Restored original favicons, simplified function titles in documentations, and added rest of cchsflow badges in README

Author: rafdoodle

R/alcohol.R

@@ -1,4 +1,4 @@
-#' @title Calculate the Low Drink Score for a CHMS Respondent Based on Alcohol Consumption
+#' @title Low risk drinking score
 #'
 #' @description
 #' This function calculates a low drink score (step 1 only) for a respondent using
@@ -85,7 +85,7 @@ low_drink_score_fun <- function(CLC_SEX, ALC_11, ALCDWKY) {
   return(low_drink_score)
 }
 
-#' @title Calculate Low Drink Score According to Canada's Low-Risk Drinking Guidelines
+#' @title Low risk drinking score - former/never categories
 #'
 #' @description
 #' Computes a categorical alcohol consumption score based on Canada's Low-Risk Alcohol Drinking Guidelines (Step 1),
@@ -122,18 +122,13 @@ low_drink_score_fun <- function(CLC_SEX, ALC_11, ALCDWKY) {
 #'
 #' \strong{Step 2: Determine the final categorical score.}
 #' \itemize{
-#'   \item If Step 1 = 0:
+#'   \item If the point score from Step 1 is 0, the final category is determined based on lifetime and past-year drinking habits:
 #'     \itemize{
-#'       \item If ALC_17 == 2 and ALC_11 == 2: score = 1
-#'       \item If ALC_17 == 1 and ALC_11 == 2:
-#'         \itemize{
-#'           \item ALC_18 == 2: score = 1
-#'           \item ALC_18 == 1: score = 2
-#'         }
-#'       \item If ALC_11 == 1: score = 2
+#'       \item A score of 1 (Never drinker) is assigned if the respondent either never drank alcohol in their lifetime or is a former drinker who did not regularly consume more than 12 drinks a week.
+#'       \item A score of 2 (Low-risk drinker) is assigned if the respondent drank in the past year (but still scored 0 points) or is a former drinker with a history of regularly consuming more than 12 drinks a week.
 #'     }
-#'   \item If Step 1 = 1 or 2: score = 3
-#'   \item If Step 1 is 3 or more: score = 4
+#'   \item If the point score from Step 1 is 1 or 2, the respondent is classified as a \strong{Moderate drinker} (Score = 3).
+#'   \item If the point score from Step 1 is 3 or more, the respondent is classified as a \strong{Heavy drinker} (Score = 4).
 #' }
 #'
 #' @note

R/blood-pressure.R

@@ -1,4 +1,4 @@
-#' @title Adjust systolic blood pressure
+#' @title Adjusted systolic blood pressure
 #'
 #' @description This function adjusts systolic blood pressure based on the respondent's systolic average blood pressure across
 #' six measurements. The adjustment is made using specific correction factors. The adjusted systolic blood pressure
@@ -33,7 +33,7 @@ adjust_SBP <- function(BPMDPBPS) {
   return(SBP_adj)
 }
 
-#' @title Adjust diastolic blood pressure
+#' @title Adjusted diastolic blood pressure
 #'
 #' @description This function adjusts diastolic blood pressure based on the respondent's diastolic average blood pressure across
 #' six measurements. The adjustment is made using specific correction factors. The adjusted diastolic blood pressure
@@ -68,7 +68,7 @@ adjust_DBP <- function(BPMDPBPD) {
   return(DBP_adj)
 }
 
-#' @title Determine Hypertension Status
+#' @title Hypertension derived variable
 #'
 #' @description
 #' This function determines the hypertension status of a respondent based on their systolic and diastolic blood pressure measurements and medication usage.
@@ -177,10 +177,10 @@ determine_hypertension <- function(BPMDPBPS, BPMDPBPD, ANYMED2, CCC_32 = 2, CARD
   return(highBP14090)
 }
 
-#' @title Determine Adjusted Hypertension Status
+#' @title Hypertension derived variable with adjusted blood pressures
 #'
 #' @description
-#' This function determines the adjusted hypertension status of a respondent based on their adjusted systolic and diastolic blood pressure measurements and medication usage.
+#' This function determines the hypertension status of a respondent based on their adjusted systolic and diastolic blood pressure measurements and medication usage.
 #'
 #' @param SBP_adj An integer representing the adjusted systolic blood pressure measurement of the respondent.
 #' @param DBP_adj An integer representing the adjusted diastolic blood pressure measurement of the respondent.
@@ -286,7 +286,7 @@ determine_adjusted_hypertension <- function(SBP_adj, DBP_adj, ANYMED2, CCC_32 =
   return(highBP14090_adj)
 }
 
