diff --git a/_pkgdown.yml b/_pkgdown.yml
index d71acfb9..d0716d79 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -1,4 +1,8 @@
-url: ~
+url: https://pharmaverse.github.io/sdtm.oak
+
template:
bootstrap: 5
+ bootswatch: flatly
+navbar:
+ title: "sdtm.oak"
diff --git a/inst/template.R b/inst/create_cm_template.R
similarity index 94%
rename from inst/template.R
rename to inst/create_cm_template.R
index 5684f2ea..5b039a98 100644
--- a/inst/template.R
+++ b/inst/create_cm_template.R
@@ -1,6 +1,6 @@
# Name: CM domain
#
-# Label: R program to create MH Domain
+# Label: R program to create CM Domain
#
# Input raw data:
# study_sdtm_spec
@@ -74,7 +74,7 @@ cm <- MD1 |>
condition_left_raw_dataset = MD1,
condition_left_raw_variable = DOS,
condition_operator = "is_numeric",
- sub_algorithm = "assign_no_ct", #pass the function as the argument
+ sub_algorithm = assign_no_ct, #pass the function as the argument
target_sdtm_var = CMDOSE,
merge_to_topic_by = c(oak_id_vars,
topic_var_source = MDRAW)) |>
@@ -84,7 +84,7 @@ cm <- MD1 |>
condition_left_raw_dataset = MD1,
condition_left_raw_variable = DOS,
condition_operator = "is_character",
- sub_algorithm = "assign_no_ct",
+ sub_algorithm = assign_no_ct,
target_sdtm_var = CMDOSETXT,
merge_to_topic_by = c(oak_id_vars,
topic_var_source = MDRAW)) |>
@@ -96,7 +96,7 @@ cm <- MD1 |>
condition_operator = "diffferent_to",
condition_right_sdtm_variable_domain = CM,
condition_right_sdtm_variable = CMTRT,
- sub_algorithm = "assign_no_ct",
+ sub_algorithm = assign_no_ct,
target_sdtm_var = CMDOSETXT,
merge_to_topic_by = c(oak_id_vars,
topic_var_source = MDRAW)) |>
@@ -120,7 +120,7 @@ cm <- MD1 |>
condition_left_raw_dataset = MD1,
condition_left_raw_variable = MDPRIOR,
condition_operator = "if_checked",
- sub_algorithm = "assign_ct",
+ sub_algorithm = assign_ct,
target_sdtm_variable_codelist_code = "C66728",
target_sdtm_var = CMSTRTPT,
merge_to_topic_by = c(oak_id_vars,
@@ -131,7 +131,7 @@ cm <- MD1 |>
condition_left_raw_dataset = MD1,
condition_left_raw_variable = MDPRIOR,
condition_operator = "if_checked",
- sub_algorithm = "hardcode_no_ct",
+ sub_algorithm = hardcode_no_ct,
target_hardcoded_value = "SCREENING",
target_sdtm_var = CM.CMSTTPT,
merge_to_topic_by = c(oak_id_vars,
@@ -142,7 +142,7 @@ cm <- MD1 |>
condition_left_raw_dataset = MD1,
condition_left_raw_variable = MDONG,
condition_operator = "if_checked",
- sub_algorithm = "hardcode_ct",
+ sub_algorithm = hardcode_ct,
target_hardcoded_value = "ONGOING",
target_sdtm_variable_codelist_code = "C66728",
target_sdtm_var = CMENRTPT,
@@ -154,7 +154,7 @@ cm <- MD1 |>
condition_left_raw_dataset = MD1,
condition_left_raw_variable = MDONG,
condition_operator = "if_checked",
- sub_algorithm = "hardcode_no_ct",
+ sub_algorithm = hardcode_no_ct,
target_hardcoded_value = "DATE OF LAST ASSESSMENT",
target_sdtm_var = CMENTPT,
merge_to_topic_by = c(oak_id_vars,
diff --git a/vignettes/articles/algo_sub_algo_combo.jpg b/vignettes/articles/algo_sub_algo_combo.jpg
new file mode 100644
index 00000000..ff9246da
Binary files /dev/null and b/vignettes/articles/algo_sub_algo_combo.jpg differ
diff --git a/vignettes/articles/algorithms.Rmd b/vignettes/articles/algorithms.Rmd
new file mode 100644
index 00000000..10020463
--- /dev/null
+++ b/vignettes/articles/algorithms.Rmd
@@ -0,0 +1,211 @@
+---
+title: "Algorithms & Sub-Algorithms"
+output: rmarkdown::html_vignette
+vignette: >
+ %\VignetteIndexEntry{Algorithms}
+ %\VignetteEncoding{UTF-8}
+ %\VignetteEngine{knitr::rmarkdown}
+editor_options:
+ markdown:
+ wrap: 72
+---
+
+## Core Concept
+
+SDTM mappings are defined as algorithms that transform the collected
+(eCRF, eDT) source data into the target SDTM data model. Mapping
+algorithms are the backbone of the sdtm.oak - SDTM data transformation
+engine.
