Multiple if/else if statements using a previously created vector.

[030thill]

I'm trying to create a function that assigns a new value to previously created values for a formula I am trying to create. The vector I am using is a z-score and then I am trying to assign "points" to each z-score to add to the rest of my formula.

I have struggled first with pulling in a previous vector to use in the function as the only argument, and am now continuously getting errors due to the list of if & else if statements I have created. Any help on how to perfect this, not get errors, and have the correct script would be appreciated!!

** note: I have tried else if, else, and ifelse statements all for the list and I still get errors.**

#this is the z-score calculation for wellness#
wellness_z <- ((wellness_sum- alltime_wellness_sum)/ sd_wellness)

wellness_score <- function(wellness_z)
if (wellness_z==0 )
return(1)
if (wellness_z>=0.01 && wellness_z<=0.49)
return(2)
if (wellness_z>=0.50 && wellness_z<=0.99)
return(3)
if (wellness_z>=1.00 && wellness_z<=1.49)
return(4)
if (wellness_z>=1.50 && wellness_z<=1.99)
return(5)
if (wellness_z>=2.00 && wellness_z<=2.49)
return(6)
if (wellness_z>=2.50 && wellness_z<=2.99)
return(7)
if (wellness_z<=-0.01 && wellness_z>=-0.49)
return(-2)
if (wellness_z<=-0.50 && wellness_z>=-0.99)
return(-3)
if (wellness_z<=-1.00 && wellness_z>=-1.49)
return(-4)
if (wellness_z<=-1.50 && wellness_z>=-1.99)
return(-5)
if (wellness_z<=-2.00 && wellness_z>=-2.49)
return(-6)
if (wellness_z<=-2.50 && wellness_z>=-2.99)
return(-7)

[joels]

One option to make this less painful is to use the cut function. For example:

# Fake data
set.seed(2)
y = c(0, runif(50, 0, 3))

breaks = c(-Inf, 0, 0.05, 0.25, 0.5, 1, 1.5, 2.5, Inf)
labels = c(1:4,-3:(-6))

# Returns default category labels as factors
cut(y, breaks=breaks, include.lowest=TRUE)

# Returns desired labels, but as factors
cut(y, breaks=breaks, labels=labels, include.lowest=TRUE)

# Convert factor labels to numeric
y_score = as.numeric(as.character(cut(y, breaks=breaks, labels=labels, include.lowest=TRUE)))

y_score
 [1]  1 -3 -5 -5 -3 -6 -6  4 -6 -4 -5 -5 -3 -5 -3 -4 -6 -6 -3
[20] -4  3 -5 -4 -6  4 -4 -4  4 -4 -6  4  2  4 -5 -6 -5 -5 -6
[39] -3 -5  4 -6 -3  4  4 -6 -5 -6 -4 -5 -5

For your actual use case, you'll need to create the vectors of breaks and labels based on how you actually want to recode the values. Also, the cut function allows you to decide whether you want each interval closed on the left or the right. See the help (?cut) for details. The cut function returns a vector of factor class. as.numeric(as.character(... converts the labels back to numeric so that you can use them in further calculations.

To turn this into a function:

wellness_z = function(x) {
  
  breaks = c(0, 0.01, 0.05, 0.1, 0.5, 1, 1.5, 2.5, Inf)
  labels = c(1:4,-3:(-6))
  
  as.numeric(as.character(cut(x, breaks=breaks, labels=labels, include.lowest=TRUE)))
  
}

wellness_z(y)

I think cut is a better approach for your use case, but here are a few examples with ifelse and if.

The if/else approach would be something like the following, but with additional nested ifelse statements for each range you want to assign to a value. ifelse is "vectorized" meaning that it operates separately on every element of the input vector:

wellness_z = function(x) {
  ifelse(x==0, 1, 
         ifelse(x > 0 & x < 0.5, 2,
                ifelse(x >= 0.5 & x < 1, 3, 4)))
}

wellness_z(y)

The if statement approach doesn't work, because if is not vectorized; it looks only at the first value of the input vector:

wellness_z = function(x) {
  if(x==0) {
    1
  } else if(x > 0 & x < 0.5) {
    2
  } else if(x >= 0.5 & x < 1) {
    3
  } else {
    4
  }
}

wellness_z(y) 

[1] 1
Warning message:
In if (x == 0) { :
  the condition has length > 1 and only the first element will be used

However, you can use the base R sapply function or the purrr map function to operate on each element individually:

sapply(y, wellness_z)

purrr::map_dbl(y, wellness_z)