CTNote (version 0.1.0)

detect_subpattern: Detect a Consecutive Sub-Pattern

Description

Given a use pattern string, detect if that pattern contains a consecutive sub-pattern of interest

Usage

detect_subpattern(use_pattern, subpattern, start = 1, end = -1)

Value

A single logical value indicating if the use subpattern is present in the overall use pattern string

Arguments

use_pattern

A character string showing the daily, by visit, or weekly substance use pattern for a single subject

subpattern

A character string containing the sub-pattern of interest. For example, if study dropout is seven consecutive missing UDS, then the sub-pattern would be "ooooooo".

start

These two arguments give the integer range wherein to look for the use sub-pattern of interest. Usually, start should be the week of randomization. Defaults to 1.

end

The end of the detection range. This is often the end of followup (denoted by -1, the default value, which represents the last item in the string), or this could be a set number of weeks or visits, such as 12 weeks or 48 visits.

Details

This function can be used to detect consecutive periods of drug abstinence, drug use, or study non-compliance (as measured by failure to supply urine). For example, to detect if the subject had three consecutive use weeks, the sub-pattern would be set to "+++".

At current, we allow for many symbols in the use pattern "word", such as "_" for missing by study design, "o" missing for protocol non-compliance (the most common form of missing), "+" for positive, "-" for negative, and "*" for mixed positive and negative results (this usually comes up when the visit represents multiple days and there are both positive and negative results in those days; for example, a subject is tested weekly; they provided a positive test on Tuesday but came back to provide a negative test the following day).

Examples

  # This pattern represents 26 weeks of treatment UDS
  pattern_char <- "+++++o-------+--+-o-o-o+o+"
  
  # Replace any missing UDS ("o") with positive
  cleanPattern_char <- recode_missing_visits(pattern_char)
  
  # Example: detect if the subject was able to stay clean for at least 4
  #   weeks after randomization but before the end of a 12-week observation
  #   period
  detect_subpattern(
    cleanPattern_char,
    subpattern = "----",
    end = 12
  )
  
  # Example: detect if the subject was abstinent during the last 3 weeks
  detect_subpattern(
    cleanPattern_char,
    subpattern = "---",
    start = -3, 
    end = -1
  )