常见的解决方法是将连续变量分类,但类别数目和节点位置的选择往往带有主观性,并且分类往往会损失信息。因此,一个更好的解决方法是拟合自变量与因变量之间的非线性关系,限制性立方(Restricted cubic spline,RCS)就是分析非线性关系的最常见的...
常见的解决方法是将连续变量分类,但类别数目和节点位置的选择往往带有主观性,并且分类往往会损失信息。因此,一个更好的解决方法是拟合自变量与因变量之间的非线性关系,限制性立方(Restricted cubic spline,RCS)就是分析非线性关系的最常见的方法之一。 近年来在Lancet、BMJ等杂志经常见到利用限制性立方样条来拟合非线性关...
常见的解决方法是将连续变量分类,但类别数目和节点位置的选择往往带有主观性,并且分类往往会损失信息。因此,一个更好的解决方法是拟合自变量与因变量之间的非线性关系,限制性立方(Restricted cubic spline,RCS)就是分析非线性关系的最常见的方法之一。 近年来在Lancet、BMJ等杂志经常见到利用限制性立方样条来拟合非线性关...
Restricted cubic splines (RCS) have many advantages but they have one big disadvantage: The resultant output is not always easy to interpret. Two aspects of splines that we have not touched on is the number of knots to allow and how to place them. Various proposals have been made, but ...
I've made a macro to estimate restricted cubic spline (RCS) basis in SPSS. Splines are useful tools to model non-linear relationships. Splines are useful exploratory tools to model non-linear relationships by transforming the independent variables in multiple regression equations. SeeDurrleman and ...
mm<-lrm(diabetes~pregnant+glucose+pressure+triceps+insulin+mass+pedigree+rcs(age,k),x=T,y=T,data=PimaIndiansDiabetes2) an<-anova(mm) ggplot(Predict(mm),anova=an,pval=TRUE) 结果4: 输入5: pred.or<-Predict(mm,age=seq...
We investigated the relationship between medication adherence as a continuous measure and outcomes in MI survivors using restricted cubic splines (RCS). We identified all patients aged 鈮 65 years hospitalised for MI from 2003鈥 2008 who survived one-year post-discharge (n = 5938). Adherence to ...
The relationship of age and the cancer-specific mortality of CC was fit by univariate Cox regression with restricted cubic spline (RCS) analyses (knot = 5)19. The cut-off values were set for age stratification in CC patients based on the inflection points in RCS. OS and CSS of ...
Cox regression models with restricted cubic splines were adjusted for: age, sex, Accessibility/Remoteness Index of Australia, history of: hypertension, heart failure, atrial fibrillation, diabetes, chronic obstructive pulmonary disease, chronic kidney disease, stroke, peripheral vascular disease, coronary ...
RCS curves for a Cox regression model rcsplot(data=cancer,outcome="status",time="time",exposure="age",covariates=c("sex","race","size","metastasis")) ## ## Figure: Association Between age and status Using a Restricted Cubic Spline Regression Model. ## Graphs show HRs for status accordin...