R/label_data.R
In awconway/ptds: What the Package Does (One Line, Title Case)
Defines functions
label_data
Documented in
label_data
##' @title Label data
##' @param data dataframe from csv downloaded from redcap
##' @return
##' @author Aaron Conway
##' @export
label_data <- function(data) {
# Setting Units
# Setting Factors(will create new variable for factors)
data$redcap_event_name_factor <- factor(data$redcap_event_name,
levels = c("t3_arm_1",
"t1_arm_2",
"t2_arm_2",
"t3_arm_2",
"screening_arm_3")
)
data$sex_factor <- factor(data$sex, levels = c("1", "2", "3"))
data$procedure_factor <- factor(data$procedure,
levels = c("1", "2", "3", "4", "5",
"6", "7", "8", "9", "10", "11", "12", "13")
)
data$instructions_factor <- factor(data$instructions,
levels = c("1", "2", "3", "4", "5", "6")
)
data$ptds_dry_mouth_factor <- factor(data$ptds_dry_mouth,
levels = c("0", "1", "2")
)
data$ptds_dry_lips_factor <- factor(data$ptds_dry_lips,
levels = c("0", "1", "2")
)
data$ptds_thick_tongue_factor <- factor(data$ptds_thick_tongue,
levels = c("0", "1", "2")
)
data$ptds_thick_saliva_factor <- factor(data$ptds_thick_saliva,
levels = c("0", "1", "2")
)
data$ptds_dry_throat_factor <- factor(data$ptds_dry_throat,
levels = c("0", "1", "2")
)
data$ptds_bad_taste_factor <- factor(data$ptds_bad_taste,
levels = c("0", "1", "2")
)
data$ptds_water_factor <- factor(data$ptds_water,
levels = c("0", "1", "2")
)
data$global_thirst_factor <- factor(data$global_thirst,
levels = c("1", "2", "3", "4", "5", "6")
)
data$thirst_intensity_factor <- factor(data$thirst_intensity,
levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10")
)
data$pain_factor <- factor(data$pain,
levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10")
)
data$o2_therapy_factor <- factor(data$o2_therapy,
levels = c("1", "0")
)
data$screenprocedure_factor <- factor(data$screenprocedure,
levels = c("1", "2")
)
data$screenage_factor <- factor(data$screenage,
levels = c("1", "2")
)
data$screenemergency_factor <- factor(data$screenemergency,
levels = c("1", "2")
)
data$screenenglish_factor <- factor(data$screenenglish,
levels = c("1", "2")
)
data$screensufficient_factor <- factor(data$screensufficient,
levels = c("1", "2")
)
data$screen_eligible_factor <- factor(data$screen_eligible,
levels = c("1", "2")
)
data$screeninvited_factor <- factor(data$screeninvited,
levels = c("1", "2")
)
data$screenconsented_factor <- factor(data$screenconsented,
levels = c("1", "2")
)
levels(data$redcap_event_name_factor) <- c(
"T3 (Arm 1: Validity)",
"T1 (Arm 2: Reliability and responsiveness)",
"T2 (Arm 2: Reliability and responsiveness)",
"T3 (Arm 2: Reliability and responsiveness)",
"Screening (Arm 3: Screening)"
)
levels(data$sex_factor) <- c("Male", "Female", "Prefer not to say")
levels(data$procedure_factor) <- c(
"Angiogram or Percutaneous Coronary Intervention (PCI)",
"Cardiac Implantable Electronic Device (CIED)",
"Electrophysiology Study (EPS)",
"Structural heart intervention",
"Vascular angiography or intervention",
"Biopsy",
"Port-a-cath",
"Gall bladder stone removal",
"Endovascular aneurysm repair (EVAR)",
"Radiofrequency ablation of a tumour (RFA)",
"Fistula repair/de-clotting",
"Vascular embolization (e.g., renal)",
"Other procedure"
)
levels(data$instructions_factor) <- c(
"Extremely easy",
"Very Easy",
"Easy",
"Difficult",
"Very Difficult",
"Extremely difficult"
)
levels(data$ptds_dry_mouth_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_dry_lips_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_thick_tongue_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_thick_saliva_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_dry_throat_factor) <- c(
