UCI Machine learning crime unnormalize data

Creating Odds ratio plot comparing leading causes of death by airway disease

Odds ratio were obtained from logistic regression model comparing chronic respiratory causes of death by type of airway disease controlling age, sex, and smoking status Here is the table airway_dis or lcl ucl ACOS 4.8 2.4 9.6 Asthma 1.8 0.8 3.8 COPD 2.8 1.6 4.9 Code is given below: library(readxl) datf <- read_excel("~/Desktop/aCOS mortality/part III/Book2.xlsx") View(datf) library(ggplot2) library (ggthemes) ggplot(datf, aes(x = airway_dis, y = or, ymin = lcl, ymax = ucl)) + geom_pointrange(aes(col = factor(airway_dis)), position=position_dodge(width=0.30)) + ylab("Odds ratio & 95% CI") + geom_hline(aes(yintercept = 1)) + scale_color_discrete(name = "Airway disease") + xlab("") + theme_solarized() + scale_fill_solarized()

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