Given the following equation definition:
For men: (10 x w) + (6.25 x h) - (5 x a) + 5 For women:(10 x w) + (6.25 x h) - (5 x a) - 161
w = weight in kg (1 pound = 0.45359237 kilograms) h = height in cm (1 inch = 2.54 centimeters) a = age (in years)
Activity Factor Category Definition:
1.2 if sedentary, little or no exercise and desk job 1.375 if lightly Active, light exercise, or sports 1-3 days a week 1.55 if moderately active, moderate exercise, or sports 3-5 days a week 1.725 if very active, hard exercise, or sports 6-7 days a week 1.9 if extremely active, hard daily exercise or sports and physical job
I am trying to build a reverse calculation given N-1 variables.
For example given:
target_calories: 1500 gender: F weight = 50 height = 170 What is her age? age = (target_calories - ((10*w) + (6.25*h) + 5))/(-5)
I am trying to generalize it and here is what I have done so far:
var_table <- tibble(gender = "M", w_kg = w_kg, h_cm = h_cm, age = age, activity_factor = activity_factor) var2calc <- names(which(sapply(var_table, anyNA)))
I can solve this using a lot of if-else statements but I am trying to make it efficient and elegant.
I thought about calculations within the above
tibble var_table + dplyr verbs and given a missing variable value, calculate it according to a specific formula.
Please advise what is the best way to do this?