Browsing by Author "Chen, S"

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    Bayesian analysis on meta-analysis of case-control studies accounting for within-study correlation
    (Statistical Methods in Medical Research, 2015) Chen, Y; Chu, H; Luo, S; Nie, L; Chen, S
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    Estimating censored regression models in the presence of nonparametric multiplicative heteroskedasticity
    (Journal of Econometrics, 2000-10-01) Chen, S; Khan, S
    Powell's (1984, Journal of Econometrics 25, 303-325) censored least absolute deviations (CLAD) estimator for the censored linear regression model has been regarded as a desirable alternative to maximum likelihood estimation methods due to its robustness to conditional heteroskedasticity and distributional mis specification of the error term. However, the CLAD estimation procedure has failed in certain empirical applications due to the restrictive nature of the 'full rank' condition it requires. This condition can be especially problematic when the data are heavily censored. In this paper we introduce estimation procedures for heteroskedastic censored linear regression models with a much weaker identification restriction than that required for the LCAD, and which are flexible enough to allow for various degrees of censoring. The new estimators are shown to have desirable asymptotic properties and perform well in small-scale simulation studies, and can thus be considered as viable alternatives for estimating censored regression models, especially for applications in which the CLAD fails. © 2000 Elsevier Science S.A. All rights reserved.
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    Informational content of special regressors in heteroskedastic binary response models
    (Journal of Econometrics, 2016-07-01) Chen, S; Khan, S; Tang, X
    © 2016 Elsevier B.V.We quantify the informational content of special regressors in heteroskedastic binary response models with median-independent or conditionally symmetric errors. Based on Lewbel (1998), a special regressor is additively separable in the latent payoff and conditionally independent from the error term. We find that with median-independent errors a special regressor does not increase the identifying power by a criterion in Manski (1988) or lead to positive Fisher information for the coefficients, even though it does help recover the average structural function. With conditionally symmetric errors, a special regressor improves the identifying power, and the information for coefficients is positive under mild conditions. We propose two estimators for binary response models with conditionally symmetric errors and special regressors.
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    Rates of convergence for estimating regression coefficients in heteroskedastic discrete response models
    (Journal of Econometrics, 2003-12-01) Chen, S; Khan, S
    In this paper, we consider estimation of discrete response models exhibiting conditional heteroskedasticity of a multiplicative form, where the latent error term is assumed to be the product of an unknown scale function and a homoskedastic error term. It is first shown that for estimation of the slope coefficients in a binary choice model under this type of restriction, the semiparametric information bound is zero, even when the homoskedastic error term is parametrically specified. Hence, it is impossible to attain the parametric convergence rate for the parameters of interest. However, for ordered response models where the response variable can take at least three different values, the parameters of interest can be estimated at the parametric rate under the multiplicative heteroskedasticity assumption. Two estimation procedures are proposed. The first estimator, based on a parametric restriction on the homoskedastic component of the error term, is a two-step maximum likelihood estimators, where the unknown scale function is estimated nonparametrically in the first stage. The second procedure, which does not require the parametric restriction, estimates the parameters by a kernel weighted least-squares procedure. Under regularity conditions which are standard in the literature, both estimators are shown to be √n-consistent and asymptotically normal. © 2003 Elsevier B.V. All rights reserved.
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    Semiparametric estimation of a heteroskedastic sample selection model
    (Econometric Theory, 2003-12-01) Chen, S; Khan, S
    This paper considers estimation of a sample selection model subject to conditional heteroskedasticity in both the selection and outcome equations. The form of heteroskedasticity allowed for in each equation is multiplicative, and each of the two scale functions is left unspecified. A three-step estimator for the parameters of interest in the outcome equation is proposed. The first two stages involve nonparametric estimation of the "propensity score" and the conditional interquartile range of the outcome equation, respectively. The third stage reweights the data so that the conditional expectation of the reweighted dependent variable is of a partially linear form, and the parameters of interest are estimated by an approach analogous to that adopted in Ahn and Powell (1993, Journal of Econometrics 58, 3-29). Under standard regularity conditions the proposed estimator is shown to be √n-consistent and asymptotically normal, and the form of its limiting covariance matrix is derived.
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    Semiparametric estimation of a partially linear censored regression model
    (Econometric Theory, 2001-12-01) Chen, S; Khan, S
    In this paper we propose an estimation procedure for a censored regression model where the latent regression function has a partially linear form. Based on a conditional quantile restriction, we estimate the model by a two stage procedure. The first stage nonparametrically estimates the conditional quantile function at in-sample and appropriate out-of-sample points, and the second stage involves a simple weighted least squares procedure. The proposed procedure is shown to have desirable asymptotic properties under regularity conditions that are standard in the literature. A small scale simulation study indicates that the estimator performs well in moderately sized samples.
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    Semiparametric estimation of nonstationary censored panel data models with time varying factor loads
    (Econometric Theory, 2008-10-01) Chen, S; Khan, S
    We propose an estimation procedure for a semiparametric panel data censored regression model in which the error terms may be subject to general forms of nonstationarity. Specifically, we allow for heteroskedasticity over time and a time varying factor load on the individual specific effect. Empirically, estimation of this model would be of interest to explore how returns to unobserved skills change over time - see, e.g., Chay (1995, manuscript, Princeton University) and Chay and Honoré (1998, Journal of Human Resources 33, 4-38). We adopt a two-stage procedure based on nonparametric median regression, and the proposed estimator is shown to be √n-consistent and asymptotically normal. The estimation procedure is also useful in the group effect setting, where estimation of the factor load would be empirically relevant in the study of the intergenerational correlation in income, explored in Solon (1992, American Economic Review 82, 393-408; 1999, Handbook of Labor Economics, vol. 3, 1761-1800) and Zimmerman (1992, American Economic Review 82, 409-429). © 2008 Cambridge University Press.
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    The global abundance of tree palms
    (Global Ecology and Biogeography, 2020-09-01) Muscarella, R; Emilio, T; Phillips, OL; Lewis, SL; Slik, F; Baker, WJ; Couvreur, TLP; Eiserhardt, WL; Svenning, JC; Affum-Baffoe, K; Aiba, SI; de Almeida, EC; de Almeida, SS; de Oliveira, EA; Álvarez-Dávila, E; Alves, LF; Alvez-Valles, CM; Carvalho, FA; Guarin, FA; Andrade, A; Aragão, LEOC; Murakami, AA; Arroyo, L; Ashton, PS; Corredor, GAA; Baker, TR; de Camargo, PB; Barlow, J; Bastin, JF; Bengone, NN; Berenguer, E; Berry, N; Blanc, L; Böhning-Gaese, K; Bonal, D; Bongers, F; Bradford, M; Brambach, F; Brearley, FQ; Brewer, SW; Camargo, JLC; Campbell, DG; Castilho, CV; Castro, W; Catchpole, D; Cerón Martínez, CE; Chen, S; Chhang, P; Cho, P; Chutipong, W; Clark, C; Collins, M; Comiskey, JA; Medina, MNC; Costa, FRC; Culmsee, H; David-Higuita, H; Davidar, P; del Aguila-Pasquel, J; Derroire, G; Di Fiore, A; Van Do, T; Doucet, JL; Dourdain, A; Drake, DR; Ensslin, A; Erwin, T; Ewango, CEN; Ewers, RM; Fauset, S; Feldpausch, TR; Ferreira, J; Ferreira, LV; Fischer, M; Franklin, J; Fredriksson, GM; Gillespie, TW; Gilpin, M; Gonmadje, C; Gunatilleke, AUN; Hakeem, KR; Hall, JS; Hamer, KC; Harris, DJ; Harrison, RD; Hector, A; Hemp, A; Herault, B; Pizango, CGH; Coronado, ENH; Hubau, W; Hussain, MS; Ibrahim, FH; Imai, N; Joly, CA; Joseph, S; Anitha, K; Kartawinata, K; Kassi, J; Killeen, TJ
    Aim: Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location: Tropical and subtropical moist forests. Time period: Current. Major taxa studied: Palms (Arecaceae). Methods: We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co-occurring non-palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results: On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long-term climate stability. Life-form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non-tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above-ground biomass, but the magnitude and direction of the effect require additional work. Conclusions: Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.
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    Voriconazole plus terbinafine combination antifungal therapy for invasive Lomentospora prolificans infections: analysis of 41 patients from the FungiScope® registry 2008-2019.
    (Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases, 2020-06) Jenks, JD; Seidel, D; Cornely, OA; Chen, S; van Hal, S; Kauffman, C; Miceli, MH; Heinemann, M; Christner, M; Jover Sáenz, A; Burchardt, A; Kemmerling, B; Herbrecht, R; Steinmann, J; Shoham, S; Gräber, S; Pagano, L; Deeren, D; Aslam, S; Taplitz, R; Revankar, SG; Baddley, J; Mehta, SR; Reed, S; Slavin, MA; Hoenigl, M