+
+**Key Points:**
+
+- Algorithms can be re-used across multiple SDTM domains.
+
+- Algorithms are pre-specified for data collection standards in MDR
+ (if applicable)
+
+- Programming language agnostic - this concept does not rely on a
+ specific programming language for implementation. The OAK team
+ implemented them as R functions.
+
+Here is an example of reusing an algorithm across multiple domains,
+variables, and also to a non-standard
+
+
+
+## List of Algorithms
+
+```{r echo = FALSE, results = "asis"}
+library(knitr)
+algorithms <- data.frame(
+ `Algorithm Name` = c(
+ "ASSIGN_NO_CT",
+ "ASSIGN_CT",
+ "AE_AEREL",
+ "HARDCODE_CT",
+ "HARDCODE_NO_CT",
+ "DATASET_LEVEL",
+ "NOTSUBMITTED",
+ "IF_THEN_ELSE",
+ "MERGE",
+ "RELREC",
+ "MULTIPLE_RESPONSES",
+ "SPLIT_TO_SUPPQUAL",
+ "REMOVE_DUP",
+ "GROUP_BY"
+ ),
+ `Description` = c(
+ paste(
+ "One-to-one mapping between the raw source and a target",
+ "SDTM variable that has no controlled terminology restrictions.",
+ "Just a simple assignment",
+ "statement. This algorithm will also handle the concatenation of",
+ "multiple items into a target SDTM variable."
+ ),
+ paste(
+ "One-to-one mapping between the raw source and a target ",
+ "SDTM variable that is subject to controlled terminology restrictions.",
+ "A simple assign statement and applying controlled terminology.",
+ "This will be used only if the SDTM variable has an associated",
+ "controlled terminology."
+ ),
+ paste(
+ "Algorithm that is currently unique to AE.AEREL,",
+ "particularly when more than one drug is used in the study.
If any collected study drug",
+ "causalities are 'Yes' then AE.AEREL is Y.
If all collected study",
+ "drug causalities are 'NA' then AE.AEREL is NA.
If no study drug",
+ "causalities are 'Yes' but there is at least one causality of 'No'",
+ "then AE.AEREL is N.
Individual study drug causality responses are",
+ "stored in AERELn in SUPPAE."
+ ),
+ paste(
+ "Mapping a hardcoded value to a target SDTM variable that is subject to terminology restrictions.",
+ "This will be used only if the SDTM variable has an associated",
+ "controlled terminology."
+ ),
+ paste(
+ "Mapping a hardcoded value to a target SDTM variable that has no terminology restrictions."
+ ),
+ paste(
+ "Indicates a dataset-level mapping. These mappings will",
+ "be applied to all SDTM records created from that source.",
+ "Also called a eCRF-level mappings in eCRF and dataset-level",
+ "mappings in eDT"
+ ),
+ paste(
+ "Instruction that `sdtm.oak` should not map the collected item to SDTM at all."
+ ),
+ paste(
+ "Represents the If then else statement. This can be an if statement",
+ "with no else or with the else condition. This algorithm will be",
+ "used for the annotations where a condition has to be evaluated",
+ "before a mapping is performed. A sub-algorithm is required. If the",
+ "condition resolves to `TRUE`, the sub-algorithm will be executed."
+ ),
+ paste(
+ "To indicate a join condition with a secondary source or multiple sources.",
+ "Merges are expressed at the domain level only",
+ "(not at data point or variable level).",
+ "This is a sub-algorithm and can only be used with algorithm DATASET_LEVEL."
+ ),
+ paste(
+ "Associate two domains based on the variables in each domain and how those are related.",
+ "Specifies the name of two domains that are related via RELREC."
+ ),
+ paste(
+ "Consolidate the responses from more than one source variable into one target variable.",
+ "Used when multiple responses may be given for a single SDTM column.",
+ "`sdtm.oak` will populate all target variable(s) after determining the number of responses provided."
+ ),
+ paste(
+ "Consolidates the responses from more than one",
+ "source variable into more than one target variable",
+ "(always a suppqual/non-standard variable).",
+ "There is no 'parent' target variable that is populated with 'MULTIPLE'."
+ ),
+ paste(
+ "Sub-algorithm at the domain level that indicates some source records may",
+ "be removed during the `sdtm.oak` mapping process if determined to be duplicate records."