-#' @title Determine Controlled Hypertension Status
+#' @title Controlled hypertension derived variable
 #'
 #' @description
 #' This function determines the controlled hypertension status of a respondent based on their systolic and diastolic blood pressure measurements and medication usage.
@@ -388,10 +388,10 @@ determine_controlled_hypertension <- function(BPMDPBPS, BPMDPBPD, ANYMED2, CCC_3
   return(Control14090)
 }
 
-#' @title Determine Controlled Adjusted Hypertension Status
+#' @title Controlled hypertension derived variable with adjusted blood pressures
 #'
 #' @description
-#' This function determines the controlled adjusted hypertension status of a respondent based on their adjusted systolic and diastolic blood pressure measurements and medication usage.
+#' This function determines the controlled hypertension status of a respondent based on their adjusted systolic and diastolic blood pressure measurements and medication usage.
 #'
 #' @param SBP_adj An integer representing the adjusted systolic blood pressure measurement of the respondent.
 #' @param DBP_adj An integer representing the adjusted diastolic blood pressure measurement of the respondent.

R/cholesterol-and-obesity.R

@@ -1,4 +1,4 @@
-#' @title Calculate Non-HDL Cholesterol Level
+#' @title Non-HDL cholesterol level
 #'
 #' @description This function calculates a respondent's non-HDL cholesterol level by subtracting their HDL cholesterol level
 #' from their total cholesterol level. It first checks whether the input values `LAB_CHOL` (total cholesterol)
@@ -36,9 +36,9 @@ calculate_nonHDL <- function(LAB_CHOL, LAB_HDL) {
   return(nonHDL)
 }
 
-#' Non-HDL Cholesterol Categorization
+#' @title Categorical non-HDL cholesterol level
 #'
-#' This function categorizes individuals' non-HDL cholesterol levels based on a threshold value.
+#' @description This function categorizes individuals' non-HDL cholesterol levels based on a threshold value.
 #'
 #' @param nonHDL Numeric value representing an individual's non-HDL cholesterol level.
 #'
@@ -72,7 +72,7 @@ categorize_nonHDL <- function(nonHDL) {
   return(nonhdltodd)
 }
 
-#' @title Calculate Waist-to-Height Ratio (WHR)
+#' @title Waist-to-height ratio (WHR)
 #'
 #' @description This function calculates the Waist-to-Height Ratio (WHR) by dividing the waist circumference by the height of the respondent.
 #'

R/diabetes.R

@@ -1,6 +1,6 @@
-#' @title Determine Inclusive Diabetes Status
+#' @title Diabetes derived variable
 #'
-#' @description This function evaluates inclusive diabetes status based on three factors: `diab_m`, `CCC_51`, and `diab_drug2`.
+#' @description This function evaluates diabetes status based on three factors: `diab_m`, `CCC_51`, and `diab_drug2`.
 #'
 #' @param diab_m An integer indicating whether the respondent has diabetes based on HbA1c level. 1 for "Yes", 2 for "No".
 #' @param CCC_51 An integer indicating whether the respondent self-reported diabetes. 1 for "Yes", 2 for "No".

R/diet.R

@@ -1,4 +1,4 @@
-#' @title Calculate daily fruit and vegetable consumption in a year for respondent in CHMS cycles 1-2.
+#' @title Daily fruit and vegetable consumption in a year - cycles 1-2
 #'
 #' @description This function calculates the daily fruit and vegetable consumption in a year for respondent in the Canadian Health Measures
 #' Survey (CHMS) cycles 1-2. It takes seven parameters, each representing the number of times per year a specific fruit or vegetable item
@@ -53,7 +53,7 @@ find_totalFV_cycles1and2 <- function(WSDD14Y, GFVD17Y, GFVD18Y, GFVD19Y, GFVD20Y
   return(totalFV)
 }
 
-#' @title Calculate daily fruit and vegetable consumption in a year for respondents in CHMS cycles 3-6.
+#' @title Daily fruit and vegetable consumption in a year - cycles 3-6
 #'
 #' @description This function calculates the daily fruit and vegetable consumption in a year for respondents in the Canadian Health Measures
 #' Survey (CHMS) cycles 3-6. It takes eleven parameters, each representing the number of times per year a specific fruit or
@@ -115,7 +115,7 @@ find_totalFV_cycles3to6 <- function(WSDD34Y, WSDD35Y, GFVD17AY, GFVD17BY, GFVD17
   return(totalFV)
 }
 
-#' @title Diet Categorization
+#' @title Categorical diet indicator
 #'
 #' @description This function categorizes individuals' diet quality based on their total fruit and vegetable consumption.
 #'

