An Investigation of the Impact of Misrouting Under Two-Stage Multistage Testing: A Simulation Study

2014 ◽  
Vol 2014 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Sooyeon Kim ◽  
Tim Moses
Keyword(s):  
Simulation Study ◽  
Two Stage ◽  
Multistage Testing ◽  
The Impact

scholarly journals A Simulation Study of the Impact of LP EGR on a Two-Stage Turbocharged Diesel Engine

2009 ◽  
Vol 64 (3) ◽  
pp. 361-379 ◽  
Author(s):  
P. Gautier ◽  
A. Albrecht ◽  
A. Chasse ◽  
P. Moulin ◽  
A. Pagot ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Simulation Study ◽  
Two Stage ◽  
Turbocharged Diesel Engine ◽  
The Impact

scholarly journals Robust Inferences from a Before-and-After Study with Multiple Unaffected Control Groups

2013 ◽  
Vol 1 (2) ◽  
pp. 209-234 ◽  
Author(s):  
Pengyuan Wang ◽  
Mikhail Traskin ◽  
Dylan S. Small
Keyword(s):  
Sensitivity Analysis ◽  
Control Groups ◽  
Two Stage ◽  
Time Effects ◽  
Unaffected Control ◽  
Group Time ◽  
Before And After ◽  
Group Variation ◽  
The Impact ◽  
Before And After Study

AbstractThe before-and-after study with multiple unaffected control groups is widely applied to study treatment effects. The current methods usually assume that the control groups’ differences between the before and after periods, i.e. the group time effects, follow a normal distribution. However, there is usually no strong a priori evidence for the normality assumption, and there are not enough control groups to check the assumption. We propose to use a flexible skew-t distribution family to model group time effects, and consider a range of plausible skew-t distributions. Based on the skew-t distribution assumption, we propose a robust-t method to guarantee nominal significance level under a wide range of skew-t distributions, and hence make the inference robust to misspecification of the distribution of group time effects. We also propose a two-stage approach, which has lower power compared to the robust-t method, but provides an opportunity to conduct sensitivity analysis. Hence, the overall method of analysis is to use the robust-t method to test for the overall hypothesized range of shapes of group variation; if the test fails to reject, use the two-stage method to conduct a sensitivity analysis to see if there is a subset of group variation parameters for which we can be confident that there is a treatment effect. We apply the proposed methods to two datasets. One dataset is from the Current Population Survey (CPS) to study the impact of the Mariel Boatlift on Miami unemployment rates between 1979 and 1982.The other dataset contains the student enrollment and grade repeating data in West Germany in the 1960s with which we study the impact of the short school year in 1966–1967 on grade repeating rates.

scholarly journals A Two-Stage Joint Model for Nonlinear Longitudinal Response and a Time-to-Event with Application in Transplantation Studies

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Magdalena Murawska ◽  
Dimitris Rizopoulos ◽  
Emmanuel Lesaffre
Keyword(s):  
Empirical Bayes ◽  
Cox Model ◽  
Data Sets ◽  
Two Stage ◽  
Nonlinear Mixed Effects Model ◽  
Resistance Evolution ◽  
Longitudinal Response ◽  
Longitudinal Measurements ◽  
Subject Specific ◽  
The Impact

In transplantation studies, often longitudinal measurements are collected for important markers prior to the actual transplantation. Using only the last available measurement as a baseline covariate in a survival model for the time to graft failure discards the whole longitudinal evolution. We propose a two-stage approach to handle this type of data sets using all available information. At the first stage, we summarize the longitudinal information with nonlinear mixed-effects model, and at the second stage, we include the Empirical Bayes estimates of the subject-specific parameters as predictors in the Cox model for the time to allograft failure. To take into account that the estimated subject-specific parameters are included in the model, we use a Monte Carlo approach and sample from the posterior distribution of the random effects given the observed data. Our proposal is exemplified on a study of the impact of renal resistance evolution on the graft survival.

scholarly journals The impact of excluding or including Death Certificate Initiated (DCI) cases on estimated cancer survival: A simulation study

2021 ◽  
Vol 71 ◽  
pp. 101881
Author(s):  
Therese M.-L. Andersson ◽  
Tor Åge Myklebust ◽  
Mark J. Rutherford ◽  
Bjørn Møller ◽  
Isabelle Soerjomataram ◽  
...  
Keyword(s):  
Simulation Study ◽  
Cancer Survival ◽  
Death Certificate ◽  
The Impact

scholarly journals When does the use of individual patient data in network meta-analysis make a difference? A simulation study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Steve Kanters ◽  
Mohammad Ehsanul Karim ◽  
Kristian Thorlund ◽  
Aslam Anis ◽  
Nick Bansback
Keyword(s):  
Simulation Study ◽  
Treatment Effect ◽  
Mean Squared Error ◽  
Individual Patient Data ◽  
Meta Analysis ◽  
Model Performance ◽  
Patient Data ◽  
Meta Regression ◽  
Treatment Comparisons ◽  
The Impact

