new_adherence function

Probabilistically model adherence

Model the drug adherence using either a binomial probability distribution or a markov chain model based on the probability of staying adherent and of becoming adherent once non-adherent.

new_adherence(
  n = 100,
  type = c("markov", "binomial"),
  p_markov_remain_ad = 0.75,
  p_markov_become_ad = 0.75,
  p_binom = 0.7
)

Arguments

• n: number of occasions to simulate
• type: type of adherence simulation, either "markov" or "binomial"
• p_markov_remain_ad: markov probability of staying adherent
• p_markov_become_ad: markov probability of going from non-adherent to adherent state
• p_binom: binomial probability of being adherent

Returns

Returns a vector of length n

containing values 0 (non-adherent) or 1 (adherent).

Numeric vector of length n