Merge pull request #47 from nutriverse:dev

initial tidying up of spellings

DESCRIPTION

@@ -22,7 +22,8 @@ Suggests:
     knitr,
     testthat (>= 3.0.0),
     covr,
-    spelling
+    spelling,
+    tibble
 Encoding: UTF-8
 Language: en-GB
 LazyData: true

R/data.R

@@ -1,35 +1,31 @@
-################################################################################
 #'
-#' Infant and Young Children Indicators Sample Dataset
+#' Infant and young child feeding indicators sample dataset
 #'
-#' This sample demo dataset (`iycfData`) contained 359 observations and 46
-#' variables. The following tables explain the detailed description of each
-#' variable included in the sample dataset. The CARE International Myanmar
-#' Country program provided this demo dataset, and all the Personal
-#' Identifiable Information (PII) were excluded.
+#' This is an example IYCF dataset with 359 observations and 46
+#' variables. The dataset is from CARE International Myanmar country programme.
+#' All personally identifiable information have been excluded.
 #'
 #' @format A data frame with 46 columns and 359 rows.
 #'
-#'
 #' **Variables** | **WHO Question Number** | **Description**
 #' :--- | :--- | :---
-#' *csex* | | child sex
-#' *calc_age_months* | | child age in month
-#' *child_bf* | Q1 | ever breastfed
-#' *child_eibf* | Q2 | first put to the breast - immediately
-#' *child_eibf_hrs* | Q2 | first put to the breast - hours
-#' *child_eibf_days* | Q2 | first put to the breast - days
-#' *bf_2days* | Q3 | given anything other than breast milk, first 2-days of child age
-#' *child_bfyest* | Q4 | breastfed yesterday during the day or at night
-#' *bf_bottle* | Q5 | drink anything from a bottle with a nipple yesterday
-#' *child_water* | Q6A | Plain water
-#' *child_bms* | Q6B | Infant formula
-#' *child_bms_freq* | Q6Bnum | Infant formula - frequency
-#' *child_milk* | Q6C | Milk from animals
-#' *child_milk_freq* | Q6Cnum | Milk from animals - frequency
-#' *child_milk_sweet* | Q6Cswt | Milk from animals - sweet or flavored type milk
-#' *child_mproduct* | Q6D | Yogurt drinks
-#' *child_mproduct_freq* | Q6Dnum | Yogurt drinks - frequency
+#' *csex* | | Sex of child; 1 = male; 0 = female.
+#' *calc_age_months* | | Age of child in months (calculated).
+#' *child_bf* | Q1 | Has child ever been breastfed?; 1 = Yes; 0 = No.
+#' *child_eibf* | Q2 | When was child first put to the breast: 0 = immediately; 1 = hours; 2 = days; 999 = Don't know/no response.
+#' *child_eibf_hrs* | Q2 | If *child_eibf* is 1, number of hours child first put to the breast; integer value.
+#' *child_eibf_days* | Q2 | If *child_eibf* is 2, number of days child first put to the breast; integer value.
+#' *bf_2days* | Q3 | Has child been given anything other than breast milk within the child's first 2 days of age? 1 = Yes; 0 = No.
+#' *child_bfyest* | Q4 | Has child been breastfed yesterday during the day or at night? 1 = Yes; 0 = No.
+#' *bf_bottle* | Q5 | Has child drank anything from a bottle with a nipple yesterday? 1 = Yes; 0 = No.
+#' *child_water* | Q6A | Has child drank *plain water* yesterday? 1 = Yes; 0 = No.
+#' *child_bms* | Q6B | Has child drank *infant formula* yesterday? 1 = Yes; 0 = No.
+#' *child_bms_freq* | Q6Bnum | How many times has child drank *infant formula*? Integer value.
+#' *child_milk* | Q6C | Has child drank *milk from animals* yesterday? 1 = Yes; 0 = No.
+#' *child_milk_freq* | Q6Cnum | How many times has child drank *milk from animals*? Integer value.
+#' *child_milk_sweet* | Q6Cswt | For children who drank *milk from animals*, was milk sweetened or flavoured? 1 = Yes; = No.
+#' *child_mproduct* | Q6D | Has child drank *yogurt drinks* yesterday? 1 = Yes; 0 = No.
+#' *child_mproduct_freq* | Q6Dnum | How many times has child rank *yogurt drinks*? Integer value.
 #' *child_mproduct_sweet* | Q6Dswt | Yogurt drinks - sweet or flavored type yogurt
 #' *child_chocolate* | Q6E | Chocolate-flavored drinks
 #' *child_juice* | Q6F| Fruit juice or fruit-flavored drinks
@@ -60,15 +56,12 @@
 #' *child_oth_food* | Q7R |Any other solid, semi-solid or soft food
 #' *child_food_freq* | Q8 | number of any solid, semi-solid or soft foods yesterday
 #'
-#'
 #' @source CARE Myanmar
 #'
 #' @examples
-#' # explore the first 6 observations from the dataset
-#' head(iycfData)
+#' iycfData
 #'
-#
-################################################################################
+
 "iycfData"
 