R/exercise.R

@@ -1,4 +1,4 @@
-#' @title Calculate the average minutes of exercise per day for week-long accelerometer data.
+#' @title Average minutes of exercise per day for week-long accelerometer data
 #'
 #' @description This function calculates the average minutes of exercise per day across a week of accelerometer data. It takes seven
 #' parameters, each representing the minutes of exercise on a specific day (Day 1 to Day 7) of accelerometer measurement.
@@ -43,7 +43,7 @@ find_week_accelerometer_average <- function(AMMDMVA1, AMMDMVA2, AMMDMVA3, AMMDMV
   return(MVPA_min)
 }
 
-#' @title Convert minutes per day to minutes per week.
+#' @title Minutes per week from minutes per day
 #'
 #' @description This function takes the average minutes of exercise per day across a week of accelerometer use as an input (`MVPA_min`) and
 #' calculates the equivalent minutes of exercise per one week of accelerometer use. The result is returned as a numeric value.
@@ -70,9 +70,9 @@ minperday_to_minperweek <- function(MVPA_min) {
   return(minperweek)
 }
 
-#' Categorize Weekly Physical Activity
+#' @title Categorical weekly physical activity indicator
 #'
-#' This function categorizes individuals' weekly physical activity levels based on a threshold value.
+#' @description This function categorizes individuals' weekly physical activity levels based on a threshold value.
 #'
 #' @param minperweek Numeric value representing an individual's minutes of moderate-to-vigorous
 #'   physical activity (MVPA) per week.

R/family-history.R

@@ -1,4 +1,4 @@
-#' @title Determine cardiovascular disease (CVD) personal history
+#' @title Cardiovascular disease (CVD) personal history
 #'
 #' @description This function determines a respondent's cardiovascular disease (CVD) personal history based on the presence or absence
 #' of specific conditions related to heart disease, heart attack, and stroke.
@@ -35,7 +35,7 @@ determine_CVD_Personal_History <- function(CCC_61, CCC_63, CCC_81) {
   return(cardiov)
 }
 
-#' @title Determine Cardiovascular Disease (CVD) Family History
+#' @title Cardiovascular Disease (CVD) family history
 #'
 #' @description This function evaluates a respondent's family history of cardiovascular disease (CVD), based on data about diagnoses of heart disease and stroke in immediate family members and the ages at which these diagnoses occurred. It identifies premature CVD if any diagnosis occurred before age 60.
 #'

R/income.R

@@ -1,4 +1,4 @@
-#' @title Calculate adjusted total household income based on weighted household size.
+#' @title Adjusted total household income
 #'
 #' @description This function calculates the adjusted total household income based on the respondent's income amount
 #'              and actual household size, taking into account the weighted household size.
@@ -58,9 +58,9 @@ calculate_Hhld_Income <- function(THI_01, DHHDHSZ) {
   return(adj_hh_inc)
 }
 
-#' Categorize Household Income
+#' @title Categorical adjusted household income
 #'
-#' This function categorizes individuals' household income based on specified income ranges.
+#' @description This function categorizes individuals' adjusted household income based on specified income ranges.
 #'
 #' @param adj_hh_inc Numeric value representing the adjusted household income.
 #'
@@ -103,9 +103,9 @@ categorize_income <- function(adj_hh_inc) {
   return(incq)
 }
 
-#' Check If in Lowest Income Quintile
+#' @title Lowest income quintile indicator
 #'
-#' This function checks if an individual's income category corresponds to the lowest income quintile.
+#' @description This function checks if an individual's income category corresponds to the lowest income quintile.
 #'
 #' @param incq Categorical value indicating the income category as defined by the categorize_income function.
 #'

R/kidney.R

@@ -1,4 +1,4 @@
-#' @title Calculate the estimated glomerular filtration rate (GFR) based on serum creatine
+#' @title Estimated glomerular filtration rate (GFR)
 #'
 #' @description This function calculates the estimated glomerular filtration rate (GFR) according to Finlay's formula,
 #'              where serum creatine is in mg/dL. The calculation takes into account the respondent's ethnicity, sex, and age.
@@ -65,9 +65,9 @@ calculate_GFR <- function(LAB_BCRE, PGDCGT, CLC_SEX, CLC_AGE) {
   return(GFR)
 }
 
-#' Categorize Glomerular Filtration Rate (GFR) to Chronic Kidney Disease (CKD) Stage
+#' @title Chronic kidney disease (CKD) derived variable
 #'
-#' This function categorizes individuals' glomerular filtration rate (GFR) into stages of Chronic Kidney Disease (CKD).
+#' @description This function categorizes individuals' glomerular filtration rate (GFR) into stages of Chronic Kidney Disease (CKD).
 #'
 #' @param GFR Numeric value representing the glomerular filtration rate.
 #'