Abstract Background The use of individual patient data (IPD) in network meta-analyses (NMA) is rapidly growing. This study aimed to determine, through simulations, the impact of select factors on the validity and precision of NMA estimates when combining IPD and aggregate data (AgD) relative to using AgD only. Methods Three analysis strategies were compared via simulations: 1) AgD NMA without adjustments (AgD-NMA); 2) AgD NMA with meta-regression (AgD-NMA-MR); and 3) IPD-AgD NMA with meta-regression (IPD-NMA). We compared 108 parameter permutations: number of network nodes (3, 5 or 10); proportion of treatment comparisons informed by IPD (low, medium or high); equal size trials (2-armed with 200 patients per arm) or larger IPD trials (500 patients per arm); sparse or well-populated networks; and type of effect-modification (none, constant across treatment comparisons, or exchangeable). Data were generated over 200 simulations for each combination of parameters, each using linear regression with Normal distributions. To assess model performance and estimate validity, the mean squared error (MSE) and bias of treatment-effect and covariate estimates were collected. Standard errors (SE) and percentiles were used to compare estimate precision. Results Overall, IPD-NMA performed best in terms of validity and precision. The median MSE was lower in the IPD-NMA in 88 of 108 scenarios (similar results otherwise). On average, the IPD-NMA median MSE was 0.54 times the median using AgD-NMA-MR. Similarly, the SEs of the IPD-NMA treatment-effect estimates were 1/5 the size of AgD-NMA-MR SEs. The magnitude of superior validity and precision of using IPD-NMA varied across scenarios and was associated with the amount of IPD. Using IPD in small or sparse networks consistently led to improved validity and precision; however, in large/dense networks IPD tended to have negligible impact if too few IPD were included. Similar results also apply to the meta-regression coefficient estimates. Conclusions Our simulation study suggests that the use of IPD in NMA will considerably improve the validity and precision of estimates of treatment effect and regression coefficients in the most NMA IPD data-scenarios. However, IPD may not add meaningful validity and precision to NMAs of large and dense treatment networks when negligible IPD are used.

Molecular Dynamics Study on the Impact of the Cutting Depth to the Titanium Nanometric Cutting

2014 ◽  
Vol 536-537 ◽  
pp. 1431-1434 ◽  
Author(s):  
Ying Zhu ◽  
Yin Cheng Zhang ◽  
Shun He Qi ◽  
Zhi Xiang
Keyword(s):  
Molecular Dynamics ◽  
Potential Energy ◽  
Cutting Force ◽  
Simulation Study ◽  
Cutting Process ◽  
Work Piece ◽  
Cutting Depth ◽  
Nanometric Cutting ◽  
The Impact

Based on the molecular dynamics (MD) theory, in this article, we made a simulation study on titanium nanometric cutting process at different cutting depths, and analyzed the changes of the cutting depth to the effects on the work piece morphology, system potential energy, cutting force and work piece temperature in this titanium nanometric cutting process. The results show that with the increase of the cutting depth, system potential energy, cutting force and work piece temperature will increase correspondingly while the surface quality of machined work piece will decrease.

Effect of female executives on Chinese cultural media enterprise efficiency

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ying Li ◽  
Yung-Ho Chiu ◽  
Tai-Yu Lin ◽  
Hongyi Cen
Keyword(s):  
Boards Of Directors ◽  
Company Performance ◽  
Tobit Regression ◽  
Female Executives ◽  
Two Stage ◽  
Content Type ◽  
Female Directors ◽  
The Impact ◽  
Cultural Media ◽  
Better Than

Purpose As more women are now being appointed to senior and top management positions and invited to sit on boards of directors, they are now directly participating in strategic company decision-making. As female directors have been found to provide new ideas, increase company competitiveness, efficiency and performance and bring a greater number of external resources to a company than male directors, this paper aims to put female directors as a variable into the data envelopment analysis (DEA) and statistical models to explore the effect of female directors on operating performances. The DEA first quantified and measured the company efficiencies, after which the statistical model analyzed the correlations between the variables to specifically identify the impact of female decision makers on the operating efficiencies in state-owned and private enterprises. Design/methodology/approach A novel two-stage, meta-hybrid dynamic DEA was developed to explore Chinese cultural media company efficiencies under optimal input and output resource allocations, after which Tobit Regression was applied to determine the effect of female executives on these efficiencies. Findings From 2012 to 2016, the overall efficiencies in Chinese state-owned cultural media enterprises were better than in the private cultural media enterprises. The overall technology gaps (TGs) in the state-owned cultural media enterprises were better than in the private cultural media enterprises. Originality/value Previous research has tended to focus on the causal relationships between female senior executives and business performances; however, there have been few studies on the relationships between female executives and company performance from an efficiency perspective (optimal resource allocation). This paper, therefore, is the first to develop a novel two-stage, meta-hybrid dynamic DEA to examine Chinese cultural media enterprise efficiencies, and the first to apply Tobit Regression to assess the effect of female executives on those efficiencies.

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