 

R/get_ebf.R

@@ -1,26 +1,21 @@
-################################################################################
-#
+#' 
 #' @title Construct exclusive breastfeeding status for under 6 months old child
 #'
 #' @description Identification of individual 0-5 months old children exclusive
 #'    breastfeeding status
 #'
 #' @param age This parameter holds the information about child age in the month
 #'    format.
-#'
 #' @param q4 The binary variable which mentioned that the child was receiving
 #'    breastfeeding in the previous day (yes = "1", no = "0").
-#'
 #' @param liquid_food The binary variable which mentioned that the child was
 #'    receiving any type of liquid foods beside breastfeeding yesterday
 #'    (yes = 1 or no = 0).
-#'
 #' @param solid_food The binary variable which mentioned that the child was
 #'    receiving any type of solid foods yesterday (yes = 1 or no = 0).
 #'
-#' @return binary variables indicate child was exclusively breastfed or not
-#'    during the previous day (ebf = 1 or 0)
-#'
+#' @returns A vector of binary values indicating whether a child was exclusively
+#'   breastfed or not during the previous day (1 = Yes or 0 = No).
 #'
 #' @examples
 #'
@@ -53,10 +48,7 @@
 #'
 #' @author Nicholus Tint Zaw
 #' @export
-#' @rdname get_ebf
 #'
-#'
-#################################################################################
 
 # Exclusive Breastfeeding
 get_ebf <- function(q4, age, liquid_food, solid_food){
@@ -70,9 +62,6 @@ get_ebf <- function(q4, age, liquid_food, solid_food){
     ebf <- ifelse(is.na(q4) | is.na(age) | is.na(liquid_food) |
                     is.na(solid_food), NA, ebf)
 
-    return(ebf)
+    ebf
   }
 }
-
-#################################################################################
-

R/get_foodscore.R

@@ -42,6 +42,8 @@
 #'  vita_fruveg <- round(runif(nrow(df), min = 0, max = 1), 0)
 #'  oth_fruveg <- round(runif(nrow(df), min = 0, max = 1), 0)
 #'
+#################################################################################
+
 #'  # Calculate Food Consumption Score
 #'  food_score <- get_foodscore(breastmilk, grains, pulses, dairy, meat,
 #'                              eggs, vita_fruveg, oth_fruveg)

README.Rmd

@@ -31,14 +31,14 @@ knitr::opts_chunk$set(
 
 The first 1,000 days of life (from pregnancy to a child’s 2nd birthday) are critical for addressing childhood malnutrition, especially stunting. Infant and young child feeding practices (IYCF) largely overlap with this period as they cover breastfeeding and complementary feeding practices for the first two years of a child’s life. They also have a significant impact on childhood health, nutrition outcomes, and child survival. It is, therefore, critical for countries to measure IYCF practices as part of their efforts to monitor their progress toward Sustainable Development Goal 2. It is also important for development agencies to be able to monitor and evaluate their programs aimed at improving infant and young child feeding practices towards improved overall childhood nutrition.
 
-WHO and UNICEF released the first IYCF indicators definition and measurement guidelines in 2008. In 2021, these guidelines were updated along with a revised standard questionnaire to capture the information required to calculate the updated IYCF indicators since the first initial publication. In general, the IYCF indicators can be categorized into three main categories: (1) breastfeeding indicators, (2) complementary indicators, and (3) other indicators, which are focused on bottle-feeding practices and the generation of data visualization plots for the breastfeeding status by age.
+WHO and UNICEF released the first IYCF indicators definition and measurement guidelines in 2008. In 2021, these guidelines were updated along with a revised standard questionnaire to capture the information required to calculate the updated IYCF indicators since the first initial publication. In general, the IYCF indicators can be categorized into three main categories: *(1) breastfeeding indicators*, *(2) complementary indicators*, and *(3) other indicators*.
 
