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Issue #337: Use family as string in Ebola vignette #423

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Issue #337: Use family as string in Ebola vignette #423

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059e829
Try using string in Ebola vignette
athowes Nov 6, 2024
9295ed5
Try strings as factors fix
athowes Nov 7, 2024
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10 changes: 6 additions & 4 deletions vignettes/ebola.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,8 @@ knitr::opts_chunk$set(
warning = FALSE,
error = FALSE
)

options(stringsAsFactors = FALSE)
```

In this vignette, we use the `epidist` package to analyze line list data from the 2014-2016 outbreak of Ebola in Sierra Leone [@who_ebola_2014_2016].
Expand Down Expand Up @@ -220,15 +222,15 @@ 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 = mu ~ 1` to place an model with only an intercept parameter (i.e. `~ 1` in R formula syntax) on the `mu` parameter of the lognormal distribution specified using `family = lognormal()`.
To do this, we set `formula = mu ~ 1` to place an model with only an intercept parameter (i.e. `~ 1` in R formula syntax) on the `mu` parameter of the lognormal distribution specified using `family = "lognormal"`.
(Note that the lognormal distribution has two distributional parameters `mu` and `sigma`.
As a model is not explicitly placed on `sigma`, a constant model `sigma ~ 1` is assumed.)

```{r}
fit <- epidist(
data = obs_prep,
formula = mu ~ 1,
family = lognormal(),
family = "lognormal",
algorithm = "sampling",
refresh = 0,
silent = 2,
Expand All @@ -252,7 +254,7 @@ 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,
Expand Down Expand Up @@ -281,7 +283,7 @@ fit_sex_district <- epidist(
mu ~ 1 + sex + (1 | district),
sigma ~ 1 + sex + (1 | district)
),
family = lognormal(),
family = "lognormal",
algorithm = "sampling",
refresh = 0,
silent = 2,
Expand Down
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