Well-Posedness of Measurement Error Models for Self-Reported Data

It is widely admitted that the inverse problem of estimating the distribution of a latent variable X* from an observed sample of X, a contaminated measurement of X*, is ill-posed. This paper shows that a property of self-reporting errors, observed from validation studies, is that the probability of reporting the truth is nonzero conditional on the true values, and furthermore, this property implies that measurement error models for self-reporting data are in fact well-posed. We also illustrate that the classical measurement error models may in fact be conditionally well-posed given prior information on the distribution of the latent variable X*.

Well-posedness of measurement error models for self-reported data

It is widely admitted that the inverse problem of estimating the distribution of a latent variable X* from an observed sample of X, a contaminated measurement of X*, is ill-posed. This paper shows that measurement error models for self-reporting data are well-posed, assuming the probability of reporting truthfully is nonzero, which is an observed property in validation studies. This optimistic result suggests that one should not ignore the point mass at zero in the error distribution when modeling measurement errors in self-reported data. We also illustrate that the classical measurement error models may in fact be conditionally well-posed given prior information on the distribution of the latent variable X*. By both a Monte Carlo study and an empirical application, we show that failing to account for the property can lead to significant bias on estimation of distribution of X*.

Well-Posedness of Measurement Error Models for Self-Reported Data ∗

It is widely admitted that the inverse problem of estimating the distribution of a latent variable X ∗ from an observed sample of X, a contaminated measurement of X ∗, is ill-posed. This paper shows that measurement error models for self-reporting data are well-posed, assuming the probability of reporting truthfully is nonzero, which is an observed property in validation studies. This optimistic result suggests that one should not ignore the point mass at zero in the error distribution when modeling measurement errors in self-reported data. We also illustrate that the classical measurement error models may in fact be conditionally well-posed given prior information on the distribution of the latent variable X ∗. By both a Monte Carlo study and an empirical application, we show that failing to account for the property can lead to significant bias on estimation of distribution of X ∗

Horizontal Mergers of Online Firms: Structural Estimation and Competitive Effects

This paper (1) presents a general model of online price competition, (2) shows how to structurally estimate the underlying parameters of the model when the number of competing firms is unknown or in dispute, (3) estimates these parameters based on UK data for personal digital assistants, and (4) uses these estimates to simulate the competitive effects of horizontal mergers. Our results suggest that competitive effects in this online market are more closely aligned with the simple homogeneous product Bertrand model than might be expected given the observed price dispersion and number of firms. Our estimates indicate that so long as two firms remain in the market post merger, the average transaction price is roughly unaffected by horizontal mergers. However, there are potential distributional effects; our estimates indicate that a three-to-two merger raises the average transaction price paid by price sensitive "shoppers" by 2.88 percent, while lowering the average transaction price paid by consumers "loyal" to a particular firm by 1.37 percent.

Influences of Stone–Wales defects on the structure, stability and electronic properties of antimonene: A first principle study

AbstractDefects are inevitably present in materials, and their existence strongly affects the fundamental physical properties of 2D materials. Here, we performed first-principles calculations to study the structural and electronic properties of antimonene with Stone–Wales defects, highlighting the differences in the structure and electronic properties. Our calculations show that the presence of a SW defect in antimonene changes the geometrical symmetry. And the band gap decreases in electronic band structure with the decrease of the SW defect concentration. The formation energy and cohesive energy of a SW defect in antimonene are studied, showing the possibility of its existence and its good stability, respectively. The difference charge density near the SW defect is explored, by which the structural deformations of antimonene are explained. At last, we calculated the STM images for the SW defective antimonene to provide more information and characters for possible experimental observation. These results may provide meaningful references to the development and design of novel nanodevices based on new 2D materials

Estimating private provision of public goods with heterogenous participants: a structural analysis

This paper estimates a structural model of private provision of public goods to provide some new empirical evidence on individuals' strategic contributing behaviors. In the model, individuals' contributing behaviors are allowed to be heterogenous and time-varying. We show that all the main components of the model including the number of different contributing strategies, functional form for each strategy, and how individuals adjust their strategies are identified from the revealed contribution choices of individuals. Further, the structural model is estimated using the data collected in a threshold public good experiment. The empirical results suggest that subjects in our experiment employ three contributing strategies, and they strategically respond to provision history by adjusting their preceding behavior. In addition, the response is heterogenous and dependent on subjects' contributing strategies

