An example of Covariate objectssampledata
aexplain. 解释。[translate] aCovariate analysis could be utilized to evaluate the effect of race on the pharmacokinetics of plinabulin. Covariate分析在plinabulin药物代谢动力学能被运用评估种族的作用。[translate] aAfter World War II,most farmers replaced wooden posts with new posts made of steel. 在...
# We also compute the principal covariate regression (PCovR) descriptors, # that reduce dimensionality while combining a variance preserving # criterion with the requirement that the low-dimensional features are # capable of estimating a target quantity (here, the energy). # # PCA pca = PCA(n...
The Wikipedia definition of ANCOVA is actually quite good and I won’t bother to repeat it. Some other keys phrases you’ll hear are that ANCOVA allows you to “control for” or “partial out” the covariate which gives you the opportunity to estimate ...
The global values were taken into account as described above (section “Processing of the Marseille database—Leave-one-out SPM analysis”) including age as a linear covariate. Other settings were as above. Clusters were again formed and corrected for multiple comparisons as described above. ...
Batch normaliza- tion: Accelerating deep network training by reducing internal covariate shift. In ICML, 2015. 4 [36] Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, and Michael C Mozer. Characterizing structural regular- ities of labeled data in overparameterized models. In ICML,...
Covariate-adjusted response adaptive A form of RAR (see the “Response-adaptive randomisation” section) that accounts for patient differences is covariate-adjusted response adaptive (CARA). Randomisation probabilities are aligned to the patient’s observed biomarker information skewing allocation probabilities...
First, in order to utilize a GAM to model FA values for white matter tracts of interest, we first organized the AFQ output into a data frame which contained the FA value of each tract node for each subject, factors for group and sex, and continuous covariate values; see Supplemental ...
Bertolet M, Brooks MM, Bittner V: Tree-based identification of subgroups for time-varying covariate survival data. Stat Methods Med Res. 2012, [Epub ahead of print] Google Scholar Sun Z, Tao Y, Li S, Ferguson KK, Meeker JD, Park SK, Batterman SA, Mukherjee B: Statistical strategies ...
Next, we add covariate rank on the initial model. model2 <- glm(data = mydata, admit ~ gre + gpa + as.factor(rank), family = "binomial") summary(model2) Note that rank of the undergraduate is categorical, so we need to change it using function "as. factor". This is the output...