Browsing by Subject "Confidence interval"

Now showing 1 - 3 of 3

Open Access
MDM2 T309G polymorphism is associated with bladder cancer
(International Institute of Anticancer Research, 2006) Onat, O. E.; Tez, M.; Özçelik, T.; Törüner, G. A.
Recently, a functional T to G polymorphism at nucleotide 309 in the promoter region of the MDM2 gene (rs: 2279744, SNP 309) has been identified. This polymorphism has an impact on the expression of the MDM2 gene, which is a key negative regulator of the tumor suppressor molecule p53. The effect of T309G polymorphism of the MDM2 gene on bladder cancer susceptibility was investigated in a case-control study of 75 bladder cancer patients and 103 controls from Turkey. The G/G genotype exhibited an increased risk of 2.68 (95% CI, 1.34-5.40) for bladder cancer compared with the combination of low-risk genotypes T/T and T/G at this locus. These results show an association between MDM2 T309G polymorphism and bladder cancer in our study group. To the best of our knowledge, this is the first study reporting that MDM2 T309G polymorphism may be a potential genetic susceptibility factor for bladder cancer.
Open Access
Quantifying input uncertainty in an assemble-to-order system simulation with correlated input variables of mixed types
(IEEE, 2014) Akçay, Alp; Biller, B.
We consider an assemble-to-order production system where the product demands and the time since the last customer arrival are not independent. The simulation of this system requires a multivariate input model that generates random input vectors with correlated discrete and continuous components. In this paper, we capture the dependence between input variables in an undirected graphical model and decouple the statistical estimation of the univariate input distributions and the underlying dependence measure into separate problems. The estimation errors due to finiteness of the real-world data introduce the so-called input uncertainty in the simulation output. We propose a method that accounts for input uncertainty by sampling the univariate empirical distribution functions via bootstrapping and by maintaining a posterior distribution of the precision matrix that corresponds to the dependence structure of the graphical model. The method improves the coverages of the confidence intervals for the expected profit the per period.
Open Access
Weak and strong quantile representations for randomly truncated data with applications
(Elsevier, 1993-05-26) Gürler, Ü.; Stute, W.; Wang, J. L.
Suppose that we observe bivariate data (X,. q) only when Y, < Xi (left truncation). Denote with F the marginal d.f. of the X’s In this paper we derive a Bahadur-type representation for the quantile function of the pertaining product-limit estimator of F. As an application we obtain confidence intervals and bands for quantiles of F.