    Objectives

    Lomentospora prolificans is an emerging cause of serious invasive fungal infections. Optimal treatment of these infections is unknown, although voriconazole-containing treatment regimens are considered the treatment of choice. The objective of this study was to evaluate the role of combination antifungal therapy for L. prolificans infections.

    Methods

    We performed a retrospective review of medical records of patients with invasive L. prolificans infection diagnosed between 1 January 2008 and 9 September 2019 that were documented in the FungiScope® registry of rare invasive fungal infections. We compared clinical outcomes between antifungal treatment strategies.

    Results

    Over the study period, 41 individuals with invasive L. prolificans infection from eight different countries were documented in the FungiScope® registry. Overall, 17/40 (43%) had treatment response/stable disease and 21/40 (53%) had a fatal outcome attributed to invasive fungal infection. Combination antifungal therapy was associated with increased 28-day survival (15/24 survived versus 4/16 receiving monotherapy; p 0.027) and the combination voriconazole plus terbinafine trended to be associated with higher rates of treatment success (10/16, 63%, 95% CI 35%-85%) compared with other antifungal treatment regimens (7/24, 29%, 95% CI 13%-51%, p 0.053). In Kaplan-Meier survival analysis there was a higher survival probability in individuals receiving the voriconazole/terbinafine combination compared with other antifungal regimens (median survival 150 days versus 17 days).

    Conclusions

    While overall mortality was high, combination antifungal treatment, and in particular combination therapy with voriconazole plus terbinafine may be associated with improved treatment outcomes compared with other antifungal regimens for the treatment of invasive L. prolificans infections.