Loading Data
library(readr)
data_M5<- read_csv("C:/Users/gmutya048/Downloads/data (4).csv")
##
## -- Column specification --------------------------------------------------------
## cols(
## `Patient ID` = col_double(),
## Gender = col_character(),
## Race = col_character(),
## Treatment = col_character(),
## Improved = col_character()
## )
data_M5$Improved <- plyr::mapvalues(data_M5$Improved, from = c("Y", "N"), to = c("Yes", "No"))
data_M5$Gender <- plyr::mapvalues(data_M5$Gender, from = c("M", "F"), to = c("Male", "Female"))
Analysis
df1<-table(data_M5$Treatment, data_M5$Improved, data_M5$Gender)
mantelhaen.test(df1)
##
## Mantel-Haenszel chi-squared test with continuity correction
##
## data: df1
## Mantel-Haenszel X-squared = 17.26, df = 1, p-value = 3.26e-05
## alternative hypothesis: true common odds ratio is not equal to 1
## 95 percent confidence interval:
## 3.115328 23.921939
## sample estimates:
## common odds ratio
## 8.632768
library(vcd)
## Loading required package: grid
woolf_test(df1)
##
## Woolf-test on Homogeneity of Odds Ratios (no 3-Way assoc.)
##
## data: df1
## X-squared = 0.02621, df = 1, p-value = 0.8714
There is no evidence to suggest that Gender impacts this joint association (??2 = 0.02621 p = 0.8714).
df2<-table(data_M5$Treatment, data_M5$Improved, data_M5$Race)
mantelhaen.test(df2)
##
## Mantel-Haenszel chi-squared test with continuity correction
##
## data: df2
## Mantel-Haenszel X-squared = 13.457, df = 1, p-value = 0.0002441
## alternative hypothesis: true common odds ratio is not equal to 1
## 95 percent confidence interval:
## 2.238563 14.959234
## sample estimates:
## common odds ratio
## 5.786811
library(vcd)
woolf_test(df2)
##
## Woolf-test on Homogeneity of Odds Ratios (no 3-Way assoc.)
##
## data: df2
## X-squared = 5.7032, df = 3, p-value = 0.127
Likewise there is no evidence to suggest that Race impacts this joint association (??2 = 5.7032 p = 0.127).
Tables and Figures
library(vcd)
mosaic(~Treatment +Improved, data = data_M5, shade=TRUE, legend=TRUE , main = "Improved", labeling = labeling_values)
library(vcd)
mosaic(~Treatment +Improved+Gender, data = data_M5, shade=TRUE, legend=TRUE , main = "Improved", labeling = labeling_values,)
library(vcd)
mosaic(~Treatment +Improved+Race, data = data_M5, shade=TRUE, legend=TRUE , main = "Improved", labeling = labeling_values)