Validating Arguments for Observational Instruments: Attending to Multiple Sources of Variation

2012 ◽  
Vol 17 (2-3) ◽  
pp. 88-106 ◽  
Author(s):  
Heather C. Hill ◽  
Charalambos Y. Charalambous ◽  
David Blazar ◽  
Daniel McGinn ◽  
Matthew A. Kraft ◽  
...  
2017 ◽  
Vol 96 ◽  
pp. 122-127 ◽  
Author(s):  
Michele Johnstone ◽  
Michele Schiffer ◽  
Ary A. Hoffmann

2015 ◽  
Vol 105 (2) ◽  
pp. 710-746 ◽  
Author(s):  
Neale Mahoney

This paper examines the implicit health insurance that households receive from the ability to declare bankruptcy. Exploiting multiple sources of variation in asset exemption law, I show that uninsured households with a greater financial cost of bankruptcy make higher out-of-pocket medical payments, conditional on the amount of care received. In turn, I find that households with greater wealth at risk are more likely to hold health insurance. The implicit insurance from bankruptcy distorts the insurance coverage decision. Using a microsimulation model, I calculate that the optimal Pigovian penalties are three-quarters as large as the average penalties under the Affordable Care Act. (JEL D14, H51, I13, K35)


2021 ◽  
pp. 304-330
Author(s):  
Anusha Chari ◽  
Ryan Leary

This chapter presents a case study that investigates the pricing of key contract provisions in Puerto Rican debt. It contributes to a body of research that asks whether investors price contract provisions and, if so, whether the pricing varies with credit risk. Contract provisions across different types of Puerto Rican bonds contain multiple sources of variation. Specifically, the chapter examines investor pricing of three key legal provisions of Puerto Rican debt; general obligation debt versus the secured bonds issued by the Puerto Rico Sales Tax Financing Corporation; debt issued under New York law versus Puerto Rican law; and finally impact of the Puerto Rico Oversight, Management, and Economic Stability Act (PROMESA) which retroactively enacted collective action clauses for Puerto Rican debt. In each instance, we find evidence consistent with the hypothesis that investors value specific contract provisions and legal protections and more so when credit risk is high, and restructuring becomes likely.


2020 ◽  
Author(s):  
Seth W. Egger ◽  
Stephen G. Lisberger

ABSTRACTWe seek to understand the neural mechanisms that perform sensory decoding for motor behavior, advancing the field by designing decoders based on neural circuits. A simple experiment produced a surprising result that shapes our approach. Changing the size of a target for smooth pursuit eye movements changes the relationship between the variance and mean of the evoked behavior in a way that contradicts the regime of “signal-dependent noise” and defies traditional decoding approaches. A theoretical analysis leads us to conclude that sensory decoding circuits for pursuit include multiple parallel pathways and multiple sources of variation. Behavioral and neural responses with biomimetic statistics emerge from a biologically-motivated circuit model with noise in the pathway that is dedicated to flexibly adjusting the strength of visual-motor transmission. Flexible adjustment of transmission strength applies much more broadly to issues in sensory-motor control such as Bayesian integration and control strategies to optimize motor behavior.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Elizabeth R. Hutton ◽  
Christopher R. Vakoc ◽  
Adam Siepel

AbstractHigh-throughput CRISPR-Cas9 knockout screens are widely used to evaluate gene essentiality in cancer research. Here we introduce a probabilistic modeling framework, Analysis of CRISPR-based Essentiality (ACE), that accounts for multiple sources of variation in CRISPR-Cas9 screens and enables new statistical tests for essentiality. We show using simulations that ACE is effective at predicting both absolute and differential essentiality. When applied to publicly available data, ACE identifies known and novel candidates for genotype-specific essentiality, including RNA m6-A methyltransferases that exhibit enhanced essentiality in the presence of inactivating TP53 mutations. ACE provides a robust framework for identifying genes responsive to subtype-specific therapeutic targeting.


2017 ◽  
Author(s):  
Alun L. Lloyd ◽  
Uriel Kitron ◽  
T. Alex Perkins ◽  
Gonzalo M. Vazquez-Prokopec ◽  
Lance A. Waller

AbstractIn mathematical epidemiology, a well-known formula describes the impact of heterogeneity on the basic reproductive number, R0, for situations in which transmission is separable and for which there is one source of variation in susceptibility and one source of variation in infectiousness. This formula is written in terms of the magnitudes of the heterogeneities, as quantified by their coefficients of variation, and the correlation between them. A natural question to ask is whether analogous results apply when there are multiple sources of variation in susceptibility and/or infectiousness. In this paper we demonstrate that with three or more coupled heterogeneities, R0 under separable transmission depends on details of the distribution of the heterogeneities in a way that is not seen in the well-known simpler situation. We provide explicit formulae for the cases of multivariate normal and multivariate log-normal distributions, showing that R0 can again be expressed in terms of the magnitudes of the heterogeneities and the pairwise correlations between them. The formulae, however, differ between the two multivariate distributions, demonstrating that no formula of this type applies generally when there are three or more coupled heterogeneities. We see that the results of the formulae are approximately equal when heterogeneities are relatively small and show that an earlier result in the literature (Koella, 1991) should be viewed in this light. We provide numerical illustrations of our results and discuss a setting in which coupled heterogeneities are likely to have a major impact on the value of R0. We also describe a rather surprising result: in a system with three heterogeneities, R0 can exhibit non-monotonic behavior with increasing levels of heterogeneity, in marked contrast to the familiar two heterogeneity setting in which R0 either increases or decreases with increasing heterogeneity.


1976 ◽  
Vol 6 (1) ◽  
pp. 123-137 ◽  
Author(s):  
William A. Reinke

Many more or less attractive techniques have been proposed for statistical analyses involving multiple sources of variation, for example in examining the possible contributors to differential patterns of health services utilization and expenditure. A large scale investigation of such patterns among 10,000 households in Chile provided a useful basis for comparison of alternative analytical approaches. The multiple regression, Automatic Interaction Detection, and Multisort techniques were applied to the survey data separately and in combination and results were compared. The Multisort technique was found to be the single most useful and convenient approach, but the most meaningful results were obtained from the systematic application of the three approaches combined.


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