From 004c188c9d227968a7c7295f73bab3358c663eb1 Mon Sep 17 00:00:00 2001 From: bailliem Date: Wed, 4 Dec 2024 22:32:57 +0100 Subject: [PATCH] remove ref to method_bayes seed --- tests/testthat/test-utils.R | 3 +-- vignettes/Analyse2_with_ADMI.Rmd | 5 ++--- vignettes/Single_analysis_workflow.Rmd | 6 +++--- vignettes/delta_analyse_mi_data.Rmd | 3 +-- 4 files changed, 7 insertions(+), 10 deletions(-) diff --git a/tests/testthat/test-utils.R b/tests/testthat/test-utils.R index be981f3..faaee21 100644 --- a/tests/testthat/test-utils.R +++ b/tests/testthat/test-utils.R @@ -27,8 +27,7 @@ test_that("positive test get_imputed_data (from vignettes)", { method <- rbmi::method_bayes( n_samples = N_IMPUTATIONS, burn_in = 200, - burn_between = 5, - seed = 675442751 + burn_between = 5 ) # Subset relevant columns diff --git a/vignettes/Analyse2_with_ADMI.Rmd b/vignettes/Analyse2_with_ADMI.Rmd index e694838..a747358 100644 --- a/vignettes/Analyse2_with_ADMI.Rmd +++ b/vignettes/Analyse2_with_ADMI.Rmd @@ -29,9 +29,9 @@ library(readr) library(purrr) library(rbmi) library(beeca) - library(rbmiUtils) +set.seed(1974) data("ADEFF") ## Global constants @@ -97,8 +97,7 @@ vars <- rbmi::set_vars( method <- rbmi::method_bayes( n_samples = N_IMPUTATIONS, burn_in = 200, - burn_between = 5, - seed = 675442751 + burn_between = 5 ) # Create a dataset with the necessary columns diff --git a/vignettes/Single_analysis_workflow.Rmd b/vignettes/Single_analysis_workflow.Rmd index f67d052..99a377c 100644 --- a/vignettes/Single_analysis_workflow.Rmd +++ b/vignettes/Single_analysis_workflow.Rmd @@ -26,6 +26,7 @@ This is an example of the {rbmi} only workflow. The analysis is as follows: Rubi This example exists to compare with the workflow which saves an ADMI data set, then uses {rbmiUtils} to complete the intended analysis. ```{r} +set.seed(1974) data("ADEFF") ## Global constants @@ -96,12 +97,11 @@ vars <- rbmi::set_vars( covariates = c("BASE", "STRATA", "REGION") ) -# Define which imputation method to use (here: Bayesian multiple imputation with 150 imputed datsets) +# Define which imputation method to use (here: Bayesian multiple imputation) method <- rbmi::method_bayes( n_samples = N_IMPUTATIONS, burn_in = 200, - burn_between = 5, - seed = 675442751 + burn_between = 5 ) # Create a dataset with the necessary columns diff --git a/vignettes/delta_analyse_mi_data.Rmd b/vignettes/delta_analyse_mi_data.Rmd index 09f8c84..807dad9 100644 --- a/vignettes/delta_analyse_mi_data.Rmd +++ b/vignettes/delta_analyse_mi_data.Rmd @@ -60,8 +60,7 @@ vars <- rbmi::set_vars( method <- rbmi::method_bayes( n_samples = N_IMPUTATIONS, burn_in = 200, - burn_between = 5, - seed = 675442751 + burn_between = 5 ) # Subset relevant columns