version 0.0.3

DESCRIPTION

@@ -2,7 +2,7 @@ Package: idarps
 Type: Package
 Title: Datasets and Functions for the Class "Modelling and Data
         Analysis for Pharmaceutical Sciences"
-Version: 0.0.2
+Version: 0.0.3
 Authors@R: c(
     person("Lionel", "Voirol", email = "lionelvoirol@hotmail.com", role = c("aut", "cre")),
     person("Stéphane", "Guerrier", role = "aut"),
@@ -17,12 +17,12 @@ Encoding: UTF-8
 LazyData: true
 RoxygenNote: 7.2.3
 NeedsCompilation: no
-Packaged: 2023-03-13 14:30:55 UTC; lionel
+Packaged: 2023-04-21 14:01:33 UTC; lionel
 Author: Lionel Voirol [aut, cre],
   Stéphane Guerrier [aut],
   Yuming Zhang [aut],
   Luca Insolia [aut]
 Maintainer: Lionel Voirol <lionelvoirol@hotmail.com>
 Depends: R (>= 3.5.0)
 Repository: CRAN
-Date/Publication: 2023-03-13 15:30:02 UTC
+Date/Publication: 2023-04-21 17:12:32 UTC

MD5

@@ -1,12 +1,14 @@
-ec3c0aecec8b6cc03559f33f6a8fdec5 *DESCRIPTION
+849b8b3a9edc71c8cc777c4c63298ed7 *DESCRIPTION
 dda42d6675c84f94913d4982a79f2549 *NAMESPACE
-c4db4737c0ff886b232b023ea815d268 *NEWS.md
+ed504a946309bfbcb9b44d377f733289 *NEWS.md
 585a0a06d9bde9f7e4debedcddfef402 *R/boxplot_w_points.R
 c268d52e49c1e5e611ac15230ec08190 *R/compare_to_normal.R
 c07f7a24429c20de87c159b35d2d0421 *R/compute_transparent_color.R
-017e7855e80e382387a5a18fdd844ff5 *R/document_data.R
-a1818c5e22bd0c17a0354cb12dc71c14 *README.md
+1afbdd047dcf808d5bea663fa59b7fa6 *R/document_data.R
+5a0dd8a750e5a51935168ec6dfa786bb *README.md
+60e2ecfe1b9d37e83bce76154fd54e27 *data/BreastCancer.RData
 628c0fc954e394fdcf8cd3c19e145087 *data/HP13Cbicarbonate.RData
+d8127f0a4c7ec786af26f0ffb1139c98 *data/PeruvianBP.RData
 9613c418dd86799f3a9dc3b17be464b7 *data/bronchitis.RData
 63635bb1e2c81a47d4b28fef1371eb87 *data/codex.RData
 c193cf15bf06ecabad616486721bc5fb *data/cortisol.RData
@@ -18,17 +20,19 @@ c193cf15bf06ecabad616486721bc5fb *data/cortisol.RData
 fb5284c68f52fa79002d73607e582cac *data/reading.RData
 21b99860c1ecb9e8d457994f348b72be *data/snoring.RData
 771fc60b3bc47f0d17a3e7d200c1c559 *data/students.RData
-58cfa8b80daec5b82daee673387a63e4 *man/HP13Cbicarbonate.Rd
+fedc93a95878b303c1ada24d5a533d21 *man/BreastCancer.Rd
+953d3f2d9aba8865ac91600c6f60b1af *man/HP13Cbicarbonate.Rd
+d51bc610d5dec8604b50e4c08cd2a837 *man/PeruvianBP.Rd
 ea2d13b61201be383c7ef2a71a242ac8 *man/boxplot_w_points.Rd
-bf51ae78cf12c24c129b3adcfc4dc48c *man/bronchitis.Rd
-0ec3e2c07914a1a1697982f9423947c9 *man/codex.Rd
-fa23c3f1a88116e8e86e6d02da1c4e70 *man/cortisol.Rd
-6ca4ed7c7677714fe58c3b8c0848cada *man/covid.Rd
-2d9c147f28fbab6be7252712d0b8f0bc *man/data_covid_switzerland_spatial.Rd
-36bc076f00773d2b0dcf30436f849c25 *man/diet.Rd
-de5bb8fbc14dc612b06c32498f0953c6 *man/fev.Rd
+52f526949e7a332d993edd9e6e9414aa *man/bronchitis.Rd
+a053c43a10862a29d00479b451ceb2f1 *man/codex.Rd
+1a7304c02d1560130f278c30855c8d74 *man/cortisol.Rd
+91f7e167aadf93e13ba431f113ef070a *man/covid.Rd
+1a738a041468cd6b72106e40cb560d62 *man/data_covid_switzerland_spatial.Rd
+1d1b06e31e2d6d4c3053ebf03bc32ca2 *man/diet.Rd
+a862f0020258741bfc011830eb0efbe0 *man/fev.Rd
 3f9edc939df701506bba96e75877b39d *man/hist_compare_to_normal.Rd
-6a52a394b7f03f30c13b4f4f7653e950 *man/pharmacy.Rd
-2a7344513225020abe4816bc02a022b1 *man/reading.Rd
-f8474228cd905fd440f67735a23436e3 *man/snoring.Rd
-31f6f82f498d762973c2c61f595d50cd *man/students.Rd
+442c7c8bb1118940b7645eacc63d0954 *man/pharmacy.Rd
+1c3a111d2c8d224c7333a60256b53be1 *man/reading.Rd
+5857d1ac9746f6f21320e5dae6877c18 *man/snoring.Rd
+7deb5d0935f8be9e2f437a92f74dbc72 *man/students.Rd

