Fix prior scales typo in dietary fat example (issue #34)

dmphillippo · Apr 19, 2024 · c40a1fa · c40a1fa
1 parent 1d93c6a
commit c40a1fa
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Showing 3 changed files with 231 additions and 223 deletions.
diff --git a/tests/testthat/test-example_dietary_fat.R b/tests/testthat/test-example_dietary_fat.R
@@ -8,17 +8,17 @@ skip_on_cran()
 params <-
 list(run_tests = FALSE)
 
-## ----code=readLines("children/knitr_setup.R"), include=FALSE--------------------------------------
+## ---- code=readLines("children/knitr_setup.R"), include=FALSE-------------------------------------
 
 
-## ----eval = FALSE---------------------------------------------------------------------------------
+## ---- eval = FALSE--------------------------------------------------------------------------------
 ## library(multinma)
 ## options(mc.cores = parallel::detectCores())
 
 ## ----setup, echo = FALSE--------------------------------------------------------------------------
 library(multinma)
-nc <- switch(tolower(Sys.getenv("_R_CHECK_LIMIT_CORES_")), 
-             "true" =, "warn" = 2, 
+nc <- switch(tolower(Sys.getenv("_R_CHECK_LIMIT_CORES_")),
+             "true" =, "warn" = 2,
              parallel::detectCores())
 options(mc.cores = nc)
 
@@ -28,10 +28,10 @@ head(dietary_fat)
 
 
 ## -------------------------------------------------------------------------------------------------
-diet_net <- set_agd_arm(dietary_fat, 
+diet_net <- set_agd_arm(dietary_fat,
                         study = studyc,
                         trt = trtc,
-                        r = r, 
+                        r = r,
                         E = E,
                         trt_ref = "Control",
                         sample_size = n)
@@ -43,7 +43,7 @@ summary(normal(scale = 100))
 
 
 ## -------------------------------------------------------------------------------------------------
-diet_fit_FE <- nma(diet_net, 
+diet_fit_FE <- nma(diet_net,
                    trt_effects = "fixed",
                    prior_intercept = normal(scale = 100),
                    prior_trt = normal(scale = 100))
@@ -53,7 +53,7 @@ diet_fit_FE <- nma(diet_net,
 diet_fit_FE
 
 
-## ----eval=FALSE-----------------------------------------------------------------------------------
+## ---- eval=FALSE----------------------------------------------------------------------------------
 ## # Not run
 ## print(diet_fit_FE, pars = c("d", "mu"))
 
@@ -67,19 +67,19 @@ summary(normal(scale = 100))
 summary(half_normal(scale = 5))
 
 
-## ----eval=FALSE-----------------------------------------------------------------------------------
+## ---- eval=FALSE----------------------------------------------------------------------------------
 ## diet_fit_RE <- nma(diet_net,
 ##                    trt_effects = "random",
-##                    prior_intercept = normal(scale = 10),
-##                    prior_trt = normal(scale = 10),
+##                    prior_intercept = normal(scale = 100),
+##                    prior_trt = normal(scale = 100),
 ##                    prior_het = half_normal(scale = 5))
 
-## ----echo=FALSE, warning=FALSE--------------------------------------------------------------------
+## ---- echo=FALSE, warning=FALSE-------------------------------------------------------------------
 diet_fit_RE <- nowarn_on_ci(
-                 nma(diet_net, 
+                 nma(diet_net,
                      trt_effects = "random",
-                     prior_intercept = normal(scale = 10),
-                     prior_trt = normal(scale = 10),
+                     prior_intercept = normal(scale = 100),
+                     prior_trt = normal(scale = 100),
                      prior_het = half_normal(scale = 5))
                  )
 
@@ -88,7 +88,7 @@ diet_fit_RE <- nowarn_on_ci(
 diet_fit_RE
 
 
-## ----eval=FALSE-----------------------------------------------------------------------------------
+## ---- eval=FALSE----------------------------------------------------------------------------------
 ## # Not run
 ## print(diet_fit_RE, pars = c("d", "mu", "delta"))
 
@@ -113,15 +113,15 @@ plot(dic_RE)
 
 
 ## ----diet_pred_FE, fig.height = 2-----------------------------------------------------------------
-pred_FE <- predict(diet_fit_FE, 
-                   baseline = distr(qnorm, mean = -3, sd = 1.77^-0.5), 
+pred_FE <- predict(diet_fit_FE,
+                   baseline = distr(qnorm, mean = -3, sd = 1.77^-0.5),
                    type = "response")
 pred_FE
 plot(pred_FE)
 
 ## ----diet_pred_RE, fig.height = 2-----------------------------------------------------------------
-pred_RE <- predict(diet_fit_RE, 
-                   baseline = distr(qnorm, mean = -3, sd = 1.77^-0.5), 
+pred_RE <- predict(diet_fit_RE,
+                   baseline = distr(qnorm, mean = -3, sd = 1.77^-0.5),
                    type = "response")
 pred_RE
 plot(pred_RE)

diff --git a/vignettes/example_dietary_fat.Rmd b/vignettes/example_dietary_fat.Rmd
@@ -98,16 +98,16 @@ Fitting the RE model
 ```{r, eval=FALSE}
 diet_fit_RE <- nma(diet_net, 
                    trt_effects = "random",
-                   prior_intercept = normal(scale = 10),
-                   prior_trt = normal(scale = 10),
+                   prior_intercept = normal(scale = 100),
+                   prior_trt = normal(scale = 100),
                    prior_het = half_normal(scale = 5))
 ```
 ```{r, echo=FALSE, warning=FALSE}
 diet_fit_RE <- nowarn_on_ci(
                  nma(diet_net, 
                      trt_effects = "random",
-                     prior_intercept = normal(scale = 10),
-                     prior_trt = normal(scale = 10),
+                     prior_intercept = normal(scale = 100),
+                     prior_trt = normal(scale = 100),
                      prior_het = half_normal(scale = 5))
                  )
 ```