 
-## Why riycf package? 
+## Why the {riycf} package?
 
-Although the initial measurement guidelines were published in 2008 with many humanitarian organizations and country health ministries implementing these indicators, no comprehensive statistical programming package to calculate these indicators is yet available. Therefore, every time the researchers (or humanitarian organizations) are required to collect and analyze, they need a considerable amount of time to re-code all the syntax (depending on which statistical program they are using). That is time-consuming work. 
+Although the initial measurement guidelines were published in 2008 with many humanitarian organisations and country health ministries implementing these indicators, no comprehensive statistical programming package to calculate these indicators is yet available. Therefore, every time the researchers (or humanitarian organisations) are required to collect and analyse, they need a considerable amount of time to recode all the syntax (depending on which statistical program they are using). That is time-consuming work. 
 
-This `{riycf}` package aims to address that technical gap by providing an easy-to-use package of automated functions` to calculate all IYCF indicators provided in the WHO guideline ([the Indicators for assessing infant and young child feeding practices: definitions and measurement methods](https://www.who.int/publications/i/item/9789240018389)). This include comprehensive guidelines for step-by-step usage of each automated function to analyze individual IYCF indicators in R software to make it easier for those less familiar with R software.
+This `{riycf}` package aims to address that technical gap by providing an easy-to-use package of functions to calculate all IYCF indicators provided in the [WHO guidelines](https://www.who.int/publications/i/item/9789240018389). This include comprehensive guidelines for step-by-step usage of each automated function to analyse individual IYCF indicators using R.
 
 
 ## Installation 
@@ -66,7 +66,7 @@ Based on the WHO guideline’s indicator definition, the `{riycf}` package funct
 
 ### (Beneficial in) Data cleaning
 
-Each IYCF package function will perform the data quality check to ensure all the required data (variables) were correctly constructed in the dataset. For example, the minimum meal frequency indicator analysis requires the following variables for data analysis: child age, breastfeeding status, and frequency of child feeding on the previous day. The child age and child meal frequency data should be present in the `numeric - integer` format, and the breastfeeding status should be coded as a binary true/false variable with yes = 1 and no = 0. The riycf package function will ensure that integer variables are actually integers and variables that need to be re-coded into numeric scores are re-coded.
+Each IYCF package function will perform the data quality check to ensure all the required data (variables) were correctly constructed in the dataset. For example, the minimum meal frequency indicator analysis requires the following variables for data analysis: child age, breastfeeding status, and frequency of child feeding on the previous day. The child age and child meal frequency data should be present in the `numeric - integer` format, and the breastfeeding status should be coded as a binary true/false variable with yes = 1 and no = 0. The `{riycf}` package function will ensure that integer variables are actually integers and variables that need to be recoded into numeric scores are recoded accordingly.
 
 ### IYCF indicator generation
 
@@ -75,7 +75,7 @@ The indicator calculation process would continue if there were no issues with th
 
 ## Data collection with computer-assisted personal interviews (CAPI)  
 
-This package also provides the already programmed IYCF Questionnaires (based on WHO sample IYCF questionnaires) in XLS programming format. Detailed guidelines for accessing those forms are provided in the vignette article called "WHO IYCF Questionnaire XLS Forms." The different types of XLS programmed IYCF questionnaires can download on [this Github page](https://github.com/nicholustintzaw/iycf_xls_forms). 
+This package also provides the already programmed IYCF Questionnaires (based on WHO sample IYCF questionnaires) in XLS programming format. Detailed guidelines for accessing those forms are provided in the vignette article called "WHO IYCF Questionnaire XLS Forms." The different types of XLS programmed IYCF questionnaires can download on [this GitHub page](https://github.com/nicholustintzaw/iycf_xls_forms). 
 
 ## Citation
 

README.md

@@ -38,30 +38,26 @@ measurement guidelines in 2008. In 2021, these guidelines were updated
 along with a revised standard questionnaire to capture the information
 required to calculate the updated IYCF indicators since the first
 initial publication. In general, the IYCF indicators can be categorized
-into three main categories: (1) breastfeeding indicators, (2)
-complementary indicators, and (3) other indicators, which are focused on
-bottle-feeding practices and the generation of data visualization plots
-for the breastfeeding status by age.
+into three main categories: *(1) breastfeeding indicators*, *(2)
+complementary indicators*, and *(3) other indicators*.
 
