diff --git a/vignettes/ebola.Rmd b/vignettes/ebola.Rmd
index e764eabb8..cde97afd4 100644
--- a/vignettes/ebola.Rmd
+++ b/vignettes/ebola.Rmd
@@ -216,13 +216,13 @@ Now we are ready to fit the latent individual model.
 We start by fitting a single lognormal distribution to the data. 
 This model assumes that a single distribution describes all delays in the data, regardless of the case's location, sex, or any other covariates.
 To do this, we set `formula = bf(mu ~ 1, sigma ~ 1)` to place an model with only and intercept parameter (i.e. `~ 1` in R formula syntax) on the `mu` and `sigma` parameters of the lognormal distribution.
-This distribution is specified using `family = "lognormal"`.
+This distribution is specified using `family = lognormal()`.
 
 ```{r}
 fit <- epidist(
   data = obs_prep,
   formula = bf(mu ~ 1, sigma ~ 1),
-  family = "lognormal",
+  family = lognormal(),
   algorithm = "sampling",
   refresh = 0,
   silent = 2,
@@ -246,7 +246,7 @@ To fit a model which varies the parameters of the fitted lognormal distribution,
 fit_sex <- epidist(
   data = obs_prep,
   formula = bf(mu ~ 1 + sex, sigma ~ 1 + sex),
-  family = "lognormal",
+  family = lognormal(),
   algorithm = "sampling",
   refresh = 0,
   silent = 2,
@@ -275,7 +275,7 @@ fit_sex_district <- epidist(
     mu ~ 1 + sex + (1 | district),
     sigma ~ 1 + sex + (1 | district)
   ),
-  family = "lognormal",
+  family = lognormal(),
   algorithm = "sampling",
   refresh = 0,
   silent = 2,