Manisha Desai,Aya A Mitani,Susan W Bryson et al.
Manisha Desai et al.
Little research has been devoted to multiple imputation (MI) of derived variables. This study investigates various MI approaches for the outcome, rate of change, when the analysis model is a two-stage linear regression. Simulations showed t...
Using multiple imputation to address the inconsistent distribution of a controlling variable when modeling an infrequent outcome [0.03%]
利用多重插补解决建模罕见结果时控制变量分布不一致的问题
Yujia Zhang,Sara Crawford,Sheree L Boulet et al.
Yujia Zhang et al.
Temporal changes in methods for collecting longitudinal data can generate inconsistent distributions of affected variables, but effects on parameter estimates have not been well described. We examined differences in Apgar scores of infants ...
Semiparametric Mixed Models for Nested Repeated Measures Applied to Ambulatory Blood Pressure Monitoring Data [0.03%]
嵌套重复测量的半参数混合模型及在动态血压监测数据中的应用
Rhonda D Szczesniak,Dan Li,Raouf S Amin
Rhonda D Szczesniak
Semiparametric mixed models are increasingly popular for statistical analysis of medical device studies in which long sequences of repeated measurements are recorded. Monitoring these sequences at different periods over time on the same ind...
Compound Identification Using Penalized Linear Regression on Metabolomics [0.03%]
基于代谢组学的惩罚线性回归化合物识别方法
Ruiqi Liu,Dongfeng Wu,Xiang Zhang et al.
Ruiqi Liu et al.
Compound identification is often achieved by matching the experimental mass spectra to the mass spectra stored in a reference library based on mass spectral similarity. Because the number of compounds in the reference library is much larger...
Statistical Power of Alternative Structural Models for Comparative Effectiveness Research: Advantages of Modeling Unreliability [0.03%]
替代结构模型的统计功效：建模不可靠性的优势
Emil N Coman,Eugen Iordache,Lisa Dierker et al.
Emil N Coman et al.
The advantages of modeling the unreliability of outcomes when evaluating the comparative effectiveness of health interventions is illustrated. Adding an action-research intervention component to a regular summer job program for youth was ex...
A Monte Carlo Power Analysis of Traditional Repeated Measures and Hierarchical Multivariate Linear Models in Longitudinal Data Analysis [0.03%]
纵向数据分析中传统重复测量与多层次 multivariate 线性模型的Monte Carlo功率分析
Hua Fang,Gordon P Brooks,Maria L Rizzo et al.
Hua Fang et al.
The power properties of traditional repeated measures and hierarchical linear models have not been clearly determined in the balanced design for longitudinal studies in the current literature. A Monte Carlo power analysis of traditional rep...
Covariate-Adjusted Constrained Bayes Predictions of Random Intercepts and Slopes [0.03%]
调整协变量的约束贝叶斯随机效应预测方法
Robert H Lyles,Reneé H Moore,Amita K Manatunga et al.
Robert H Lyles et al.
Constrained Bayes methodology represents an alternative to the posterior mean (empirical Bayes) method commonly used to produce random effect predictions under mixed linear models. The general constrained Bayes methodology of Ghosh (1992) i...
A Spline-Based Lack-Of-Fit Test for Independent Variable Effect in Poisson Regression [0.03%]
基于样条的泊松回归中自变量效应的不匹配检验方法
Chin-Shang Li,Wanzhu Tu
Chin-Shang Li
In regression analysis of count data, independent variables are often modeled by their linear effects under the assumption of log-linearity. In reality, the validity of such an assumption is rarely tested, and its use is at times unjustifia...
Dongfeng Wu,Xiaoqin Wu,Ioana Banicescu et al.
Dongfeng Wu et al.
A general simulation procedure is described to validate model fitting algorithms for complex likelihood functions that are utilized in periodic cancer screening trials. Although screening programs have existed for a few decades, there are s...
Type I Error Rates For A One Factor Within-Subjects Design With Missing Values [0.03%]
具有缺失值的单因素被试内设计的一类错误率
Miguel A Padilla,James Algina
Miguel A Padilla
Missing data are a common problem in educational research. A promising technique, that can be implemented in SAS PROC MIXED and is therefore widely available, is to use maximum likelihood to estimate model parameters and base hypothesis tes...