-## Why riycf package?
+## Why the {riycf} package?
 
 Although the initial measurement guidelines were published in 2008 with
-many humanitarian organizations and country health ministries
+many humanitarian organisations and country health ministries
 implementing these indicators, no comprehensive statistical programming
 package to calculate these indicators is yet available. Therefore, every
-time the researchers (or humanitarian organizations) are required to
-collect and analyze, they need a considerable amount of time to re-code
+time the researchers (or humanitarian organisations) are required to
+collect and analyse, they need a considerable amount of time to recode
 all the syntax (depending on which statistical program they are using).
 That is time-consuming work.
 
 This `{riycf}` package aims to address that technical gap by providing
-an easy-to-use package of automated functions\` to calculate all IYCF
-indicators provided in the WHO guideline ([the Indicators for assessing
-infant and young child feeding practices: definitions and measurement
-methods](https://www.who.int/publications/i/item/9789240018389)). This
+an easy-to-use package of functions to calculate all IYCF indicators
+provided in the [WHO
+guidelines](https://www.who.int/publications/i/item/9789240018389). This
 include comprehensive guidelines for step-by-step usage of each
-automated function to analyze individual IYCF indicators in R software
-to make it easier for those less familiar with R software.
+automated function to analyse individual IYCF indicators using R.
 
 ## Installation
 
@@ -99,10 +95,10 @@ requires the following variables for data analysis: child age,
 breastfeeding status, and frequency of child feeding on the previous
 day. The child age and child meal frequency data should be present in
 the `numeric - integer` format, and the breastfeeding status should be
-coded as a binary true/false variable with yes = 1 and no = 0. The riycf
-package function will ensure that integer variables are actually
-integers and variables that need to be re-coded into numeric scores are
-re-coded.
+coded as a binary true/false variable with yes = 1 and no = 0. The
+`{riycf}` package function will ensure that integer variables are
+actually integers and variables that need to be recoded into numeric
+scores are recoded accordingly.
 
 ### IYCF indicator generation
 
@@ -122,7 +118,7 @@ This package also provides the already programmed IYCF Questionnaires
 Detailed guidelines for accessing those forms are provided in the
 vignette article called “WHO IYCF Questionnaire XLS Forms.” The
 different types of XLS programmed IYCF questionnaires can download on
-[this Github page](https://github.com/nicholustintzaw/iycf_xls_forms).
+[this GitHub page](https://github.com/nicholustintzaw/iycf_xls_forms).
 
 ## Citation
 

data-raw/processData.R

@@ -1,22 +1,20 @@
-
 # SAMPLE DATASET for IYCF INDICATORS EXAMPLE
 
-################################################################################
-
-# Breastfeeding Sample Data
+## Breastfeeding Sample Data
 bfData <- read.csv("data-raw/bf_data.csv")
+
 # usethis::use_data(bfData, overwrite = TRUE, compress = "xz")
 
-################################################################################
 
-# Complementary Feeding Sample Data
+## Complementary Feeding Sample Data
 cfData <- read.csv("data-raw/iycf_data.csv")
 # usethis::use_data(cfData, overwrite = TRUE, compress = "xz")
 
-# IYCF Dataset - CARE Myanmar Sample data
+
+## IYCF Dataset - CARE Myanmar Sample data
 iycfData <- rbind(bfData, cfData)
 
-# required additional variable creation - to matched with WHO questionnaires
+## required additional variable creation - to matched with WHO questionnaires
 iycfData$bf_2days <- rbinom(n = nrow(iycfData), size = 1, prob = 0.3)
 iycfData$bf_bottle <- rbinom(n = nrow(iycfData), size = 1, prob = 0.15)
 iycfData$child_milk_sweet <- rbinom(n = nrow(iycfData), size = 1, prob = 0.3)
@@ -58,9 +56,6 @@ final_var <- c('csex', 'calc_age_months', 'child_bf', 'child_eibf',
                'child_fish', 'child_beans', 'child_cheese', 'child_sweets',
                'child_snack', 'child_oth_food', 'child_food_freq')
 
-iycfData <- iycfData[, final_var]
+iycfData <- tibble::as_tibble(iycfData[, final_var])
 
 usethis::use_data(iycfData, overwrite = TRUE, compress = "xz")
-
-
-################################################################################