使用 R 的“CBPS”包后如何访问匹配的数据集?
How to access matched dataset after using `CBPS` package of R?
我正在使用 CBPS
R 包对数据集与两级治疗组进行倾向得分匹配。
这是我写的代码:
fit <- CBPS(formula=formu1, data = data2, ATT = TRUE, twostep = FALSE, standardize = TRUE)
rr.att.CBPS <- Match(Y=Y, Tr=Tr, X=fitted(fit), M=1, ties=FALSE, replace=FALSE, estimand='ATT')
但是,如何访问匹配的数据集进行分析?
我建议您改用 MatchIt
包。
想象一个名为 'dataset' 的数据集,其中包含一个二元处理组 (T) 和一些其他协变量 (V1,V2,V3) 和一个目标变量 (p)。
install.packages("MatchIt") #if not installed before
library("MatchIt") #importing MatchIt
# Formula for matching(include other covariates which treatment groups will be matched based on them, eg. V1 & V2)
formula <- "T ~ V1+V2"
formula <- as.formula(formula) #making formula format
#implementing matching process with nearest neighbour method with 2:1 ratio by logistic regression
matched_data <- matchit(formula, method = "nearest", ratio = 2, data = dataset, link = "logit")
# assigning matched data to a variable which then can be used for further analysis such as regression
final_matched <- match.data(mached_data)
# Absolute standardized mean difference plot of variables used to match for assessment of balance before and after matching
plot(summary(matched_data))
我正在使用 CBPS
R 包对数据集与两级治疗组进行倾向得分匹配。
这是我写的代码:
fit <- CBPS(formula=formu1, data = data2, ATT = TRUE, twostep = FALSE, standardize = TRUE)
rr.att.CBPS <- Match(Y=Y, Tr=Tr, X=fitted(fit), M=1, ties=FALSE, replace=FALSE, estimand='ATT')
但是,如何访问匹配的数据集进行分析?
我建议您改用 MatchIt
包。
想象一个名为 'dataset' 的数据集,其中包含一个二元处理组 (T) 和一些其他协变量 (V1,V2,V3) 和一个目标变量 (p)。
install.packages("MatchIt") #if not installed before
library("MatchIt") #importing MatchIt
# Formula for matching(include other covariates which treatment groups will be matched based on them, eg. V1 & V2)
formula <- "T ~ V1+V2"
formula <- as.formula(formula) #making formula format
#implementing matching process with nearest neighbour method with 2:1 ratio by logistic regression
matched_data <- matchit(formula, method = "nearest", ratio = 2, data = dataset, link = "logit")
# assigning matched data to a variable which then can be used for further analysis such as regression
final_matched <- match.data(mached_data)
# Absolute standardized mean difference plot of variables used to match for assessment of balance before and after matching
plot(summary(matched_data))