Repository logo
Log In
Log in as University member:
Log in as external user:
Have you forgotten your password?

Please contact the hohPublica team if you do not have a valid Hohenheim user account (hohPublica@uni-hohenheim.de)
Hilfe
  • English
  • Deutsch
    Communities & Collections
    All of hohPublica
Log In
Log in as University member:
Log in as external user:
Have you forgotten your password?

Please contact the hohPublica team if you do not have a valid Hohenheim user account (hohPublica@uni-hohenheim.de)
Hilfe
  • English
  • Deutsch
  1. Home
  2. Browse by Subject

Browsing by Subject "Mixed treatment comparisons"

Type the first few letters and click on the Browse button
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    Publication
    A REML method for the evidence‐splitting model in network meta‐analysis
    (2023) Piepho, Hans‐Peter; Forkman, Johannes; Malik, Waqas Ahmed
    Checking for possible inconsistency between direct and indirect evidence is an important task in network meta‐analysis. Recently, an evidence‐splitting (ES) model has been proposed, that allows separating direct and indirect evidence in a network and hence assessing inconsistency. A salient feature of this model is that the variance for heterogeneity appears in both the mean and the variance structure. Thus, full maximum likelihood (ML) has been proposed for estimating the parameters of this model. Maximum likelihood is known to yield biased variance component estimates in linear mixed models, and this problem is expected to also affect the ES model. The purpose of the present paper, therefore, is to propose a method based on residual (or restricted) maximum likelihood (REML). Our simulation shows that this new method is quite competitive to methods based on full ML in terms of bias and mean squared error. In addition, some limitations of the ES model are discussed. While this model splits direct and indirect evidence, it is not a plausible model for the cause of inconsistency.

  • Contact
  • FAQ
  • Cookie settings
  • Imprint/Privacy policy