Partial Identification of the Average Treatment Effect Using Instrumental Variables: Review of Methods for Binary Instruments, Treatments, and Outcomes

Several methods have been proposed for partially or point identifying the average treatment effect (ATE) using instrumental variable (IV) type assumptions. The descriptions of these methods are widespread across the statistical, economic, epidemiologic, and computer science literature, and the connections between the methods have not been readily apparent. In the setting of a binary instrument, treatment, and outcome, we review proposed methods for partial and point identification of the ATE under IV assumptions, express the identification results in a common notation and terminology, and propose a taxonomy that is based on sets of identifying assumptions. We further demonstrate and provide software for the application of these methods to estimate bounds. Supplementary materials for this article are available online

Velocity Statistics in the Two-Dimensional Granular Turbulence

We studied the macroscopic statistical properties on the freely evolving quasi-elastic hard disk (granular) system by performing a large-scale (up to a few million particles) event-driven molecular dynamics systematically and found that remarkably analogous to an enstrophy cascade process in the decaying two-dimensional fluid turbulence. There are four typical stages in the freely evolving inelastic hard disk system, which are homogeneous, shearing (vortex), clustering and final state. In the shearing stage, the self-organized macroscopic coherent vortices become dominant. In the clustering stage, the energy spectra are close to the expectation of Kraichnan-Batchelor theory and the squared two-particle separation strictly obeys Richardson law.Comment: 4 pages, 4 figures, to be published in PR

Correlation functions of small-scale fluctuations of the interplanetary magnetic field

The Interplanetary Magnetic Field shows complex spatial and temporal variations. Single spacecraft measurements reveal only a one dimensional section of this rich four dimensional phenomenon. Multi-point measurements of the four Cluster spacecraft provide a unique tool to study the spatiotemporal structure of the field. Using Cluster data we determined three dimensional correlation functions of the fluctuations. By means of the correlation function one can describe and measure field variations. Our results can be used to verify theoretical predictions, to understand the formation and nature of solar wind turbulence. We found that the correlation length varies over almost six orders of magnitude. The IMF turbulence shows significant anisotropy with two distinct populations. In certain time intervals the ratio of the three axes of the correlation ellipse is 1/2.2/6 while in the remaining time we found extremely high correlation along one axis. We found favoured directions in the orientation of the correlation ellipsoids.Comment: accepted to Solar Physics on June 14, 2010. 10 pages, 8 figure

Iron valence in double-perovskite (Ba,Sr,Ca)2FeMoO6: Isovalent substitution effect

In the Fe-Mo based B-site ordered double-perovskite, A2FeMoO6.0, with iron in the mixed-valence II/III state, the valence value of Fe is not precisely fixed at 2.5 but may be fine-tuned by means of applying chemical pressure at the A-cation site. This is shown through a systematic 57Fe Mossbauer spectroscopy study using a series of A2FeMoO6.0 [A = (Ba,Sr) or (Sr,Ca)] samples with high degree of Fe/Mo order, the same stoichiometric oxygen content and also almost the same grain size. The isomer shift values and other hyperfine parameters obtained from the Mossbauer spectra confirm that Fe remains in the mixed-valence state within the whole range of A constituents. However, upon increasing the average cation size at the A site the precise valence of Fe is found to decrease such that within the A = (Ba,Sr) regime the valence of Fe is closer to II, while within the A = (Sr,Ca) regime it is closer to the actual mixed-valence II/III state. As the valence of Fe approaches II, the difference in charges between Fe and Mo increases, and parallel with this the degree of Fe/Mo order increases. Additionally, for the less-ordered samples an increased tendency of clustering of the anti-site Fe atoms is deduced from the Mossbauer data.Comment: 19 pages, 6 figures, submitted to Phys. Rev.

Synchronous dual primary ovarian and endometrial carcinomas

OBJECTIVES: The synchronous occurrence of carcinoma confined to the ovary and endometrium presents a diagnostic and therapeutic dilemma. These tumors have been variously staged as FIGO Stage IIA ovarian carcinoma, Stage III endometrial carcinoma, or synchronous dual primary carcinomas. Accumulating evidence suggests such patients have a favorable outcome. This retrospective study was undertaken to review our experience with these fascinating tumors. METHODS: The clinical records and the pathologic findings of 16 patients with synchronous dual primary ovarian and endometrial carcinomas were reviewed. RESULTS: The median age was 51 years. Abnormal uterine bleeding was the most common presenting symptom (70%). All patients had Stage I ovarian and endometrial carcinomas. Fourteen patients (88%) had endometrioid carcinoma in both sites, while two patients (12%) had dissimilar histology. For 15 patients (94%), the grade of both tumors was identical. Only three (19%) patients had myometrial invasion, with less than 50% involvement in each case. All patients underwent surgical staging, 11 (70%) of whom received adjuvant radiation or chemotherapy. The five patients treated with surgery alone had Grade 1 endometrioid tumors. The only relapse occurred in a patient with a clear cell component in both sites. No patient has died of disease. CONCLUSIONS: Patients with synchronous dual primary carcinomas appear to have a more favorable prognosis than that expected with Stage IIA ovarian or Stage III endometrial carcinoma (100% vs. 63% or 42% survival at 3 years, respectively). The excellent survival for patients with Grade 1 dual endometrioid tumors treated with surgery alone suggests that adjuvant therapy may not be necessary for this sub-group.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30414/1/0000034.pd

Multiple drivers of decline in the global status of freshwater crayfish (Decapoda: Astacidea)

International audienceRates of biodiversity loss are higher in freshwater ecosystems than in most terrestrial or marine ecosystems, making freshwater conservation a priority. However, prioritization methods are impeded by insufficient knowledge on the distribution and conservation status of freshwater taxa, particularly invertebrates. We evaluated the extinction risk of the world's 590 freshwater crayfish species using the IUCN Categories and Criteria and found 32% of all species are threatened with extinction. The level of extinction risk differed between families, with proportionally more threatened species in the Parastacidae and Astacidae than in the Cambaridae. Four described species were Extinct and 21% were assessed as Data Deficient. There was geographical variation in the dominant threats affecting the main centres of crayfish diversity. The majority of threatened US and Mexican species face threats associated with urban development, pollution, damming and water management. Conversely, the majority of Australian threatened species are affected by climate change, harvesting, agriculture and invasive species. Only a small proportion of crayfish are found within the boundaries of protected areas, suggesting that alternative means of long-term protection will be required. Our study highlights many of the significant challenges yet to come for freshwater biodiversity unless conservation planning shifts from a reactive to proactive approach

A statistical framework for assessing pharmacological responses and biomarkers using uncertainty estimates

High-throughput testing of drugs across molecular-characterised cell lines can identify candidate treatments and discover biomarkers. However, the cells’ response to a drug is typically quantified by a summary statistic from a best-fit dose-response curve, whilst neglecting the uncertainty of the curve fit and the potential variability in the raw readouts. Here, we model the experimental variance using Gaussian Processes, and subsequently, leverage uncertainty estimates to identify associated biomarkers with a new Bayesian framework. Applied to in vitro screening data on 265 compounds across 1074 cancer cell lines, our models identified 24 clinically established drug-response biomarkers, and provided evidence for six novel biomarkers by accounting for association with low uncertainty. We validated our uncertainty estimates with an additional drug screen of 26 drugs, 10 cell lines with 8 to 9 replicates. Our method is applicable to any dose-response data without replicates, and improves biomarker discovery for precision medicine