Minor documentation updates

NEWS.md

@@ -6,7 +6,8 @@
 
 To reduce the complexity of this package and help people understand what they 
 are getting, I have removed all functions that directly analyze 
-interaction/moderation effects and put them into a new package, `interactions`.
+interaction/moderation effects and put them into a new package, 
+[`interactions`](https://interactions.jacob-long.com).
 There are still some functions in `jtools` that support `interactions`, but
 some users may find that everything they ever used `jtools` for has now moved 
 to `interactions`. The following functions have moved to `interactions`:

README.Rmd

@@ -176,11 +176,31 @@ These show the 95% interval width of a normal distribution for each estimate.
 arguments like `robust` and `scale`. This enables a wider range of 
 models that have support from the `broom` package but not for `summ`. 
 
+### Plotting model predictions (`effect_plot`)
+
+Sometimes the best way to understand your model is to look at the predictions
+it generates. Rather than look at coefficients, `effect_plot` lets you plot
+predictions across values of a predictor variable alongside the observed data. 
+
+```{r}
+effect_plot(fit_c, pred = hp, interval = TRUE, plot.points = TRUE)
+```
+
+And a new feature in version `2.0.0` lets you plot *partial residuals*
+instead of the raw observed data, allowing you to assess model quality after
+accounting for effects of control variables.
+
+```{r}
+effect_plot(fit_c, pred = hp, interval = TRUE, partial.residuals = TRUE)
+```
+
+Categorical predictors, polynomial terms, (G)LM(M)s, weighted data, and much
+more are supported. 
+
 ### Other stuff
 
 There are several other things that might interest you.
 
-* `effect_plot`: Plot predicted lines from regression models 
 * `gscale`: Scale and/or mean-center data, including `svydesign` objects
 * `scale_mod` and `center_mod`: Re-fit models with scaled and/or mean-centered
 data