Variable selection in nonparametric additive models

We consider a nonparametric additive model of a conditional mean function in which the number of variables and additive components may be larger than the sample size but the number of nonzero additive components is "small" relative to the sample size. The statistical problem is to determine which additive components are nonzero. The additive components are approximated by truncated series expansions with B-spline bases. With this approximation, the problem of component selection becomes that of selecting the groups of coefficients in the expansion. We apply the adaptive group Lasso to select nonzero components, using the group Lasso to obtain an initial estimator and reduce the dimension of the problem. We give conditions under which the group Lasso selects a model whose number of components is comparable with the underlying model, and the adaptive group Lasso selects the nonzero components correctly with probability approaching one as the sample size increases and achieves the optimal rate of convergence. The results of Monte Carlo experiments show that the adaptive group Lasso procedure works well with samples of moderate size. A data example is used to illustrate the application of the proposed method.Comment: Published in at http://dx.doi.org/10.1214/09-AOS781 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Substance use, risky sexual behaviors, and their associations in a Chinese sample of senior high school students

BACKGROUND: Given the higher prevalence of risky sexual behaviors and substance use, adolescents and youths are at risk for HIV. Despite its importance, however, to the best of our knowledge, there are only a few researches on risky behaviors in Chinese adolescents/youths. The present study aimed to describe the prevalence of sexual and substance use behaviors among a Chinese sample of senior high school students. And more specifically, the associations of socio-demographic factors and substance use with risky sexual behaviors were examined in the sample. METHODS: A cross-sectional study was conducted in 10 senior high schools. A total of 2668 senior high school students aged 15.17 to 23.42 years participated in the survey. A self-administrated questionnaire was used to collect information on sexual and substance use behaviors. RESULTS: The percentages of students who ever had sexual intercourse in lifetime or during last three months were 7.0% and 5.1%, respectively. Among the participants with sexual intercourse during last three months, 42.1% ever had unprotected sexual intercourse and 49.4% had intercourse with two or more partners. Multivariate logistic regression analyses showed that cigarette smoke and illicit drug use were related to unprotected sexual intercourse (defined as “sexual intercourse without condom use”) and younger age of first sexual intercourse was related to multiple-partner sexual intercourse. CONCLUSIONS: HIV/sexual transmitted infection (STI) health education and prevention are necessary among the Chinese adolescents, particularly among those adolescents with experience of sexual intercourse and/or substance use, which has a long-term beneficial to the control of HIV/STI in China

MicroRNA Let-7f Inhibits Tumor Invasion and Metastasis by Targeting MYH9 in Human Gastric Cancer

BACKGROUND: MicroRNAs (miRNAs) are important regulators that play key roles in tumorigenesis and tumor progression. A previous report has shown that let-7 family members can act as tumor suppressors in many cancers. Through miRNA array, we found that let-7f was downregulated in the highly metastatic potential gastric cancer cell lines GC9811-P and SGC7901-M, when compared with their parental cell lines, GC9811 and SGC7901-NM; however, the mechanism was not clear. In this study, we investigate whether let-7f acts as a tumor suppressor to inhibit invasion and metastasis in gastric cancers. METHODOLOGY/PRINCIPAL: Real-time PCR showed decreased levels of let-7f expression in metastatic gastric cancer tissues and cell lines that are potentially highly metastatic. Cell invasion and migration were significantly impaired in GC9811-P and SGC7901-M cell lines after transfection with let-7f-mimics. Nude mice with xenograft models of gastric cancer confirmed that let-7f could inhibit gastric cancer metastasis in vivo after transfection by the lentivirus pGCsil-GFP- let-7f. Luciferase reporter assays demonstrated that let-7f directly binds to the 3'UTR of MYH9, which codes for myosin IIA, and real-time PCR and Western blotting further indicated that let-7f downregulated the expression of myosin IIA at the mRNA and protein levels. CONCLUSIONS/SIGNIFICANCE: Our study demonstrated that overexpression of let-7f in gastric cancer could inhibit invasion and migration of gastric cancer cells through directly targeting the tumor metastasis-associated gene MYH9. These data suggest that let-7f may be a novel therapeutic candidate for gastric cancer, given its ability to reduce cell invasion and metastasis

Consistent group selection in high-dimensional linear regression

In regression problems where covariates can be naturally grouped, the group Lasso is an attractive method for variable selection since it respects the grouping structure in the data. We study the selection and estimation properties of the group Lasso in high-dimensional settings when the number of groups exceeds the sample size. We provide sufficient conditions under which the group Lasso selects a model whose dimension is comparable with the underlying model with high probability and is estimation consistent. However, the group Lasso is, in general, not selection consistent and also tends to select groups that are not important in the model. To improve the selection results, we propose an adaptive group Lasso method which is a generalization of the adaptive Lasso and requires an initial estimator. We show that the adaptive group Lasso is consistent in group selection under certain conditions if the group Lasso is used as the initial estimator.Comment: Published in at http://dx.doi.org/10.3150/10-BEJ252 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm