Search Results (3)

Due to the flexibility of the Weibull distribution and the proportional hazard (PH) model, Weibull PH is widely used in survival analysis under right censored data and interval censored data but it is seldom investigated under current status data, partially because there is less information in current status data than in right censored data and interval censored data. This paper considers the Weibull PH model under the current status data and introduces the Poisson latent variables to augment the data, then uses the expectation-maximization (EM) algorithm to obtain the maximum likelihood estimators of the model parameters. The EM algorithm is compared with the Newton–Raphson (NR) algorithm from several perspectives in the simulation studies, and the results show that the proposed method has several highlights, such as computational simplicity, improved convergence stability, and overall estimator results that are either comparable or slightly better in terms of bias. Furthermore, the performance of the Weibull PH model and the semi-parametric PH model is compared under two simulation scenarios, and two standard model selection criteria are used for model selection. The results indicate that the Weibull PH model has significant advantages when failure time follows a Weibull distribution. Lastly, the Weibull PH model along with EM algorithm is applied to lung tumor data and intraocular lens (IOL) calcification data with the aim of assessing the impact of covariates, including environmental factors and gender, on event timing and risk. Full article

Regression adjustment is often used to estimate average treatment effect (ATE) in randomized experiments. Recently, some penalty-based regression adjustment methods have been proposed to handle the high-dimensional problem. However, these existing high-dimensional regression adjustment methods may fail to achieve satisfactory performance when the covariates are highly correlated. In this paper, we propose a novel adjustment estimation method for ATE by combining the semi-standard partial covariance (SPAC) and regression adjustment methods. Under some regularity conditions, the asymptotic normality of our proposed SPAC adjustment ATE estimator is shown. Some simulation studies and an analysis of HER2 breast cancer data are carried out to illustrate the advantage of our proposed SPAC adjustment method in addressing the highly correlated problem of the Rubin causal model. Full article

Reference values of sway parameters have not been published for the Leonardo mechanograph^® so far. The aim of this cross-sectional study was to determine normative values on postural control measured by the force plate Leonardo Mechanograph^® and to analyze the influence of age and sex on balance performance. A set of standardized standing positions with eyes opened (Romberg, semi-tandem, tandem, unipedal standing) was carried out. Analysis of covariance (ANCOVA) was used to detect age-and sex-related differences in center of pressure (COP) parameters (path length, velocity, elliptical area, anterior-posterior, and medio-lateral directions). Measurements were available for 570 subjects aged 20–86 years. Statistical analysis showed a high effect of age group on postural control (partial n² between 0.1 and 0.4) with a U-shaped dependency between postural control and age for all area- and path-related COP parameters, with the largest sway in the youngest (aged 20–40) and the oldest age group (aged 60–86). For velocity of COP, a linear deterioration with increasing age was found. Medio-lateral components of COP are likely to indicate the extent of postural control. Significant sex differences were not clearly supported by current findings. Age- and sex-related normative values are a useful resource for diagnostic, research, and training. Full article