Identification and Estimation of Online Price Competition With an Unknown Number of Firms

This paper considers identification and estimation of a general model for online price competition. We show that when the number of competing firms is unknown the underlying parameters of the model can still be identified and estimated employing recently developed results on measurement errors. We illustrate our methodology using UK data for personal digital assistants and employ the estimates to simulate competitive effects. Our results reveal that heightened competition has differential effects on the prices paid by different consumer segments

Sorafenib modulates the radio sensitivity of hepatocellular carcinoma cells in vitro in a schedule-dependent manner

BACKGROUND: Hepatocellular carcinoma (HCC) has a high incidence and mortality. Radiotherapy and sorafenib have proven effective for HCC. Here, we investigated whether sorafenib modulated the response of HCC cells to irradiation in vitro, effect of timing of sorafenib, and the underlying mechanisms. METHODS: Cell viability of the HCC cell lines, SMMC-7721 and Bel-7402, was examined by the 3-(4,5-dimethylthiazol-2-yl)-5(3-carboxymethoxyphenyl)-2(4-sulfophenyl)-2 H-terazolium (MTT) assays. Clonogenic growth assays of SMMC-7721 and Bel-7402 were determined by colony formation assays. DNA damage was assessed by monitoring γ-HAX foci in irradiated cells with immunofluorescence microscopy, and cell cycle distribution changes were examined by flow cytometry. Effects of sorafenib (15 μM) added 30 min prior to radiation (pre-irradiation sorafenib) of SMMC-7721 and BEL-7402 or 24 h post-irradiation (post-irradiation sorafenib) on irradiated SMMC-7721 and BEL-7402 cells were compared to those of radiation alone or no treatment. RESULTS: The effect of sorafenib was dependent on its time of addition in relationship to irradiation of cells. Pre-irradiation sorafenib did not significantly affect the viability of SMMC-7221 and BEL-7402 cells compared with irradiation treatment alone. In contrast, post-irradiation sorafenib increased the sensitivity of irradiated SMMC-7221 and BEL-7402 cells significantly in a time-dependent manner. Pre-irradiation sorafenib significantly increased the surviving fraction of SMMC-7221 and BEL-7402 cells in clonogenic assays whereas post-irradiation sorafenib significantly reduced the surviving fractions of SMMC-7221 and BEL-7402 cells. SMMC-7721 cells treated with sorafenib 30 min before irradiation had significantly fewer cells with γ-H2AX foci (23.8 ± 2.9%) than SMMC-7721 cells receiving radiation alone (59.9 ± 2.4; P < 0.001). Similarly, BEL-7402 cells receiving sorafenib prior to irradiation had significantly fewer cells with γ-H2AX foci (46.4 ± 3.8%) than those receiving radiation alone (25.0 ± 3.0%; P < 0.001). In addition, irradiation (6 Gy) caused a significant increase in the percentage of both SMMC-7721 and BEL-7402 cells in G2/M at 12 to 16 h post irradiation, which was markedly delayed by pre-irradiation sorafenib. CONCLUSIONS: Sorafenib combined with irradiation exerted a schedule-dependent effect in HCC cells in vitro, which has significant implications for the combined use of sorafenib and radiotherapy for HCC patients

Herb Target Prediction Based on Representation Learning of Symptom related Heterogeneous Network.

Traditional Chinese Medicine (TCM) has received increasing attention as a complementary approach or alternative to modern medicine. However, experimental methods for identifying novel targets of TCM herbs heavily relied on the current available herb-compound-target relationships. In this work, we present an Herb-Target Interaction Network (HTINet) approach, a novel network integration pipeline for herb-target prediction mainly relying on the symptom related associations. HTINet focuses on capturing the low-dimensional feature vectors for both herbs and proteins by network embedding, which incorporate the topological properties of nodes across multi-layered heterogeneous network, and then performs supervised learning based on these low-dimensional feature representations. HTINet obtains performance improvement over a well-established random walk based herb-target prediction method. Furthermore, we have manually validated several predicted herb-target interactions from independent literatures. These results indicate that HTINet can be used to integrate heterogeneous information to predict novel herb-target interactions