From 87646551a454ee4004be45a6ded3ddcda55ea7c1 Mon Sep 17 00:00:00 2001
From: Grace Skinner
@@ -99,6 +99,8 @@ install.packages(path_to_file, repos = NULL, type = "source") # where path_to_fi
### Using the Dynameta package
+Any meta-analysis must be underpinned by a robust evidence gathering framework, which must be completed before proceeding with Dynameta. This includes writing and registering a protocol outlining clearly defined research questions and evidence inclusion criteria, carefully considering the suitability of evidence based on these criteria, and determining who will be responsible for updating the meta-analysis with Dynameta, and for how long (as to avoid research waste). Please refer to the guidance documents listed below in the 'Resources' tab section.
+
Once you have successfully installed Dynameta, to access help documentation, run:
```
help(package = "Dynameta")
@@ -150,10 +152,10 @@ sample_data
### Resources tab
* Contains useful links to guidance developed by communities of practice when conducting evidence syntheses. These include:
+ * [Collaboration for Environmental Evidence (CEE)](https://environmentalevidence.org/). See [here](https://environmentalevidence.org/information-for-authors) for full guidance document.
* [PRISMA](http://www.prisma-statement.org/) - For reporting systematic reviews and meta-analysis (developed for medical field but see ecology specific version below).
* [PRISMA Extension for Ecology and Evolution](http://www.prisma-statement.org/Extensions/EcoEvo) - For conducting environmental evidence syntheses.
* [ROSES](https://www.roses-reporting.com/) - For reporting systematic reviews and meta-analysis (developed for environmental research).
- * [Collaboration for Environmental Evidence (CEE)](https://environmentalevidence.org/). See [here](https://environmentalevidence.org/information-for-authors) for full guidance document.
* [Cochrane Handbook for Systematic Reviews of Interventions](https://training.cochrane.org/handbook/current) - For conducting systematic reviews (developed for medical field).
* [Campbell Collaboration](https://www.campbellcollaboration.org/research-resources/training-courses.html) - For conducting evidence syntheses (developed for social sciences field).
* The following are useful guides for conducting meta-analyses:
@@ -173,6 +175,7 @@ sample_data
* sample_data.R - describes the sample data included with the package that can be analysed using the Dynameta Shiny app (necessary to make the help documentation for the dataset).
* data
* sample_data.rda - R data file containing the sample data.
+* docs - directory for building the Dynameta pkgdown website.
* inst
* Dynameta_app
* server.R - defines how the Dynameta Shiny app works (back-end development).
@@ -192,11 +195,13 @@ sample_data
* man
* launch_Dynameta.Rd - R documentation file for the launch_Dynameta() function.
* sample_data.Rd - R documentation file for the sample data.
+ * figures - images needed for pkgdown website.
* tests
* testthat/test-shinytest2_test.R - test driver script that runs the shinytest2 tests in the inst/Dynameta_app/tests directory.
* testthat.R - part of standard setup for testthat.
* vignettes
* Dynameta.Rmd - R markdown document for the Dynameta package and Shiny app vignette.
+* CITATION.cff - citation file for Dynameta.
* DESCRIPTION - overall metadata about the Dynameta package.
* LICENSE - declare Dynameta package as licensed.
* LICENSE.md - includes a copy of the full text of the license.
diff --git a/docs/articles/Dynameta.html b/docs/articles/Dynameta.html
index e063426..1318fb3 100644
--- a/docs/articles/Dynameta.html
+++ b/docs/articles/Dynameta.html
@@ -95,10 +95,10 @@
IUCN
threats classification scheme) on biodiversity. Nevertheless, the
code can be easily repurposed to suit a variety of meta-analytic
-contexts. The server.R and ui.R files that define the Dynameta Shiny app
-can be found in the Dynameta_app/ directory. On github, Dynameta_app/
-can be found in the inst/
+contexts. Please see the Editing
+the codebase section of this vignette for an example of this. The
+server.R and ui.R files that define the Dynameta Shiny app can be found
+in the Dynameta_app/ directory. On github, Dynameta_app/ can be found in
+the inst/
directory. If you have installed the package, the Dynameta_app/
directory can be found directly in the package root directory, alongside
the DESCRIPTION, NAMESPACE, etc. files.