"Not bothered",
"Slightly bothered", "Very bothered"
)
levels(data$ptds_bad_taste_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_water_factor) <- c(
"Not bothered",
"Slightly bothered", "Very bothered"
)
levels(data$global_thirst_factor) <- c(
"Extremely uncomfortable",
"Very uncomfortable",
"Mildly uncomfortable",
"Comfortable",
"Very comfortable",
"Extremely comfortable"
)
levels(data$thirst_intensity_factor) <- c(
"0", "1", "2", "3", "4",
"5", "6", "7", "8", "9", "10"
)
levels(data$pain_factor) <- c(
"0- No pain",
"1- Very mild",
"2- Discomforting",
"3- Tolerable",
"4- Distressing",
"5- Very distressing",
"6- Intense",
"7- Very intense",
"8- Utterly horrible",
"9- Excrutiating/ unbearable",
"10- Unimaginable/ unspeakable"
)
levels(data$o2_therapy_factor) <- c("Yes", "No")
levels(data$screenprocedure_factor) <- c(
"Cardiac Cath Lab",
"Interventional Radiology"
)
levels(data$screenage_factor) <- c("Yes", "No")
levels(data$screenemergency_factor) <- c("Yes", "No")
levels(data$screenenglish_factor) <- c("Yes", "No")
levels(data$screensufficient_factor) <- c("Yes", "No")
levels(data$screen_eligible_factor) <- c("Yes", "No")
levels(data$screeninvited_factor) <- c("Yes", "No")
levels(data$screenconsented_factor) <- c("Yes", "No")
attr(data$id, "label") <- "Record ID"
attr(data$redcap_event_name, "label") <- "Event Name"
attr(data$date_time, "label") <- "Date/time"
attr(data$age, "label") <- "Age"
attr(data$sex_factor, "label") <- "Sex"
attr(data$procedure_factor, "label") <- "Type of procedure"
attr(data$other_procedure, "label") <- "Specify other type of procedure"
attr(data$food, "label") <- "Last food"
attr(data$fluids, "label") <- "Last clear fluids"
attr(data$instructions_factor, "label") <- "How easy was it for you to understand the instructions you received about fasting before your procedure ?"
attr(data$fasting_description, "label") <- "Can you please briefly describe what instructions you received about when to stop eating and drinking before your procedure?"
attr(data$ptds_dry_mouth_factor, "label") <- "My mouth is dry"
attr(data$ptds_dry_lips_factor, "label") <- "My lips are dry"
attr(data$ptds_thick_tongue_factor, "label") <- "My tongue is thick"
attr(data$ptds_thick_saliva_factor, "label") <- "My saliva is thick"
attr(data$ptds_dry_throat_factor, "label") <- "My throat is dry"
attr(data$ptds_bad_taste_factor, "label") <- "I have a bad taste in my mouth"
attr(data$ptds_water_factor, "label") <- "I want to drink water"
attr(data$global_thirst_factor, "label") <- "Please rate your current level of thirst discomfort"
attr(data$thirst_intensity_factor, "label") <- "Please rate the intensity of your thirst on a scale of 0 to 10, where 0 is no thirst and 10 is the most intense thirst you could imagine."
attr(data$pain_factor, "label") <- "Please rate your pain on a scale of 0-10"
attr(data$o2_therapy_factor, "label") <- "Are you on oxygen therapy? "
attr(data$screendate, "label") <- "Date of screening"
attr(data$screenprocedure, "label") <- "Procedure location"
attr(data$screenage, "label") <- "Under 16 years of age"
attr(data$screenemergency, "label") <- "Undergoing an emergency procedure"
attr(data$screenenglish, "label") <- "Not able to understand or speak English"
attr(data$screensufficient, "label") <- "Insufficient time prior to procedure"
attr(data$screen_eligible, "label") <- "Eligible?"
attr(data$screeninvited, "label") <- "Invitation to participate provided?"
attr(data$screenconsented, "label") <- "Provided consent?"
attr(data$studyid, "label") <- "Study ID"
return(data)
}
awconway/ptds documentation built on Oct. 20, 2020, 11:05 p.m.
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Defines functions label_data
Documented in label_data
##' @title Label data
##' @param data dataframe from csv downloaded from redcap
##' @return
##' @author Aaron Conway
##' @export
label_data <- function(data) {
# Setting Units
# Setting Factors(will create new variable for factors)
data$redcap_event_name_factor <- factor(data$redcap_event_name,
levels = c("t3_arm_1",
"t1_arm_2",
"t2_arm_2",
"t3_arm_2",
"screening_arm_3")
)
data$sex_factor <- factor(data$sex, levels = c("1", "2", "3"))
data$procedure_factor <- factor(data$procedure,
levels = c("1", "2", "3", "4", "5",
"6", "7", "8", "9", "10", "11", "12", "13")
)
data$instructions_factor <- factor(data$instructions,
levels = c("1", "2", "3", "4", "5", "6")
)
data$ptds_dry_mouth_factor <- factor(data$ptds_dry_mouth,
levels = c("0", "1", "2")
)
data$ptds_dry_lips_factor <- factor(data$ptds_dry_lips,
levels = c("0", "1", "2")
)
data$ptds_thick_tongue_factor <- factor(data$ptds_thick_tongue,
levels = c("0", "1", "2")
)
data$ptds_thick_saliva_factor <- factor(data$ptds_thick_saliva,
levels = c("0", "1", "2")
)
data$ptds_dry_throat_factor <- factor(data$ptds_dry_throat,
levels = c("0", "1", "2")
)
data$ptds_bad_taste_factor <- factor(data$ptds_bad_taste,
levels = c("0", "1", "2")
)
data$ptds_water_factor <- factor(data$ptds_water,
levels = c("0", "1", "2")
)
data$global_thirst_factor <- factor(data$global_thirst,
levels = c("1", "2", "3", "4", "5", "6")
)
data$thirst_intensity_factor <- factor(data$thirst_intensity,
levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10")
)
data$pain_factor <- factor(data$pain,
levels = c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10")
)
data$o2_therapy_factor <- factor(data$o2_therapy,
levels = c("1", "0")
)
data$screenprocedure_factor <- factor(data$screenprocedure,
levels = c("1", "2")
)
data$screenage_factor <- factor(data$screenage,
levels = c("1", "2")
)
data$screenemergency_factor <- factor(data$screenemergency,
levels = c("1", "2")
)
data$screenenglish_factor <- factor(data$screenenglish,
levels = c("1", "2")
)
data$screensufficient_factor <- factor(data$screensufficient,
levels = c("1", "2")
)
data$screen_eligible_factor <- factor(data$screen_eligible,
levels = c("1", "2")
)
data$screeninvited_factor <- factor(data$screeninvited,
levels = c("1", "2")
)
data$screenconsented_factor <- factor(data$screenconsented,
levels = c("1", "2")
)
levels(data$redcap_event_name_factor) <- c(
"T3 (Arm 1: Validity)",
"T1 (Arm 2: Reliability and responsiveness)",
"T2 (Arm 2: Reliability and responsiveness)",
"T3 (Arm 2: Reliability and responsiveness)",
"Screening (Arm 3: Screening)"
)
levels(data$sex_factor) <- c("Male", "Female", "Prefer not to say")
levels(data$procedure_factor) <- c(
"Angiogram or Percutaneous Coronary Intervention (PCI)",
"Cardiac Implantable Electronic Device (CIED)",
"Electrophysiology Study (EPS)",
"Structural heart intervention",
"Vascular angiography or intervention",
"Biopsy",
"Port-a-cath",
"Gall bladder stone removal",
"Endovascular aneurysm repair (EVAR)",
"Radiofrequency ablation of a tumour (RFA)",
"Fistula repair/de-clotting",
"Vascular embolization (e.g., renal)",
"Other procedure"
)
levels(data$instructions_factor) <- c(
"Extremely easy",
"Very Easy",
"Easy",
"Difficult",
"Very Difficult",
"Extremely difficult"
)
levels(data$ptds_dry_mouth_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_dry_lips_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_thick_tongue_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_thick_saliva_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_dry_throat_factor) <- c(
"Not bothered",
"Slightly bothered", "Very bothered"
)
levels(data$ptds_bad_taste_factor) <- c(
"Not bothered",
"Slightly bothered",
"Very bothered"
)
levels(data$ptds_water_factor) <- c(
"Not bothered",
"Slightly bothered", "Very bothered"
)
levels(data$global_thirst_factor) <- c(
"Extremely uncomfortable",
"Very uncomfortable",
"Mildly uncomfortable",
"Comfortable",
"Very comfortable",
"Extremely comfortable"
)
levels(data$thirst_intensity_factor) <- c(
"0", "1", "2", "3", "4",
"5", "6", "7", "8", "9", "10"
)
levels(data$pain_factor) <- c(
"0- No pain",
"1- Very mild",
"2- Discomforting",
"3- Tolerable",
"4- Distressing",
"5- Very distressing",
"6- Intense",
"7- Very intense",
"8- Utterly horrible",
"9- Excrutiating/ unbearable",
"10- Unimaginable/ unspeakable"
)
levels(data$o2_therapy_factor) <- c("Yes", "No")
levels(data$screenprocedure_factor) <- c(
"Cardiac Cath Lab",
"Interventional Radiology"
)
levels(data$screenage_factor) <- c("Yes", "No")
levels(data$screenemergency_factor) <- c("Yes", "No")
levels(data$screenenglish_factor) <- c("Yes", "No")
levels(data$screensufficient_factor) <- c("Yes", "No")
levels(data$screen_eligible_factor) <- c("Yes", "No")
levels(data$screeninvited_factor) <- c("Yes", "No")
levels(data$screenconsented_factor) <- c("Yes", "No")
attr(data$id, "label") <- "Record ID"
attr(data$redcap_event_name, "label") <- "Event Name"
attr(data$date_time, "label") <- "Date/time"
attr(data$age, "label") <- "Age"
attr(data$sex_factor, "label") <- "Sex"
attr(data$procedure_factor, "label") <- "Type of procedure"
attr(data$other_procedure, "label") <- "Specify other type of procedure"
attr(data$food, "label") <- "Last food"
attr(data$fluids, "label") <- "Last clear fluids"
attr(data$instructions_factor, "label") <- "How easy was it for you to understand the instructions you received about fasting before your procedure ?"
attr(data$fasting_description, "label") <- "Can you please briefly describe what instructions you received about when to stop eating and drinking before your procedure?"
attr(data$ptds_dry_mouth_factor, "label") <- "My mouth is dry"
attr(data$ptds_dry_lips_factor, "label") <- "My lips are dry"
attr(data$ptds_thick_tongue_factor, "label") <- "My tongue is thick"
attr(data$ptds_thick_saliva_factor, "label") <- "My saliva is thick"
attr(data$ptds_dry_throat_factor, "label") <- "My throat is dry"
attr(data$ptds_bad_taste_factor, "label") <- "I have a bad taste in my mouth"
attr(data$ptds_water_factor, "label") <- "I want to drink water"
attr(data$global_thirst_factor, "label") <- "Please rate your current level of thirst discomfort"
attr(data$thirst_intensity_factor, "label") <- "Please rate the intensity of your thirst on a scale of 0 to 10, where 0 is no thirst and 10 is the most intense thirst you could imagine."
attr(data$pain_factor, "label") <- "Please rate your pain on a scale of 0-10"
attr(data$o2_therapy_factor, "label") <- "Are you on oxygen therapy? "
attr(data$screendate, "label") <- "Date of screening"
attr(data$screenprocedure, "label") <- "Procedure location"
attr(data$screenage, "label") <- "Under 16 years of age"
attr(data$screenemergency, "label") <- "Undergoing an emergency procedure"
attr(data$screenenglish, "label") <- "Not able to understand or speak English"
attr(data$screensufficient, "label") <- "Insufficient time prior to procedure"
attr(data$screen_eligible, "label") <- "Eligible?"
attr(data$screeninvited, "label") <- "Invitation to participate provided?"
attr(data$screenconsented, "label") <- "Provided consent?"
attr(data$studyid, "label") <- "Study ID"
return(data)
}
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