ◽  
Nicolas Brunner
Keyword(s):  
Quantum States ◽  
Hidden Variable ◽  
Entangled Quantum States ◽  
Algorithmic Construction ◽  
Hidden Variable Models ◽  
Local Hidden Variable
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