library(dplyr)
 
gss = read.csv(file.choose(), header=T) # "GSS3.csv"
str(gss) # structure

gss = gss[(gss$happy!="Don't know") & (gss$happy!="No answer"),]
gss = gss[(gss$jobsecok!="Dont know") & (gss$jobsecok!="No answer") 
 & (gss$jobsecok!="Not applicable"),]
tbl = table(gss$jobsecok, gss$happy)

library(DescTools)
GoodmanKruskalGamma(x,y) # if above individual vectors
GoodmanKruskalGamma(tbl, conf.level=.95) # easier

KendallTauB(tbl, conf.level=.95)
ConDisPairs(tbl)

source(file.choose()) # choose MantelHaenszel.R

# two-way table of jobsecok (rows) and happy (columns)
tbl = matrix(c(15,21,64,73,25,47,248,474,5,21,100,311),nrow=4)

# user input scores u and v -- need to match the dimensions of tbl 
u = c(1,2,3,4); v = c(1,2,3)
MH.test(tbl, u, v)

# no user input scores, uses midranks
MH.test.mid(tbl)