Multivariate logistic regression analyses revealed that the use of gas cooking(OR 2.08,95%CI 1.32-3.26),foam pillow(OR 1.94,95%CI 1.19-3.16),and house dampness(OR 1.84,95%CI 1.25-2.71) were significant risk factors for "current wheezing".
Describes the method for planning sequential multivariate acceptance sampling based on some of the results obtained by Jackson and Bradley,with boundary value tables of the sequential x~2-test and T~2-test,when α=β=0.05, p=2,3,4 and λ_0~2=0,provided.
本文根据 Jackson 和 Bradley 的一些结果,说明序列多变量抽样验收方案的制订方法,并对α=β=0.05,p=2,3,4,λ_0~2=0给出序列 X~2-检验和 T~2-检验的界限值表。
Multivariate stepwise logistic regression in single locus analysis, with adjustment for common risk factors for hypertension, demonstrated that the OR for DD/ID versus Ⅱ for hypertension among men was significant (OR 1.57; 95% CI, 1.09～2.27; P = 0.016) in dominant genetic model.
In a multivariable COX regression model,the hazard ratio of death from any cause for the patients with BNP levels in the fourth quartile as compared with those patients with those in the first quartile was 2.4(95% CI:1.5～4.0,P＜0.001 ).
Multiresolution Analysis and Multivariate Approximation of Smooth Signals in CB(Rd
In order to arrive at some of our results, we set up a general multivariate version of Littlewood-Paley type inequality which was originally considered by Lemarié and Meyer , then by Chui and Shi , and Long .
The accuracy of f is the highest degree p such that all multivariate polynomials q with degree(q)>amp;lt;p are exactly reproduced from linear combinations of translates of f1,...,fr along the lattice Γ.
These coefficients are multivariate polynomials yα,i(x) of degree |α| evaluated at lattice points k∈Γ.
Affine Frames of Multivariate Box Splines and their Affine Duals
It is concluded that multi-variable analyses of as complex a problem as we tried to investigate cannot produce a testable hypothesis and that only single-variable analyses are appropriate strategies for this type of research.
The major difficulty arising in statistics of multi-variable functions is "the curse of dimensionality": the rates of accuracy in estimation and separation rates in detection problems behave poorly when the number of variables increases.
The multi-variable statistical model for animals dying with one type of tumor is not applicable to those dying with tumors of other types or sites.
A multi-variable test method, known as the Orthogonal Array, was used to optimize the parameters for the laser gas nitriding process (LGNP) to avoid surface cracking.
An illustrative example is given, to demonstrate the effectiveness of the algorithm for eliminating the effects of ill-conditioning in the training data, in an application of neural modelling of a multi-variable chemical process.