#74 udpate wording

Author: jeffreyad

adam/adae.qmd

@@ -85,7 +85,7 @@ metacore <- spec_to_metacore(
 
 # Select ADSL Variables {#adslvars}
 
-Some variables from the `ADSL` dataset required for the derivations are merged into the `AE` domain using the `admiral::derive_vars_merged()` function. Find other `{admiral}` variables and functions by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>). The rest of the relevant `ADSL` variables will be added later.
+Some variables from the `ADSL` dataset required for the derivations are merged into the `AE` domain using the `admiral::derive_vars_merged()` function. Find other `{admiral}` functions and related variables by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>). The rest of the relevant `ADSL` variables will be added later.
 
 ```{r}
 # Select required ADSL variables

adam/adpc.qmd

@@ -16,7 +16,7 @@ The Non-compartmental analysis (NCA) ADaM uses the CDISC Implementation Guide (<
 
 ## First Load Packages
 
-First we will load the packages required for our project. We will use `{admiral}` for the creation of analysis data. `{admiral}` requires `{dplyr}`, `{lubridate}` and `{stringr}`. Find `{admiral}` variables and functions by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>). We will use `{metacore}` and `{metatools}` to store and manipulate metadata from our specifications. We will use `{xportr}` to perform checks on the final data and export to a transport file.
+First we will load the packages required for our project. We will use `{admiral}` for the creation of analysis data. `{admiral}` requires `{dplyr}`, `{lubridate}` and `{stringr}`. Find other `{admiral}` functions and related variables by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>). We will use `{metacore}` and `{metatools}` to store and manipulate metadata from our specifications. We will use `{xportr}` to perform checks on the final data and export to a transport file.
 
 The source SDTM data will come from the CDISC pilot study data stored in `{pharmaversesdtm}`.
 

adam/adppk.qmd

@@ -16,7 +16,7 @@ The Population PK Analysis Data (ADPPK) follows the CDISC Implementation Guide (
 
 ## First Load Packages
 
-First we will load the packages required for our project. We will use `{admiral}` for the creation of analysis data. `{admiral}` requires `{dplyr}`, `{lubridate}` and `{stringr}`. Find `{admiral}` variables and functions by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>). We will use `{metacore}` and `{metatools}` to store and manipulate metadata from our specifications. We will use `{xportr}` to perform checks on the final data and export to a transport file.
+First we will load the packages required for our project. We will use `{admiral}` for the creation of analysis data. `{admiral}` requires `{dplyr}`, `{lubridate}` and `{stringr}`. Find other `{admiral}` functions and related variables by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>). We will use `{metacore}` and `{metatools}` to store and manipulate metadata from our specifications. We will use `{xportr}` to perform checks on the final data and export to a transport file.
 
 The source SDTM data will come from the CDISC pilot study data stored in `{pharmaversesdtm}`.
 

adam/adrs.qmd

@@ -14,7 +14,7 @@ source("functions/print_df.R")
 
 # Introduction
 
-The Response Analysis Dataset (`ADRS`) is an essential part of oncology clinical trials for monitoring disease response and progression. This article describes how to create an `ADRS` ADaM dataset, focusing on common oncology endpoint parameters based on RECIST v1.1 criteria. The primary response values include `CR` (Complete Response), `PR` (Partial Response), `SD` (Stable Disease), `NON-CR/NON-PD` (Non-CR/Non-PD), `PD` (Progressive Disease), and `NE` (Not Evaluable). See `{admiral}` and `{admiralonco}` for mor information. Find other `{admiral}` variables and functions by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>)
+The Response Analysis Dataset (`ADRS`) is an essential part of oncology clinical trials for monitoring disease response and progression. This article describes how to create an `ADRS` ADaM dataset, focusing on common oncology endpoint parameters based on RECIST v1.1 criteria. The primary response values include `CR` (Complete Response), `PR` (Partial Response), `SD` (Stable Disease), `NON-CR/NON-PD` (Non-CR/Non-PD), `PD` (Progressive Disease), and `NE` (Not Evaluable). See `{admiral}` and `{admiralonco}` for mor information. Find other `{admiral}` functions and related variables by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>)
 
 This guide uses key pharmaverse packages along with tidyverse components to demonstrate the step-by-step process, ensuring the inclusion of metadata, validation, and exporting to a compliant SAS transport file (XPT).
 

adam/adsl.qmd

@@ -20,7 +20,7 @@ The four packages used with a brief description of their purpose are as follows:
 
 -   [`{metacore}`](https://atorus-research.github.io/metacore/): provides harmonized metadata/specifications object.
 -   [`{metatools}`](https://pharmaverse.github.io/metatools/): uses the provided metadata to build/enhance and check the dataset.
--   [`{admiral}`](https://pharmaverse.github.io/admiral/index.html): provides the ADaM derivations. (Find variables and functions by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>))
+-   [`{admiral}`](https://pharmaverse.github.io/admiral/index.html): provides the ADaM derivations. (Find functions and related variables by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>))
 -   [`{xportr}`](https://atorus-research.github.io/xportr/): delivers the SAS transport file (XPT) and eSub checks.
 
 It is important to understand `{metacore}` objects by reading through the above linked package site, as these are fundamental to being able to use `{metatools}` and `{xportr}`.

adam/adtte.qmd

@@ -53,7 +53,7 @@ adrs <- adrs_onco
 
 # Define Event and Censoring Sources
 
-We define event and censoring sources using the `admiral::event_source()` and `admiral::censor_source()` functions. This forms the basis for calculating time-to-event endpoints. Find other `{admiral}` variables and functions by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>).
+We define event and censoring sources using the `admiral::event_source()` and `admiral::censor_source()` functions. This forms the basis for calculating time-to-event endpoints. Find other `{admiral}` functions and related variables by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>).
 
 ```{r}
 # Define event and censoring sources

adam/advs.qmd

@@ -43,7 +43,7 @@ For the purpose of this example, we will use the `ADSL` dataset from `{pharmaver
 
 # Load Data and Required pharmaverse Packages {#loaddata}
 
-First we will load the packages required for our project. We will use `{admiral}` for the creation of analysis data. `{admiral}` requires `{dplyr}`, `{lubridate}` and `{stringr}`. Find `{admiral}` variables and functions by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>). We will use `{metacore}` and `{metatools}` to store and manipulate metadata from our specifications. We will use `{xportr}` to perform checks on the final data and export to a transport file.
+First we will load the packages required for our project. We will use `{admiral}` for the creation of analysis data. `{admiral}` requires `{dplyr}`, `{lubridate}` and `{stringr}`. Find `{admiral}` functions and related variables by searching [admiraldiscovery](<https://pharmaverse.github.io/admiraldiscovery/articles/reactable.html>). We will use `{metacore}` and `{metatools}` to store and manipulate metadata from our specifications. We will use `{xportr}` to perform checks on the final data and export to a transport file.
 
 Then we will load our input data.