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Merge pull request #57 from Merck/56-release-v011
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update arguments
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wangben718 committed Jul 3, 2024
2 parents 62e0447 + 7bb7dae commit 7d9720c
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Showing 9 changed files with 34 additions and 11 deletions.
7 changes: 7 additions & 0 deletions NEWS.md
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@@ -1,5 +1,12 @@
# forestly 0.1.1

- Add button to display SOC column for subset
- Refine the default value of `meta_forestly()`
- Update `format_ae_listing()` to be better aligned with oncology AEs reporting
- Enhance functionality related to drill-down listing
- Inherit paramter_term from all parameters of a metadata by default (#20)
- Allow user to specify treatment group (#15)
- Add warning when using tibble as input (#17)
- Fix bug when there is no record of a selected AE category (#9).
- Fix bug when there are multiple plots displayed on one page (#12).
- Update dataset `forestly_adae` since a variable was a factor
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4 changes: 2 additions & 2 deletions R/meta_forestly.R
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Expand Up @@ -47,8 +47,8 @@ meta_forestly <- function(
population_term = "apat",
observation_term = "safety",
parameter_term = "any;rel",
population_subset = SAFFL == "Y",
observation_subset = SAFFL == "Y",
population_subset,
observation_subset,
treatment_group = "TRTA") {
meta <- metalite::meta_adam(
population = as.data.frame(dataset_adsl),
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3 changes: 2 additions & 1 deletion R/prepare_ae_forestly.R
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Expand Up @@ -41,6 +41,7 @@ prepare_ae_forestly <- function(
population = NULL,
observation = NULL,
parameter = NULL,
components = "par",
reference_group = NULL,
ae_listing_display = c(
"USUBJID", "SITEID", "SEX", "RACE", "AGE", "ASTDY", "AESER",
Expand Down Expand Up @@ -101,7 +102,7 @@ prepare_ae_forestly <- function(
metalite.ae::prepare_ae_specific(meta,
population = population, observation = observation,
parameter = x,
components = c("soc", "par"),
components = components,
reference_group = reference_group
) |>
metalite.ae::extend_ae_specific_inference() |>
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4 changes: 2 additions & 2 deletions man/meta_forestly.Rd

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3 changes: 3 additions & 0 deletions man/prepare_ae_forestly.Rd

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4 changes: 3 additions & 1 deletion vignettes/forestly-cran.Rmd
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Expand Up @@ -18,7 +18,9 @@ forestly_adae$TRTA <- factor(forestly_adae$TRTA, levels = c("Xanomeline Low Dose
meta_forestly(
dataset_adsl = forestly_adsl,
dataset_adae = forestly_adae
dataset_adae = forestly_adae,
population_subset = SAFFL == "Y",
observation_subset = SAFFL == "Y"
) |>
prepare_ae_forestly(parameter = "any;rel;ser") |>
format_ae_forestly() |>
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8 changes: 6 additions & 2 deletions vignettes/forestly.Rmd
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Expand Up @@ -50,7 +50,9 @@ forestly_adae$TRTA <- factor(forestly_adae$TRTA, levels = c("Xanomeline Low Dose
meta_forestly(
dataset_adsl = forestly_adsl,
dataset_adae = forestly_adae,
parameter_term = "any;rel;ser"
parameter_term = "any;rel;ser",
population_subset = SAFFL == "Y",
observation_subset = SAFFL == "Y"
) |>
prepare_ae_forestly() |>
format_ae_forestly() |>
Expand Down Expand Up @@ -87,7 +89,9 @@ to generate the interactive forest plot.
meta_forestly(
dataset_adsl = forestly_adsl,
dataset_adae = forestly_adae,
parameter_term = "any;rel;ser"
parameter_term = "any;rel;ser",
population_subset = SAFFL == "Y",
observation_subset = SAFFL == "Y"
)
```

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4 changes: 3 additions & 1 deletion vignettes/layout.Rmd
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Expand Up @@ -40,7 +40,9 @@ The `outdata` contains all the parameters required to generate the interactive f
metadata <- meta_forestly(
dataset_adsl = forestly_adsl_3grp,
dataset_adae = forestly_adae_3grp,
parameter_term = "any;rel;ser"
parameter_term = "any;rel;ser",
population_subset = SAFFL == "Y",
observation_subset = SAFFL == "Y"
)
outdata <- metadata |> prepare_ae_forestly()
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8 changes: 6 additions & 2 deletions vignettes/meta-forestly.Rmd
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Expand Up @@ -72,7 +72,9 @@ If the deliverable requires a forest plot of all adverse events and serious adve
meta_forestly(
dataset_adsl = forestly_adsl,
dataset_adae = forestly_adae,
parameter_term = "any;ser"
parameter_term = "any;ser",
population_subset = SAFFL == "Y",
observation_subset = SAFFL == "Y"
) |>
prepare_ae_forestly() |>
format_ae_forestly() |>
Expand All @@ -85,7 +87,9 @@ However, if grade 3-5 adverse events need to be plotted as well, we can add `g35
meta_forestly(
dataset_adsl = forestly_adsl,
dataset_adae = forestly_adae,
parameter_term = "any;ser;g35"
parameter_term = "any;ser;g35",
population_subset = SAFFL == "Y",
observation_subset = SAFFL == "Y"
) |>
prepare_ae_forestly() |>
format_ae_forestly() |>
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