## Not run:
# prep <- estimateEffect(1:3 ~ treatment, gadarianFit, gadarian)
# plot.estimateEffect(prep, "treatment", model=gadarianFit,
# method="pointestimate")
# plot.estimateEffect(prep, "treatment", model=gadarianFit,
# method="difference",cov.value1=1,cov.value2=0)
#
# #If the covariate were a binary factor,
# #the factor labels can be used to
# #specify the values of cov.value1 (e.g., cov.value1="treat").
#
# # String variables must be turned to factors prior to plotting.
# #If you see this error, Error in rep.int(c(1, numeric(n)), n - 1L) :
# # invalid 'times' value, then you likely have not done this.
#
# #Example of binary times binary interaction
# gadarian$binaryvar <- sample(c(0,1), nrow(gadarian), replace=T)
# temp <- textProcessor(gadarian$open.ended.response,metadata=gadarian)
# out <- prepDocuments(temp$documents, temp$vocab, temp$meta)
# stm1 <- stm(out$documents, out$vocab, 3, prevalence=~treatment*binaryvar,
# data=gadarian)
# prep <- estimateEffect(c(2) ~ treatment*binaryvar, stmobj=stm1,
# metadata=gadarian)
#
# par(mfrow=c(1,2))
# plot.estimateEffect(prep, "treatment", method="pointestimate",
# cov.value1=1, cov.value2=0, xlim=c(-1,1), moderator="binaryvar", moderator.value=1)
# plot.estimateEffect(prep, "treatment", method="pointestimate",
# cov.value1=1, cov.value2=0, xlim=c(-1,1), moderator="binaryvar",
# moderator.value=0)
# ## End(Not run)
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