Any meta-analysis must be underpinned by a robust evidence gathering +framework, which must be completed before proceeding with Dynameta. This +includes writing and registering a protocol outlining clearly defined +research questions and evidence inclusion criteria, carefully +considering the suitability of evidence based on these criteria, and +determining who will be responsible for updating the meta-analysis with +Dynameta, and for how long (as to avoid research waste). Please refer to +the resources listed in the README.
+Once you have successfully installed Dynameta, to access help documentation, run:
@@ -254,8 +265,7 @@2. Run models tabDynameta will run the model in real-time and produce a forest plot of the results. This includes an estimate of the overall effect size of your chosen IUCN threat on biodiversity. -
You are also able to download the model object (.rds) and a file -containing the results summary of the model fitting (.txt). +There are options available to download the results. @@ -283,13 +293,22 @@
Editing the codebaseDynameta GitHub repo, or +
Careful consideration needs to be taken when conducting sub-group +analysis, both in terms of deciding when it is appropriate to carry out, +and when interpreting the results. As a guide, the Cochrane +Handbook section 10.11.5.1 suggests that at least ten data points +need to be available for each sub-group modelled. For a guide to +interpreting the results, please see Richardson +et al. (2019).
++
To add sub-group analysis as an option in Dynameta, you need access +to the scripts that need to be edited. Possible options are to fork the +Dynameta GitHub repo, or download the repo as a zipped file.
Next you will need to open the ui.R and server.R files that make up the Dynameta shiny app. These are in the /inst/Dynameta_app/ @@ -343,7 +362,7 @@
2 ### Running custom models
Code/text to alter/add:
-# Alter this text to describe difference between subset analysis and subgroup analysis
+# Alter this text to describe difference between subset analysis and sub-group analysis
## Comment out this original text ##
#p(h5("Based on your research question, you can filter the data by threat, location, taxonomic order, and biodiversity metric.")),
@@ -356,7 +375,7 @@ 2
and run a meta-analytic model on this subset of data."),
$li("Choose a moderator variable and carry out a full sub-group analysis
tags (meta-regression with a categorical predictor) to see if the pooled effect sizes
- found in these subgroups differ from each other.")
+ found in these sub-groups differ from each other.")
)),
Insert the code beneath these lines of code:
# Download forest plot button
-output$download_forest_plot <- shiny::downloadHandler(
+output$download_forest_plot <- shiny::downloadHandler(
filename = function() {
paste0("forest_plot", base::Sys.Date(), ".png", sep="")
@@ -533,7 +552,7 @@ 1
Code to add:
## Make reactive moderator (for sub-group analysis) choices
-output$reactive_moderator_choice <- shiny::renderUI({
+output$reactive_moderator_choice <- shiny::renderUI({
shinyWidgets::pickerInput(inputId = "moderator_choice",
label = "Moderator:",
choices = base::names(data()),
@@ -544,7 +563,7 @@ 1
### Run model
# Run sub-group analysis model once the run model button has been pressed
-sub_group_analysis <- shiny::eventReactive(input$run_sub_group_analysis, {
+sub_group_analysis <- shiny::eventReactive(input$run_sub_group_analysis, {
subgroup_analysis_data <- data()
@@ -583,15 +602,15 @@ 1
}, error = function(e) {
# If model does not successfully run, stop the process and return this error message
- base::stop(shiny::safeError(paste0("This model failed to run. This may be due to insufficient data for this model to run, but please see the R error message: ", e)))
+ base::stop(shiny::safeError(paste0("This model failed to run. This may be due to insufficient data for this model to run, but please see the R error message: ", e)))
})
})
### Render the model summary output
-output$subgroup_model_output <- shiny::renderPrint({
+output$subgroup_model_output <- shiny::renderPrint({
- shiny::req(sub_group_analysis())
+ shiny::req(sub_group_analysis())
base::summary(sub_group_analysis())
@@ -613,6 +632,18 @@ 1
Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch +VA (editors). Cochrane Handbook for Systematic Reviews of Interventions +version 6.3 (updated February 2022). Cochrane, 2022. Available from +www.training.cochrane.org/handbook.