NEWS.md

@@ -1,3 +1,7 @@
+# idarps version 0.0.3
+
+Added datasets BreastCancer and PeruvianBP and their description.
+
 # idarps version 0.0.2
 
 Corrected typos in datasets reading and codex.

R/document_data.R

@@ -1,5 +1,4 @@
 #'
-#'
 #' Intensive care admission of COVID-19 patients in Belgium
 #'
 #' @description Data from Parisi, et al., (2021) which studies the applicability of predictive models for intensive care
@@ -8,11 +7,11 @@
 #'
 #' @format A data frame with 64 rows and 5 variables:
 #' \describe{
-#'   \item{icu}{admission to an Intensive Care Unit, binary (0 for no, 1 for yes)}
-#'   \item{sex}{sex, binary (men, women)}
-#'   \item{age}{age in year}
+#'   \item{icu}{admission to an Intensive Care Unit (0 for no, 1 for yes)}
+#'   \item{sex}{sex (men, women)}
+#'   \item{age}{age in years}
 #'   \item{ldh}{lactate dehydrogenase in U/L}
-#'   \item{spo2}{oxygen saturation in (percentage)}
+#'   \item{spo2}{oxygen saturation in percentage}
 #' }
 #'
 #' @references Parisi, Nicolas, et al. "Non applicability of validated predictive models for intensive care admission and death of COVID-19 patients in a secondary care hospital in Belgium.", Journal of Emergency and Critical Care Medicine, (2021).
@@ -23,15 +22,14 @@
 #'
 #' Customer attendance of a pharmacy in Geneva
 #'
-#' A dataset containing the number of clients in a Pharmacy for each hour over two years
+#' @description This dataset contains the number of clients in a pharmacy for each hour over two years.
 #'
 #' @format A data frame with 17520 rows and 4 variables:
 #' \describe{
 #'   \item{date}{the date}
-#'   \item{hours}{the hour of the day (1-24)}
+#'   \item{hours}{the hour of the day}
 #'   \item{weekday}{the week day}
-#'   \item{attendance}{The recorded number of clients}
-#'
+#'   \item{attendance}{the recorded number of clients}
 #' }
 "pharmacy"
 #'
@@ -41,19 +39,19 @@
 #'
 #' Biomarkers in pigs fed with various diets
 #'
-#' A dataset containing measured biomarkers in pigs fed with various diets
+#' @description This dataset contains measured biomarkers in pigs fed with various diets.
 #'
 #' @format A data frame with 61 rows and 9 variables:
 #' \describe{
 #'   \item{id}{the id of the pig}
-#'   \item{group}{the diet fed to the pig (chipped diet or non chipped diet)}
+#'   \item{group}{the diet fed to the pig (chipped diet or non-chipped diet)}
 #'   \item{gender}{the gender of the pig}
 #'   \item{cortisol}{urine costisol in pg/ml}
 #'   \item{acth}{serum acth in pg/ml}
 #'   \item{crh}{serum crh in pg/ml}
 #'   \item{testosterone}{testosterone in ng/ml}
 #'   \item{lh}{LH in ng/ml}
-#'   \item{caloric}{Daily caloric intake in kcal}
+#'   \item{caloric}{daily caloric intake in kcal}
 #'   }
 "cortisol"
