Consolidating and Advancing the Methodology to Address Missing Participant Outcome Data in Conventional and Network Meta-analysis of Healthcare Interventions

• Applicant: Privatdozentin Dr. Loukia Spineli
• Subject Area: Epidemiology and Medical Biometry/Statistics
• Term: from 2017 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 339420617

• Final Report Year: 2021

Final Report Abstract

No abstract available

Publications

• A systematic survey shows that reporting and handling of missing outcome data in networks of interventions is poor. BMC Med Res Methodol 2018;18:115
  Spineli LM, Yepes-Nuñez JJ, Schünemann H
  
• An empirical comparison of Bayesian modelling strategies for missing binary outcome data in network meta-analysis. BMC Med Res Methodol 2019;19(1):86
  Spineli LM
  
• Modeling missing binary outcome data while preserving transitivity assumption yielded more credible network meta-analysis results. J Clin Epidemiol 2019;105:19-26
  Spineli LM
  
• Participants' outcomes gone missing within a network of interventions: Bayesian modeling strategies. Stat Med 2019;38(20):3861-3879
  Spineli LM, Kalyvas C, Pateras K
  
• Comparison of exclusion, imputation and modelling of missing binary outcome data in frequentist network meta-analysis. BMC Med Res Methodol 2020; 20(1):48
  Spineli LM, Kalyvas C
  
• Continuous(ly) missing outcome data in network meta-analysis: a one-stage pattern-mixture model approach. Stat Methods Med Res 2021; 30(4):958–975
  Spineli LM, Kalyvas C, Papadimitropoulou K
  
• Incorporating Missing Outcome Data in The Sample Size Calculation For a Future Trial: A Case Study Using a Single Trial, a Pairwise and Network Meta-Analysis. 2021
  Spineli LM
  
• Pattern-mixture model in network metaanalysis of binary missing outcome data: one-stage or two-stage approach? BMC Med Res Methodol 2021; 21(1):12
  Spineli LM, Papadimitropoulou K, Kalyvas C
  
• Quantifying the robustness of primary analysis results: a case study on missing outcome data in pairwise and network meta-analysis. Res Synth Methods 2021;12(4):475-490
  Spineli LM, Kalyvas C, Papadimitropoulou K