diff --git a/notebooks/aline/aline_propensity_score.Rmd b/notebooks/aline/aline_propensity_score.Rmd index 0ab9125..60f645c 100644 --- a/notebooks/aline/aline_propensity_score.Rmd +++ b/notebooks/aline/aline_propensity_score.Rmd @@ -145,7 +145,7 @@ library(Matching) set.seed(43770) -ps <- Match(Y=NULL, Tr=Tr, X=X, M=1, estimand='ATC', caliper=0.1, exact=FALSE, replace=FALSE); +ps <- Match(Y=NULL, Tr=Tr, X=X, M=1, estimand='ATT', caliper=0.1, exact=FALSE, replace=FALSE); # get pairs with treatment/outcome as cols outcome <- data.frame(aline_pt=y[ps$index.treated], match_pt=y[ps$index.control]) diff --git a/notebooks/aline/aline_propensity_score.html b/notebooks/aline/aline_propensity_score.html index 69050c0..b527994 100644 --- a/notebooks/aline/aline_propensity_score.html +++ b/notebooks/aline/aline_propensity_score.html @@ -715,16 +715,19 @@
set.seed(43770)
-ps <- Match(Y=NULL, Tr=Tr, X=X, M=1, estimand='ATC', caliper=0.1, exact=FALSE, replace=FALSE);
-
-# get pairs with treatment/outcome as cols
+ps <- Match(Y=NULL, Tr=Tr, X=X, M=1, estimand='ATT', caliper=0.1, exact=FALSE, replace=FALSE);
+## Warning in Match(Y = NULL, Tr = Tr, X = X, M = 1, estimand = "ATT", caliper
+## = 0.1, : replace==FALSE, but there are more (weighted) treated obs than
+## control obs. Some treated obs will not be matched. You may want to estimate
+## ATC instead.
+# get pairs with treatment/outcome as cols
outcome <- data.frame(aline_pt=y[ps$index.treated], match_pt=y[ps$index.control])
head(outcome)
## aline_pt match_pt
-## 1 0 1
-## 2 1 0
-## 3 1 0
-## 4 0 0
+## 1 0 0
+## 2 0 1
+## 3 0 0
+## 4 0 1
## 5 1 0
## 6 0 0
# mcnemar's test to see if iac related to mort (test should use matched pairs)
@@ -732,18 +735,18 @@ May 15, 2017
tab.match1
## Matched Control
## Aline 0 1
-## 0 578 122
-## 1 103 19
+## 0 582 118
+## 1 104 19
tab.match1[1,2]/tab.match1[2,1]
-## [1] 1.184466
+## [1] 1.134615
paste("95% Confint", round(exp(c(log(tab.match1[2,1]/tab.match1[1,2]) - qnorm(0.975)*sqrt(1/tab.match1[1,2] +1/tab.match1[2,1]),log(tab.match1[2,1]/tab.match1[1,2]) + qnorm(0.975)*sqrt(1/tab.match1[1,2] +1/tab.match1[2,1])) ),2))
-## [1] "95% Confint 0.65" "95% Confint 1.1"
+## [1] "95% Confint 0.68" "95% Confint 1.15"
mcnemar.test(tab.match1) # for 1-1 pairs
##
## McNemar's Chi-squared test with continuity correction
##
## data: tab.match1
-## McNemar's chi-squared = 1.44, df = 1, p-value = 0.2301
+## McNemar's chi-squared = 0.76126, df = 1, p-value = 0.3829
The above p-value, which is > 0.05, tells us that we cannot reject the null hypothesis of the aline/non-aline groups having the same mortality rate. Assuming all assumptions of our modelling process are correct, we can infer from this that the use of an indwelling arterial catheter is not associated with a mortality benefit in these patients.