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- 저자 : Ranran Chen (검색결과 2 건)
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Testing for covariance matrices in time-varying coefficient panel datamodels with fixed effects
Ranran Chen,Gaorong Li,Sanying Feng 한국통계학회 2020 Journal of the Korean Statistical Society Vol.49 No.1
In this paper, we study the tests for sphericity and identity of covariance matrices in time-varying coefficient high-dimensional panel data models with fixed effects. In order to construct the effective test statistics and avoid the influence of the unknown fixed effects, we apply the difference method to eliminate the dependence of the residual sample, and further construct test statistics using the trace estimators of the covariance matrices. For the estimators of the coefficient functions, we use the local linear dummy variable method. Under some regularity conditions, we study the asymptotic property of the estimators and establish the asymptotic distributions of our proposed test statistics without specifying an explicit relationship between the cross-sectional and the time series dimensions.We further show that the test statistics are asymptotic distribution-free. Subsequently simulation studies are carried out to evaluate our proposed methods. In order to assess the performance of our proposed test method, we compare with the existing test methods in panel data linear models with fixed effects.
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Xinyan Xie,Fang Hou,Li Li,Yanlin Chen,Lingfei Liu,Xiu Luo1,Huaiting Gu,Xin Li,Jiajia Zhang,Jianhua Gong,Ranran Song 대한신경정신의학회 2019 PSYCHIATRY INVESTIGATION Vol.16 No.5
Objective: To evaluate the association of GRIK2 and NLGN1 with autism spectrum disorder in a Chinese population. Methods: We performed spatio-temporal expression analysis of GRIK2 and NLGN1 in the developing prefrontal cortex, and examined the expression of the genes in ASD cases and healthy controls using the GSE38322 data set. Following, we performed a case-control study in a Chinese population. Results: The analysis using the publicly available expression data showed that GRIK2 and NLGN1 may have a role in the development of human brain and contribute to the risk of ASD. Later genetic analysis in the Chinese population showed that the GRIK2 rs6922753 for the T allele, TC genotype and dominant model played a significant protective role in ASD susceptibility (respectively: OR=0.840, p=0.023; OR=0.802, p=0.038; OR=0.791, p=0.020). The NLGN1 rs9855544 for the G allele and GG genotype played a significant protective role in ASD susceptibility (respectively: OR=0.844, p=0.019; OR=0.717, p=0.022). After adjusting p values, the statistical significance was lost (p>0.05). Conclusion: Our results suggested that GRIK2 rs6922753 and NLGN1 rs9855544 might not confer susceptibility to ASD in the Chinese population.
KCI
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