+ ),
+ paste(
+ "Sub-algorithm used at the domain level to group source records",
+ "before mapping to SDTM. This is used in the event we need to collapse data",
+ "collected across multiple rows into one row in SDTM but it is not a simple",
+ "un-duplication effort. For example, the way infusion study drug",
+ "administration data requires us to create 1 SDTM record in EC from 1 or more source",
+ "records in the mixed log form. When there is more than one source record,",
+ "we need to take the earliest collected infusion start date (for ECSTDTC) and",
+ "the latest collected infusion end date within an eCRF instance."
+ )
+ ),
+ `Example` = c(
+ paste(
+ "MH.MHTERM
",
+ "VS.VSDTC
",
+ "MH.MHTERM = [LNGCAHX1.HSTYP] || ' ' || 'NON-METASTATIC LUNG CANCER'
",
+ "CM.CMINDC = [MD9.MDCIND] || ' ' || [MD9.MDCINDSP]"
+ ),
+ paste("VS.VSPOS
", "VS.VSLAT"),
+ paste("For AE.AEREL and AERELn in SUPPAE"),
+ paste(
+ "MH.MHPRESP = 'Y'
",
+ "VS.VSTEST = 'Systolic Blood Pressure'
",
+ "VS.VSORRESU = 'mmHg'
"
+ ),
+ paste("FA.FASCAT = 'COVID-19 PROBABLE CASE'
",
+ "CM.CMTRT = 'FLUIDS'"),
+ paste(
+ "VS = 'Vital Signs'
",
+ "MH.MHCAT = 'PROSTATE CANCER HISTORY'
"
+ ),
+ paste(""),
+ paste(
+ "If 'Ongoing' then MH.MHENRTPT = 'ONGOING'
Else MH.MHENRTPT = 'BEFORE'
",
+ "If [HX1.STATUS] is present then MH.MHENTPT = 'FIRST DOSE OF STUDY DRUG'
",
+ "If checked then MH.MHSTTPT = 'SCREENING'
Else NOT SUBMITTED
",
+ "VS.VSMETHOD when VS.VSTESTCD = 'TEMP'",
+ "(Though the annotation text does not have the If condition,",
+ "we need to map VSMETHOD only if the VSTESTCD is TEMP. The IF_THEN_ELSE will be",
+ "used as the Algorithm for such cases even the 'If' condition is not explicitly",
+ "defined in the annotation text)"
+ ),
+ paste("AE = 'Adverse Events' on the early phase SAE eCRF"),
+ paste("BE record related to BS record via RELREC"),
+ paste(
+ "AE.AERELNST/ AERELNSn IN SUPPAE
",
+ "DM.RACE, if only one value is selected.
",
+ "DM.RACE = MULTIPLE, if more than one value is selected.
",
+ "RACEn in SUPPDM where n = 1 to N selected values"
+ ),
+ paste(
+ "If both Filipino and Samoan are checked,",
+ "CRACE1 will be 'FILIPINO' and CRACE2 will be 'SAMOAN'.
",
+ "If only Chinese is checked, CRACE1 will be 'CHINESE'."
+ ),
+ paste("AE = 'Adverse Events' on early phase SAE form"),
+ paste("EC = 'Exposure as Collected'")
+ )
+)
+knitr::kable(algorithms)
+```
+
+## Sub-algorithms
+
+sdtm.oak supports two levels for defining algorithms. For example, there
+are some SDTM mappings where a certain action has to be taken only when
+a condition is met. In such cases, the primary algorithm checks for the
+condition, and the sub-algorithm executes the mappings when the
+condition is met.
+
+Currently, sub-algorithms must be provided for these main algorithms.
+
+- IF_THEN_ELSE
+- DATASET_LEVEL
+
+Algorithms can be interchangeably used as algorithms and as
+sub-algorithms as seen below (not an exhaustive list)
+
+
+
+The permutation & combination of algorithms & sub-algorithms creates
+endless possibilities to accommodate different types of mappings.
diff --git a/vignettes/articles/reusable_algorithms.jpg b/vignettes/articles/reusable_algorithms.jpg
new file mode 100644
index 00000000..71c8962b
Binary files /dev/null and b/vignettes/articles/reusable_algorithms.jpg differ
diff --git a/vignettes/study_sdtm_spec.Rmd b/vignettes/articles/study_sdtm_spec.Rmd
similarity index 99%
rename from vignettes/study_sdtm_spec.Rmd
rename to vignettes/articles/study_sdtm_spec.Rmd
index 4645d76a..9bb740cd 100644
--- a/vignettes/study_sdtm_spec.Rmd
+++ b/vignettes/articles/study_sdtm_spec.Rmd
@@ -254,7 +254,7 @@ definition <- data.frame(
"VTLS1, DEM",
"1, 2, 3, etc",
"Vital Signs,
Demographics",
- "SYSBP,
BRTHDD",
+ "SEX_001,
BRTHDD",
"Systolic Blood Pressure,
Birth Day",
"1, 2, 3, etc",
"Text Box,
Date control",