 #'
@@ -63,20 +61,20 @@
 #'
 #' codex
 #'
-#' Data concerning an observational study conducted at Geneva University Hospitals to assess the impact of weight on the pharmacokinetics of dexamethasone in normal-weight versus obese patients hospitalized for COVID-19.
+#' @description This dataset is based on an observational study conducted at Geneva University Hospitals to assess the impact of weight on the pharmacokinetics of dexamethasone in normal-weight versus obese patients hospitalized for COVID-19.
 #'
 #' @format
 #' \describe{
-#'   \item{id}{id}
-#'   \item{gender}{gender. 0 corresponds the men and 1 to women}
-#'   \item{age}{age}
-#'   \item{bmi}{bmi}
-#'   \item{weight}{weight in (kg)}
+#'   \item{id}{ID of the patient}
+#'   \item{gender}{Gender (0 for men and 1 for women)}
+#'   \item{age}{Age}
+#'   \item{bmi}{Body mass index}
+#'   \item{weight}{Weight in kg}
 #'   \item{number_doses}{Number of doses of the dexamethasone (DEX) drug}
-#'   \item{tmax}{the time it takes for the drug to reach the maximum concentration (i.e. Cmax) after its administration in hours (h)}
-#'   \item{cmax}{the maximum concentration that  achieves in the blood after the drug has been administered (ng/m)}
+#'   \item{tmax}{The time it takes for the drug to reach the maximum concentration (i.e. Cmax) after its administration in hours (h)}
+#'   \item{cmax}{The maximum concentration that  achieves in the blood after the drug has been administered (ng/m)}
 #'   \item{t1_2}{t1_2 is the time required to decrease the drug concentration within the body by one-half during elimination in hours (h)}
-#'   \item{auc}{the integral (from 0 to 8 hours) of a curve that describes the variation of a drug concentration in the blood as a function of time it takes for a drug to reach the maximum concentration (Cmax) after administration of a drug (ng.h/m)}
+#'   \item{auc}{The integral (from 0 to 8 hours) of a curve that describes the variation of a drug concentration in the blood as a function of time it takes for a drug to reach the maximum concentration (Cmax) after administration of a drug (ng.h/m)}
 #'   \item{length_hospital}{Number of days the patient were hospitalized}
 #'   \item{length_intermed}{Number of days the patient were hospitalized at the intermediate and intensive care unit}
 #'   \item{crp}{crp}
@@ -85,19 +83,19 @@
 #'   \item{comor_v}{Presence of cormobidity type v}
 #'   \item{comor_c}{Presence of cormobidity type c}
 #'   \item{comor_r}{Presence of cormobidity type r}
-#'   \item{obese}{Is the subject obese. Indicator variable based on the BMI > 30}
+#'   \item{obese}{Indicator variable based on whether the subject is obese (i.e. with BMI > 30), 0 for no and 1 for yes.}
 #' }
 "codex"
 #'
 
