ABSTRACT
To explore the gene-based principal component logistic regression model and its application in genome-wide association study.Using the simulated genome-wide single nucleotide polymorphism (SNPs) genotypes data,we proposed a practical statistical analysis strategy-'the principal component logistic regression model',based on the gene levels to assess the association between genetic variations and complex diseases.The simulation results showed that the P value of genes in related diseases was the smallest among the results from all the genes.The results of simulation indicated that not only it could reduce the degree of freedom through hypothesis testing but could also better understand the correlations between SNPs.The gene-based principal component logistic regression model seemed to have certain statistical power for testing the association between genetic genes and diseases in the genome-wide association studies.
ABSTRACT
Multistage sampling techniques are widely applied in the cross-sectional study of epidemiology, while methods based on independent assumption are still used to analyze such complex survey data. This paper aims to introduce the application of weighted estimation methods for the complex survey data. A brief overview of basic theory is described, and then a practical analysis is illustrated to apply to the weighted estimation algorithm in a stratified two-stage clustered sampling data. For multistage sampling survey data, weighted estimation method can be used to obtain unbiased point estimation and more reasonable variance estimation, and so make proper statistical inference by correcting the clustering, stratification and unequal probability effects.
ABSTRACT
the mood of anger, sadness agitation, having some kind of infection were related to IVT. Case-crossover design seemed to be able to identify the risk factors of IVT and its intensity.