10compare.Rmd

# Compare Results {-}

Comparing `log(OR)` from all models (vertical line represents the true parameter for `log(OR)` when we generated the simulated data):

```{r, cache=TRUE, message=FALSE, warning=FALSE}
plot_summs(ITTFit, naivePPFit, BAdjPPFit, SIPWFit,
           scale = TRUE,
           robust = list("HC0","HC0","HC0", "HC0", "HC0"),
           model.names = c("ITT", "PP", "B-PP", "IPW-PP")) +
geom_vline(xintercept = 0.7)
```

Comparing `OR` from all models (vertical line represents the true parameter for `OR` when we generated the simulated data):

```{r, cache=TRUE, message=FALSE, warning=FALSE}
plot_summs(ITTFit, naivePPFit, BAdjPPFit, SIPWFit,
           scale = TRUE,
           exp = TRUE,
           robust = list("HC0","HC0","HC0", "HC0", "HC0"),
           model.names = c("ITT", "PP", "B-PP", "IPW-PP")) +
geom_vline(xintercept = exp(0.7))
```

In all of these cases, estimated parameters associated with `A` are of main interest.