 
-#' bronchitis
+#' Bronchitis
 #'
-#' Data collected in a study to assess the effects of smoking and pollution on being diagnosed with bronchitis. This dataset is based on 212 subjects
+#' @description Data collected in a study to assess the effects of smoking and pollution on being diagnosed with bronchitis. This dataset is based on 212 subjects.
 #'
 #' @format
 #' \describe{
-#' \item{bron}{Presence of bronchitis}
+#' \item{bron}{Presence of bronchitis (0 for no and 1 for yes)}
 #' \item{cigs}{Average daily number of smoked cigarettes}
 #' \item{poll}{Pollution index}
 #'
@@ -107,41 +105,39 @@
 
 
 #'
-#' diet
-#'
-#' diet
+#' Diet
 #'
 #' @format
 #' \describe{
-#'   \item{id}{id}
-#'   \item{gender}{score}
-#'   \item{age}{age}
-#'   \item{height}{height}
-#'   \item{diet.type}{diet.type}
-#'   \item{initial.weight}{initial.weight}
-#'   \item{final.weight}{final.weight}
+#'   \item{id}{ID}
+#'   \item{gender}{Gender (male or female)}
+#'   \item{age}{Age in years}
+#'   \item{height}{Height in m}
+#'   \item{diet.type}{Type of diet (A, B or C)}
+#'   \item{initial.weight}{Initial weight in kg}
+#'   \item{final.weight}{Final weight in kg}
 #' }
 "diet"
 
-#' Reading dataset
+
+#' Reading
 #'
-#' Study on the effectiveness of directed reading activities for elementary school students (6-12 years old).
+#' @description This dataset is based on the effectiveness of directed reading activities for elementary school students (6-12 years old).
 #'
 #' @format
 #' \describe{
-#'   \item{id}{Student id.}
-#'   \item{score}{Degree of Reading Power (DRP) test score.}
-#'   \item{age}{Age of the students.}
-#'   \item{group}{Binary variable indicating whether a student participated to the directed reading activities (Treatment if the student participated, Control otherwise).}
+#'   \item{id}{Student id}
+#'   \item{score}{Degree of Reading Power (DRP) test score}
+#'   \item{age}{Age of the students}
+#'   \item{group}{Binary variable indicating whether a student participated to the directed reading activities (Treatment if the student participated, Control otherwise)}
 #' }
 "reading"
 
 
 
 #'
-#' students
+#' Students
 #'
-#' students
 #'
 #' @format
 #' \describe{
@@ -155,7 +151,7 @@
 #'
 #' COVID-19 Spatial
 #'
-#' Data from the COVID-19 Data Hub joined with spatial features for Switzerland
+#' @description Data from the COVID-19 Data Hub joined with spatial features for Switzerland.
 #'
 #' @format
 #' \describe{
@@ -186,8 +182,6 @@
 #' Two groups of rats were compared (i.e. fed and overnight-fasted). Dataset from Can et al. 2022.
 #'
 #'
-#' HP13Cbicarbonate
-#'
 #' @format
 #' \describe{
 #'   \item{signal}{HP13C bicarbonate signal intensities normalized to the total sum of metabolites}
@@ -205,20 +199,19 @@
 
 
 
-#' snoring
-#' @description Study on the physical and behavioral characteristics of snorers.
+#' Snoring
+#' @description This dataset is based on a study on the physical and behavioral characteristics of snorers.
 #'
-#' snoring
 #'
 #' @format
 #' \describe{
-#' \item{sex}{gender of the person (0 for males and 1 for females).}
+#' \item{sex}{gender of the person (0 for males and 1 for females)}
 #' \item{age}{age in years}
 #' \item{height}{height in cm}
 #' \item{weight}{weight in kg}
-#' \item{smoke}{smoking behavior (0 for non-smokers and 1 for smokers).}
-#' \item{alcohol}{number of glasses drunk per day (in red wine equivalent).}
-#' \item{snore}{snoring diagnosis (0=not snoring, 1=snoring).}
+#' \item{smoke}{smoking behavior (0 for non-smokers and 1 for smokers)}
+#' \item{alcohol}{number of glasses drunk per day (in red wine equivalent)}
+#' \item{snore}{snoring diagnosis (0 for not snoring, 1 for snoring)}
 #' }
 #'
 "snoring"
@@ -231,25 +224,61 @@
 
