Minimax D-optimal designs for multivariate regression models with multi-factorsRobust regression designMinimax criterionReflection symmetryQuantitative and qualitative factorsConvex optimizationDifference of convex functionsIn multi-response regression models, the error covariance matrix is never known in practice....
The parameter vector for the regression model is θ=(θ1,θ2,θ3,θ4)⊤, where (θ1,θ2)⊤ is the center and r=(θ32+θ42)1∕2 is the radius of the circular arc. This form is helpful in the next section for finding the D-optimal designs analytically. Design issues are an...
A linear model with one treatment at V levels and the first-order regression on k continuous covariates with values on the k-cube is considered. We restric... CT Chadjipadelis - 《Journal of Statistical Planning & Inference》 被引量: 11发表: 1996年 Optimal Moment Sets for Multivariate Direc...
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These significant factors were then fitted in the multivariate regression model to evaluate independence. Simultaneously, the receiver operating characteristic curves (ROC) were obtained to evaluate the applicability of the Caprini risk assessment model and D-dimer. The potential net benefit of different ...
Our multivariate logistic regression analysis identified maternal weight as a risk factor for GH, PE and SPE, with ORs of 1.103, 1.093, and 1.080, respectively (P < 0.001). However, their relative effects were limited (the 95% CIs for OR ranged from 1.000 to 1.100). Moreover, all ...
Alcohol use in Hefei in relation to alcoholic liver disease: A multivariate logistic regression analysis.[J]. Alcohol (Fayetteville, N.Y.),2018,71 [9] Lena Zander,Christina L. Butler. Leadership modes: Success strategies for multicultural teams[J]. Scandinavian Journal of Management,2010,26(3)...
Multivariate linear regression method was used to analyze the correlations between 25(OH)D, glucose and sex hormones. ResultsPatients with vitamin D deficiency or insufficiency accounted for 96.5% of the hospitalized type 2 diabetes men. Patients with higher 25(OH)D were with higher HDL-C and ...
For some classical linear regression models, such as polynomial regression on an interval or multiple linear or quadratic regression on a simplex, D-optimal approximate designs ξ∗ with minimum support are well known. In the exact design setting with a given total number n of observations the ...
The optimal predictive variables were selected using Lasso regression, and univariate and multivariate Logistic regression analyses were performed to identify factors influencing the mortality of sepsis patients and to establish a nomogram model. Receiver operator characteristic curve (ROC curve), calibration...