```
## artificial example
set.seed(1)
x <- matrix(rpois(5 * 3, 7), ncol = 5, nrow = 3)
dimnames(x) <- list(Row = head(letters, 3), Col = tail(letters, 5))
x_lor <- loddsratio(x)
coef(x_lor)
x_lor
confint(x_lor)
summary(x_lor)
## 2 x 2 x k cases
#data(CoalMiners, package = "vcd")
lor_CM <- loddsratio(CoalMiners)
lor_CM
coef(lor_CM)
confint(lor_CM)
confint(lor_CM, log = FALSE)
## 2 x k x 2
lor_Emp <-loddsratio(Employment)
lor_Emp
confint(lor_Emp)
## 4 way tables
data(Punishment, package = "vcd")
lor_pun <- loddsratio(Freq ~ memory + attitude | age + education, data = Punishment)
lor_pun
confint(lor_pun)
summary(lor_pun)
# fit linear model using WLS
lor_pun_df <- as.data.frame(lor_pun)
pun_mod1 <- lm(LOR ~ as.numeric(age) * as.numeric(education),
data = lor_pun_df, weights = 1 / ASE^2)
anova(pun_mod1)
## illustrate ref levels
VA.fem <- xtabs(Freq ~ left + right, subset=gender=="female", data=VisualAcuity)
VA.fem
loddsratio(VA.fem) # profile contrasts
loddsratio(VA.fem, ref=1) # contrasts against level 1
loddsratio(VA.fem, ref=dim(VA.fem)) # contrasts against level 4
```

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