 
 
+#' Forced Expiratory Volume
+#' @description This dataset is based on a study conducted in suburban Boston in the late 1970s to investigate the relationship between forced expiratory volume and smoking behavior in 654 youths between the ages of 3 and 19.
+#'
+#'
+#' @format
+#' \describe{
+#' \item{fev}{forced expiratory volume or FEV, which measures the amount of air a person can exhale during a forced breath.}
+#' \item{age}{age in years}
+#' \item{sex}{gender of the person (0 for males and 1 for females)}
+#' \item{height}{height in cm}
+#' \item{smoke}{smoking behavior (0 for non-smokers and 1 for smokers)}
+#' }
+#'
+"fev"
+#'
 
 
 
 
+#' Peruvian Blood Pressure
+#' @description  This dataset consists of variables possibly relating to blood pressures of 39 Peruvians who have moved from rural high-altitude areas to urban lower-altitude areas.
+#'
+#'
+#' @format
+#' \describe{
+#' \item{Age}{Age in years}
+#' \item{Years}{Years in urban area}
+#' \item{Weight}{Weight in kg}
+#' \item{Height}{Height in mm}
+#' \item{Chin}{Chin skinfold}
+#' \item{Forearm}{Forearm skinfold}
+#' \item{Calf}{Calf skinfold}
+#' \item{Pulse}{Resting pulse rate}
+#' \item{Systol}{Systolic blood pressure}
+#' }
+#'
+"PeruvianBP"
+#'
 
 
-#' fev
-#' @description  Study conducted in suburban Boston in the late 1970s to investigate the relationship between forced expiratory volume and smoking behavior in 654 youths between the ages of 3 and 19.
+#' Breast Cancer
+#' @description  This dataset consists of several clinical features observed or measured for 116 participants in a study of breast cancer.
 #'
-#' fev
 #'
 #' @format
 #' \describe{
-#' \item{fev}{forced expiratory volume or FEV, which measures the amount of air a person can exhale during a forced breath.}
-#' \item{age}{age in years}
-#' \item{sex}{gender of the person (0 for males and 1 for females).}
-#' \item{height}{height in cm}
-#' \item{smoke}{smoking behavior (0 for non-smokers and 1 for smokers).}
+#' \item{Age}{Age in years}
+#' \item{BMI}{Body mass index in kg/\eqn{m^2}}
+#' \item{Glucose}{Glucose in mg/dL}
+#' \item{Insulin}{Insulin in \eqn{\mu}U/mL}
+#' \item{HOMA}{Homeostasis model assessment}
+#' \item{Classification}{Presence of breast cancer (0 if no cancer, 1 if with cancer)}
 #' }
 #'
-"fev"
+#' @references Patricio, Miguel, et al. "Using Resistin, glucose, age and BMI to predict the presence of breast cancer", BMC Cancer, (2018).
+#' @source \url{https://bmccancer.biomedcentral.com/articles/10.1186/s12885-017-3877-1}
+"BreastCancer"
 #'

README.md

@@ -1,6 +1,5 @@
 
 
-
 <!-- badges: start -->
 ![example workflow](https://github.com/SMAC-Group/idarps/actions/workflows/R-CMD-check.yaml/badge.svg)
 [![CRAN status](https://www.r-pkg.org/badges/version/idarps)](https://CRAN.R-project.org/package=idarps)
@@ -23,13 +22,14 @@ Package for class "Modelling and Data Analysis for Pharmaceutical Sciences" (`id
 
 The `idarps` package is available on both CRAN and GitHub. The CRAN version is considered stable while the GitHub version is subject to modifications/updates which may lead to installation problems or broken functions. You can install the stable version of the `idarps` package with:
 
-## Installation from GitHub
+## Installation from CRAN
+
 ```R
 install.packages("idarps")
 ``` 
 
+## Installation from GitHub
 
-## Installation from CRAN
 For users who are interested in having the latest developments, the GitHub version is ideal although more dependencies are required to run a stable version of the package.
 
 You can install `idarps` from GitHub with: