Merge pull request #277 from istallworthy/debugging

desc

DESCRIPTION

@@ -7,9 +7,8 @@ Authors@R: c(person("Isabella", "Stallworthy", email = "[email protected]",
 	                 comment=c(ORCID="0000-0003-3067-7154")),
             person("Meriah", "DeJoseph", email = "[email protected]", role = c("aut")),
             person("Emily", "Padrutt", email = "[email protected]", role = c("aut")),
-            person("Kyle", "Butts", email = "[email protected]", role = c("aut", ctb")),
-            person("Daniel", "Berry", email = "[email protected]", role = c("aut"))
-)
+            person("Kyle", "Butts", email = "[email protected]", role = c("aut", "ctb")),
+            person("Daniel", "Berry", email = "[email protected]", role = c("aut")))
 Description: Functions for implementing MSMS with longitudinal data.
 License: GPL-3
 Encoding: UTF-8

vignettes/Workflow_Continuous_Exposure.qmd

@@ -459,7 +459,7 @@ weights.cbps <- createWeights(obj = obj,
                              method = method,
                              formulas = formulas,
                              verbose = TRUE,
-                             maxit = 1, # just for testing to speed up --will remove
+                             maxit = 1, # just for testing to speed up
                              save.out = save.out)
 ```
 
@@ -535,16 +535,16 @@ As shown above, the GLM method produces a higher median of 1.27 and a much great
 # weights.gbm <- createWeights(obj = obj,
 #                              data = data,
 #                              method = method,
-#                              formulas = formulas, 
+#                              formulas = formulas,
 #                              save.out = save.out)
 # 
-# print(weights.gbm, 
+# print(weights.gbm,
 #       i = 1)
 # 
 # summary(weights.gbm[[1]])
 # 
-# plot(weights.gbm, 
-#      i = 1, 
+# plot(weights.gbm,
+#      i = 1,
 #      save.out = save.out)
 ```