最小临床意义差值(minimal clinically important difference,MCID)的常用估算方法包括效标法、分布法和文献分析法等。目前MCID的估算方法众多且不统一,给MCID的确定、结果解释和应用带来了困难。鉴于目前各种估算方法均存在一定局限,...最小临床意义差值(minimal clinically important difference,MCID)的常用估算方法包括效标法、分布法和文献分析法等。目前MCID的估算方法众多且不统一,给MCID的确定、结果解释和应用带来了困难。鉴于目前各种估算方法均存在一定局限,建议同时使用多种估算方法获得多个MCID初步估算值,并以效标法为主、其他方法为辅或将多种方法通过统计整合的估算值来确定最终的MCID。MCID可协助进行临床研究结果的临床意义判断、样本量估算以及临床决策等,在具体应用之前,应充分了解该MCID的估算方法和样本特征等相关细节以判断是否适用于所开展的研究或临床场景。展开更多
This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is propos...This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time t. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters' values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integrated with the FD method to complete one cycle of LHS-FD simulation iteration. This process is repeated until n final iterations of LHS-FD are obtained. The means of these n final solutions (MLHFD solutions) are tabulated, graphed and analyzed. The numerical simulation results of MLHFD for the SEIR model are presented side-by-side with deterministic solutions obtained from the classical FD scheme and homotopy analysis method with Pade approximation (HAM-Pade). The present MLHFD results are also compared with the previous non-deterministic statistical estimations from 1995 to 2015. Good agreement between the two is perceived with small errors. MLHFD method can be used to predict future behavior, range and prediction interval for the epidemic model solutions. The expected profiles of the cocaine abuse subpopulations are projected until the year 2045. Both the statistical estimations and the deterministic results of FD and HAM-Pade are found to be within the MLHFD prediction intervals for all the years and for all the subpopulations considered.展开更多
文摘最小临床意义差值(minimal clinically important difference,MCID)的常用估算方法包括效标法、分布法和文献分析法等。目前MCID的估算方法众多且不统一,给MCID的确定、结果解释和应用带来了困难。鉴于目前各种估算方法均存在一定局限,建议同时使用多种估算方法获得多个MCID初步估算值,并以效标法为主、其他方法为辅或将多种方法通过统计整合的估算值来确定最终的MCID。MCID可协助进行临床研究结果的临床意义判断、样本量估算以及临床决策等,在具体应用之前,应充分了解该MCID的估算方法和样本特征等相关细节以判断是否适用于所开展的研究或临床场景。
文摘This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time t. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters' values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integrated with the FD method to complete one cycle of LHS-FD simulation iteration. This process is repeated until n final iterations of LHS-FD are obtained. The means of these n final solutions (MLHFD solutions) are tabulated, graphed and analyzed. The numerical simulation results of MLHFD for the SEIR model are presented side-by-side with deterministic solutions obtained from the classical FD scheme and homotopy analysis method with Pade approximation (HAM-Pade). The present MLHFD results are also compared with the previous non-deterministic statistical estimations from 1995 to 2015. Good agreement between the two is perceived with small errors. MLHFD method can be used to predict future behavior, range and prediction interval for the epidemic model solutions. The expected profiles of the cocaine abuse subpopulations are projected until the year 2045. Both the statistical estimations and the deterministic results of FD and HAM-Pade are found to be within the MLHFD prediction intervals for all the years and for all the subpopulations considered.
