## Not run:
# set.seed(1)
# d <- expand.grid(major=c('Alabama', 'Alaska', 'Arkansas'),
# minor=c('East', 'West'),
# group=c('Female', 'Male'),
# city=0:2)
# n <- nrow(d)
# d$x <- (1 : nrow(d)) + runif(n)
# d$num <- round(100*runif(n))
# d$denom <- d$num + round(100*runif(n))
# d$lower <- d$x - runif(n)
# d$upper <- d$x + runif(n)
#
# # numerators and denominators are meaningless in this example
# with(d,
# dotchartpl(x, major, minor, group, city, lower=lower, upper=upper,
# big=city==0, num=num, denom=denom, xlab='x'))
#
# n <- 500
# set.seed(1)
# d <- data.frame(
# race = sample(c('Asian', 'Black/AA', 'White'), n, TRUE),
# sex = sample(c('Female', 'Male'), n, TRUE),
# treat = sample(c('A', 'B'), n, TRUE),
# smoking = sample(c('Smoker', 'Non-smoker'), n, TRUE),
# hypertension = sample(c('Hypertensive', 'Non-Hypertensive'), n, TRUE),
# region = sample(c('North America','Europe','South America',
# 'Europe', 'Asia', 'Central America'), n, TRUE))
#
# d <- upData(d, labels=c(race='Race', sex='Sex'))
#
# dm <- addMarginal(d, region)
# s <- summaryP(race + sex + smoking + hypertension ~
# region + treat, data=dm)
#
# s$region <- ifelse(s$region == 'All', 'All Regions', as.character(s$region))
#
# with(s,
# dotchartpl(freq / denom, major=var, minor=val, group=treat, mult=region,
# big=region == 'All Regions', num=freq, denom=denom)
# )
#
# s2 <- s[- attr(s, 'rows.to.exclude1'), ]
# with(s2,
# dotchartpl(freq / denom, major=var, minor=val, group=treat, mult=region,
# big=region == 'All Regions', num=freq, denom=denom)
# )
# # Note these plots can be created by plot.summaryP when options(grType='plotly')
# ## End(Not run)
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