## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(bwsTools) library(dplyr) library(tidyr) library(ggplot2) ## ----make_data, message=FALSE------------------------------------------------- dat <- vdata %>% group_by(issue) %>% summarise( totl = n(), best = sum(value == 1), wrst = sum(value == -1) ) ## ----show_dat----------------------------------------------------------------- dat ## ----ae_mnl------------------------------------------------------------------- res1 <- ae_mnl(dat, "totl", "best", "wrst") ## ----show ae_mnl_res---------------------------------------------------------- res1 ## ----------------------------------------------------------------------------- dat %>% bind_cols(res1) %>% arrange(b) %>% mutate(issue = factor(issue, issue)) %>% ggplot(aes(x = issue, y = b)) + geom_point() + geom_errorbar(aes(ymin = lb, ymax = ub), width = 0) + coord_flip() ## ----elo, eval=FALSE---------------------------------------------------------- # set.seed(1839) # res2 <- elo(vdata, "id", "block", "issue", "value") ## ----load_up_res2, include=FALSE---------------------------------------------- res2 <- structure(list(item = c("abortion", "biasmedia", "corruption", "crime", "drugs", "economy", "education", "foreignaffairs", "guns", "healthcare", "natsecurity", "race", "taxes"), elo = c(983.604707872469, 775.029578108074, 987.095165229659, 1005.70809857833, 908.116241829412, 1166.78863775417, 1065.4369480057, 858.26118119395, 1022.80855081941, 1194.37125023744, 1043.98840666976, 974.595472655393, 1013.59357525509 )), row.names = c(NA, -13L), class = c("tbl_df", "tbl", "data.frame" )) ## ----show_elo----------------------------------------------------------------- res2 ## ----correl------------------------------------------------------------------- cor(res1$b, res2$elo) plot(res1$b, res2$elo)