R/number-conditions.R

In Big-Life-Lab/cchsflow: Transforming and Harmonizing CCHS Variables

#' @title Number of chronic conditions (5 chronic conditions)
#' 
#' @description This function generates a derived variable (number_conditions)
#'  that counts the number of chronic conditions a respondent has. This function
#'  takes 5 CCHS-defined conditions (heart disease, cancer, stroke, bowel
#'  disorder, and arthritis), and well one derived variable (respiratory
#'  condition) to count the number of conditions a respondent has.
#'  
#' @param CCC_121 variable indicating if respondent has heart disease (1 = 
#'  respondent has heart disease, 2 = respondent does not have heart disease)
#' 
#' @param CCC_131 variable indicating if respondent has active cancer (1 =
#'  respondent has active cancer, 2 =  respondent does not have active cancer)
#' 
#' @param CCC_151 variable indicating if respondent suffers from the effects
#'  of a stroke (1 = respondent suffers from stroke effects, 2 = respondent
#'  does not suffer from stroke effects)
#' 
#' @param CCC_171 variable indicating if respondent has a bowel disorder (1 =
#'  respondent has bowel disorder, 2 = respondent does not have a bowel
#'  disorder)
#' 
#' @param resp_condition_der derived variable indicating if respondent has a
#'  respiratory condition (1 = respondent is over the age of 35 and has
#'  a respiratory condition, 2 = respondent is under the age of 35 and has a
#'  respiratory conditions, 3 = respondent does not have a respiratory
#'  condition). See \code{\link{resp_condition_fun1}} for
#'  documentation on how variable was derived.
#'
#' @param CCC_051 variable indicating if respondent has arthritis or
#'  rheumatism (1 = respondent has arthritis or rheumatism, 2 = respondent does
#'  not have arthritis or rheumatism)
#'
#' @details mood disorder (CCC_280) was not asked to respondents in the 2001
#'  CCHS survey cycle. This mean respondents in this cycle will only be able to
#'  have a maximum of 6 chronic conditions as opposed to 7 for respondents in
#'  other cycles. \code{\link{multiple_conditions_fun2}} is used for CCHS cycles
#'  from 2003 to 2014.
#' 
#' @return A categorical variable indicating the number of chronic conditions
#'  a respondent has. Respondents with 5 or more conditions are grouped in the
#'  "5+" category. 
#' 
#' @examples 
#'  # Using rec_with_table() to generate multiple_conditions in a CCHS
#'  # cycle.
#'  
#'  # multiple_conditions_fun1() is specified in variable_details.csv along with
#'  # the CCHS variables and cycles included.
#'  
#'  # To generate multiple_conditions, use rec_with_table() and specify the
#'  # multiple_conditions, along with the variables that are derived from it.
#'  # Since resp_condition_der is also a derived variable, you will have to
#'  # specify the variables that are derived from it. In this example, data
#'  # from the 2001 CCHS will be used, so DHHGAGE_cont, CCC_091, and CCC_91A,
#'  # and CCC_031 will be specified along with resp_condition_der.
#'  
#' library(cchsflow)
#'  conditions_2001 <- suppressWarnings(rec_with_table(cchs2001_p,
#'  c("DHHGAGE_cont", "CCC_091",
#'  "CCC_91A", "CCC_031", "CCC_121","CCC_131","CCC_151", "CCC_171","CCC_280",
#'  "resp_condition_der","CCC_051", "number_conditions")))
#'  
#'  head(conditions_2001)
#'  
#'  # Generating multiple_conditions with user inputted values
#'  # Let's say you are an individual that has heart disease, bowel disorder,
#'  # and arthritis. multiple_conditions_fun1() can be used to count the number
#'  # of chronic conditions you have
#'  
#' library(cchsflow)
#'  num_conditions <- multiple_conditions_fun1(CCC_121 = 1, CCC_131 = 2, 
#'  CCC_151 = 2, CCC_171 = 1, resp_condition_der = 3, CCC_051 = 1) 
#'  
#' print(num_conditions)
#' 
#' @seealso \code{\link{multiple_conditions_fun2}}     
#' @export

multiple_conditions_fun1 <- 
  function(CCC_121, CCC_131, CCC_151, CCC_171, resp_condition_der, CCC_051){
    
    # Convert variables to numeric
    CCC_121 <- as.numeric(CCC_121)
    CCC_131 <- as.numeric(CCC_131)
    CCC_151 <- as.numeric(CCC_151)
    CCC_171 <- as.numeric(CCC_171)
    resp_condition_der <- as.numeric(resp_condition_der)
    CCC_051 <- as.numeric(CCC_051)
    
    # set invalid/NA values to 0
    CCC_121 <- if_else2(CCC_121 %in% (1:2), CCC_121, 0)
    CCC_131 <- if_else2(CCC_131 %in% (1:2), CCC_131, 0)
    CCC_151 <- if_else2(CCC_151 %in% (1:2), CCC_151, 0)
    CCC_171 <- if_else2(CCC_171 %in% (1:2), CCC_171, 0)
    resp_condition_der <- if_else2(resp_condition_der %in% (1:3),
                                   resp_condition_der, 0)
    CCC_051 <- if_else2(CCC_051 %in% (1:2), CCC_051, 0)
    
    # adjust resp_condition to yes = 1, no = 2
    resp_condition_der <- if_else2(resp_condition_der %in% c(1:2), 1, 2)
    
    # Calculate number of conditions based on yes
    conditions <- 
      (CCC_121%%2) + (CCC_131%%2) + (CCC_151%%2) +(CCC_171%%2) +
      (resp_condition_der%%2) + (CCC_051%%2)
    
    if_else2(conditions>= 5, "5+", conditions)
  }

#' @title Number of chronic conditions (6 chronic conditions)
#' 
#' @description This function generates a derived variable (number_conditions)
#'  that counts the number of chronic conditions a respondent has. This function
#'  takes 6 CCHS-defined conditions (heart disease, cancer, stroke, bowel
#'  disorder, mood disorder and arthritis), and well one derived variable
#'  (respiratory condition) to count the number of conditions a respondent has.
#'  
#' @param CCC_121 variable indicating if respondent has heart disease (1 = 
#'  respondent has heart disease, 2 = respondent does not have heart disease)
#' 
#' @param CCC_131 variable indicating if respondent has active cancer (1 =
#'  respondent has active cancer, 2 =  respondent does not have active cancer)
#' 
#' @param CCC_151 variable indicating if respondent suffers from the effects
#'  of a stroke (1 = respondent suffers from stroke effects, 2 = respondent
#'  does not suffer from stroke effects)
#' 
#' @param CCC_171 variable indicating if respondent has a bowel disorder (1 =
#'  respondent has bowel disorder, 2 = respondent does not have a bowel
#'  disorder)
#' 
#' @param CCC_280 variable indicating if respondent has a mood disorder (1 =
#'  respondent has a mood disorder, 2 = respondent does not have a mood
#'  disorder. Note, variable was not asked to respondents in the 2001 CCHS
#'  survey cycle.
#' 
#' @param resp_condition_der derived variable indicating if respondent has a
#'  respiratory condition. (1 = respondent is over the age of 35 and has
#'  a respiratory condition, 2 = respondent is under the age of 35 and has a
#'  respiratory conditions, 3 = respondent does not have a respiratory
#'  condition). See \code{\link{resp_condition_fun1}} for
#'  documentation on how variable was derived.
#'
#' @param CCC_051 variable indicating if respondent has arthritis or
#'  rheumatism (1 = respondent has arthritis or rheumatism, 2 = respondent does
#'  not have arthritis or rheumatism)
#'
#' @details mood disorder (CCC_280) was not asked to respondents in the 2001
#'  CCHS survey cycle. This mean respondents in this cycle will only be able to
#'  have a maximum of 6 chronic conditions as opposed to 7 for respondents in
#'  other cycles. \code{\link{multiple_conditions_fun1}} is used for CCHS cycles
#'  from 2003 to 2014.
#' 
#' @return A categorical variable indicating the number of chronic conditions
#'  a respondent has. Respondents with 5 or more conditions are grouped in the
#'  "5+" category. 
#' 
#' @examples 
#'  # Using rec_with_table() to generate multiple_conditions in a CCHS
#'  # cycle.
#'  
#'  # multiple_conditions_fun2() is specified in variable_details.csv along with
#'  # the CCHS variables and cycles included.
#'  
#'  # To generate multiple_conditions, use rec_with_table() and specify the
#'  # multiple_conditions, along with the variables that are derived from it.
#'  # Since resp_condition_der is also a derived variable, you will have to
#'  # specify the variables that are derived from it. In this example, data
#'  # from the 2010 CCHS will be used, so DHHGAGE_cont, CCC_091, and CCC_031
#'  # will be specified along with resp_condition_der.
#'  
#' library(cchsflow)
#'  conditions_2009_2010 <- suppressWarnings(rec_with_table(cchs2009_2010_p,
#'  c("DHHGAGE_cont", "CCC_091",
#'  "CCC_031", "CCC_121","CCC_131","CCC_151", "CCC_171","CCC_280",
#'  "resp_condition_der","CCC_051", "number_conditions")))
#'  
#'  head(conditions_2009_2010)
#'  
#'  # Generating multiple_conditions with user inputted values
#'  # Let's say you are an individual that has heart disease, bowel disorder,
#'  # and arthritis. multiple_conditions_fun2() can be used to count the number
#'  # of chronic conditions you have
#'  
#' library(cchsflow)
#'  num_conditions <- multiple_conditions_fun2(CCC_121 = 1, CCC_131 = 2, 
#'  CCC_151 = 2, CCC_171 = 1, CCC_280 = 2, resp_condition_der = 3, CCC_051 = 1) 
#' 
#' print(num_conditions)
#' 
#' @seealso \code{\link{multiple_conditions_fun1}} 
#' @export

multiple_conditions_fun2 <- 
  function(CCC_121, CCC_131, CCC_151, CCC_171, CCC_280, resp_condition_der,
           CCC_051){
    
    # Convert variables to numeric
    CCC_121 <- as.numeric(CCC_121)
    CCC_131 <- as.numeric(CCC_131)
    CCC_151 <- as.numeric(CCC_151)
    CCC_171 <- as.numeric(CCC_171)
    CCC_280 <- as.numeric(CCC_280)
    resp_condition_der <- as.numeric(resp_condition_der)
    CCC_051 <- as.numeric(CCC_051)

    # set invalid/NA values to 0
    CCC_121 <- if_else2(CCC_121 %in% (1:2), CCC_121, 0)
    CCC_131 <- if_else2(CCC_131 %in% (1:2), CCC_131, 0)
    CCC_151 <- if_else2(CCC_151 %in% (1:2), CCC_151, 0)
    CCC_171 <- if_else2(CCC_171 %in% (1:2), CCC_171, 0)
    CCC_280 <- if_else2(CCC_280 %in% (1:2), CCC_280, 0)
    resp_condition_der <- if_else2(resp_condition_der %in% (1:3),
                                   resp_condition_der, 0)
    CCC_051 <- if_else2(CCC_051 %in% (1:2), CCC_051, 0)
    
    # adjust resp_condition to yes = 1, no = 2
    resp_condition_der <- if_else2(resp_condition_der %in% c(1:2), 1, 2)
    
    # Calculate number of conditions based on yes
    conditions <- 
      (CCC_121%%2) + (CCC_131%%2) + (CCC_151%%2) +(CCC_171%%2) +
                  (CCC_280%%2) + (resp_condition_der%%2) + (CCC_051%%2)
    
    if_else2(conditions>= 5, "5+", conditions)
  }