Variable selection for ultra-high dimensional quantile regression with missing data and measurement error.

In this paper, we consider variable selection for ultra-high dimensional quantile regression model with missing data and measurement errors in covariates. Specifically, we correct the bias in the loss function caused by measurement error by applying the orthogonal quantile regression approach and remove the bias caused by missing data using the inverse probability weighting. A nonconvex Atan penalized estimation method is proposed for simultaneous variable selection and estimation. With the proper choice of the regularization parameter and under some relaxed conditions, we show that the proposed estimate enjoys the oracle properties. The choice of smoothing parameters is also discussed. The performance of the proposed variable selection procedure is assessed by Monte Carlo simulation studies. We further demonstrate the proposed procedure with a breast cancer data set.

Comparing two epidemiologic surveillance methods to assess underestimation of human stampedes in India.

BACKGROUND: Two separate but complementary epidemiologic surveillance methods for human stampedes have emerged since the publication of the topic in 2009. The objective of this study is to estimate the degree of underreporting in India. METHOD: The Ngai Search Method was compared to the Roy Search Method for human stampede events occurring in India between 2001 and 2010. RESULTS: A total of 40 stampedes were identified by both search methods. Using the Ngai method, 34 human stampedes were identified. Using a previously defined stampede scale: 2 events were class I, 21 events were class II, 8 events were class III, and 3 events were class IV. The median deaths were 5.5 per event and median injuries were 13.5 per event. Using the Roy method, 27 events were identified, including 9 events that were not identified by the Ngai method. After excluding events based on exclusion criteria, six additional events identified by the Roy's method had a median of 4 deaths and 30 injuries. In multivariate analysis using the Ngai method, religious (6.52, 95%CI 1.73-24.66, p=0.006) and political (277.09, 95%CI 5.12-15,001.96, p=0.006) events had higher relative number of deaths. CONCLUSION: Many causes accounting for the global increase in human stampede events can only be elucidated through systematic epidemiological investigation. Focusing on a country with a high recurrence of human stampedes, we compare two independent methods of data abstraction in an effort to improve the existing database and to identify pertinent risk factors. We concluded that our previous publication underestimated stampede events in India by approximately 18% and an international standardized database to systematically record occurrence of human stampedes is needed to facilitate understanding of the epidemiology of human stampedes.