+Richardson, M., Garner, P., & Donegan, S. (2019). Interpretation +of subgroup analyses in systematic reviews: A tutorial. Clinical +Epidemiology and Global Health, 7(2), 192–198. https://doi.org/10.1016/j.cegh.2018.05.005
+Meta-analyses are used to quantitatively summarise evidence across studies in a systematic process. Their larger sample size (and hence power) compared to individual research studies increases the chance of detecting significant effects.
-Despite representing a significant improvement upon individual studies, meta-analyses have a number of limitations which Dynameta was developed to overcome: 1. Meta-analytic results are based on a snapshot of literature at a particluar time. As a living review platform, Dynameta overcomes this by enabling results to be continually updated as new evidence becomes available. 2. Meta-analytic publications are resticted to presenting the results of the chosen questions asked by those researchers. On the other hand, Dynameta allows investigation of a range of questions based on varying interests of researchers through manipulation of the graphical user interface.
-Dynameta is designed for interactive ecological meta-analyses, oriented around testing the effect of anthropogenic threats (based on the IUCN threats classification scheme) on biodiversity. Nevertheless, the code can be easily repurposed to suit a variety of meta-analytic contexts. The server.R and ui.R files that define the Dynameta Shiny app can be found in the Dynameta_app/ directory. Here on github, Dynameta_app/ can be found in the inst/ directory. If you have installed the package, the Dynameta_app/ directory can be found directly in the package root directory, alongside the DESCRIPTION, NAMESPACE, etc. files.
-For an example of how the codebase can be edited to suit a specific user’s needs, please see the last section of the Dynameta vignette (Get started).
+Despite representing a significant improvement upon individual studies, meta-analyses have a number of limitations which Dynameta was developed to overcome: 1. Meta-analytic results are based on a snapshot of literature at a particular time. As a living review platform, Dynameta overcomes this by enabling results to be continually updated as new evidence becomes available. 2. Meta-analytic publications are restricted to presenting the results of the chosen questions asked by those researchers. On the other hand, Dynameta allows investigation of a range of questions based on varying interests of researchers through manipulation of the graphical user interface.
+Dynameta is designed for interactive ecological meta-analyses, oriented around testing the effect of anthropogenic threats (based on the IUCN threats classification scheme) on biodiversity. Nevertheless, the code can be easily repurposed to suit a variety of meta-analytic contexts. For an example of how the codebase can be edited to suit a specific user’s needs, please see the last section of the Dynameta vignette (Get started). The server.R and ui.R files that define the Dynameta Shiny app can be found in the Dynameta_app/ directory. Here on github, Dynameta_app/ can be found in the inst/ directory. If you have installed the package, the Dynameta_app/ directory can be found directly in the package root directory, alongside the DESCRIPTION, NAMESPACE, etc. files.
Dynameta was developed as part of the GLiTRS project, a cross-institutional consortium aiming to build global threat-response models to better understand and predict insect biodiversity change.
Any meta-analysis must be underpinned by a robust evidence gathering framework, which must be completed before proceeding with Dynameta. This includes writing and registering a protocol outlining clearly defined research questions and evidence inclusion criteria, carefully considering the suitability of evidence based on these criteria, and determining who will be responsible for updating the meta-analysis with Dynameta, and for how long (as to avoid research waste). Please refer to the guidance documents listed below in the ‘Resources’ tab section.
Once you have successfully installed Dynameta, to access help documentation, run:
help(package = "Dynameta")
Launch the Dynameta Shiny app:
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