title: A 'missing not at random' (MNAR) and 'missing at random' (MAR) growth model comparison with a buprenorphine/naloxone clinical trial.
abstract: OBJECTIVE
  To compare three missing data strategies: (i) the latent growth model that assumes the data are missing at random (MAR) model; (ii) the Diggle-Kenward missing not at random (MNAR) model, where dropout is a function of previous/concurrent urinalysis (UA) submissions; and (iii) the Wu-Carroll MNAR model where dropout is a function of the growth factors. DESIGN : Secondary data analysis of a National Drug Abuse Treatment Clinical Trials Network trial that examined a 7-day versus 28-day taper (i.e. stepwise decrease in buprenorphine/naloxone) on the likelihood of submitting an opioid-positive UA during treatment.
  
  
  METHODS
  11 out-patient treatment settings in 10 US cities.
  
  
  METHODS
  A total of 516 opioid-dependent participants.
  
  
  METHODS
  Opioid UAs provided across the 4-week treatment period.
  
  
  RESULTS
  The MAR model showed a significant effect (B = -0.45, P < 0.05) of trial arm on the opioid-positive UA slope (i.e. 28-day taper participants were less likely to submit a positive UA over time) with a small effect size (d = 0.20). The MNAR Diggle-Kenward model demonstrated a significant (B = -0.64, P < 0.01) effect of trial arm on the slope with a large effect size (d = 0.82). The MNAR Wu-Carroll model showed a significant (B = -0.41, P < 0.05) effect of trial arm on the UA slope that was relatively small (d = 0.31).
  
  
  CONCLUSIONS
  This performance comparison of three missing data strategies (latent growth model, Diggle-Kenward selection model, Wu-Carrol selection model) on sample data indicates a need for increased use of sensitivity analyses in clinical trial research. Given the potential sensitivity of the trial arm effect to missing data assumptions, it is critical for researchers to consider whether the assumptions associated with each model are defensible.
authors.affiliation: College of Nursing, Washington State University, Spokane, WA, USA; Department of Psychology, Washington State University, Pullman, WA, USA; Program of Excellence in Addictions Research, Washington State University, Spokane, WA, USA; Program for Rural Mental Health and Substance Abuse Treatment, Washington State University, Spokane, WA, USA; Translational Addictions Research Center, Washington State University, Pullman, WA, USA.
authors.forename: Sterling
authors.initials: S
authors.lastname: McPherson
authors.forename: Celestina
authors.initials: C
authors.lastname: Barbosa-Leiker
authors.forename: Mary Rose
authors.initials: MR
authors.lastname: Mamey
authors.forename: Michael
authors.initials: M
authors.lastname: McDonell
authors.forename: Craig K
authors.initials: CK
authors.lastname: Enders
authors.forename: John
authors.initials: J
authors.lastname: Roll
mesh_terms: D000701:Analgesics, Opioid / Q000652:urine; D000069479:Buprenorphine, Naloxone Drug Combination / Q000627:therapeutic use*; D003625:Data Collection / Q000592:standards; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D015337:Multicenter Studies as Topic; D009293:Opioid-Related Disorders / Q000534:rehabilitation*; D016032:Randomized Controlled Trials as Topic; D015813:Substance Abuse Detection / Q000379:methods
chemical_list: D000701:Analgesics, Opioid; D000069479:Buprenorphine, Naloxone Drug Combination
keywords: Latent growth modeling; longitudinal missing data; missing not at random models; randomized clinical trials; sensitivity analysis; substance use disorder treatment