• Approximating Test Statistics Using Eigenvalue Block Averaging 

      Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2018)
      We introduce and evaluate a new class of approximations to common test statistics in structural equation modeling. Such test statistics asymptotically follow the distribution of a weighted sum of i.i.d. chi-square variates, ...
    • A PROBLEM WITH DISCRETIZING VALE–MAURELLI IN SIMULATION STUDIES 

      Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2019)
      Previous influential simulation studies investigate the effect of underlying non-normality in ordinal data using the Vale–Maurelli (VM) simulation method. We show that discretized data stemming from the VM method with a ...
    • Covariance Model Simulation Using Regular Vines 

      Grønneberg, Steffen; Foldnes, Njål (Journal article; Peer reviewed, 2017)
      We propose a new and flexible simulation method for non-normal data with user-specified marginal distributions, covariance matrix and certain bivariate dependencies. The VITA (VIne To Anything) method is based on regular ...
    • How general is the Vale-Maurelli simulation approach? 

      Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2015)
      The Vale-Maurelli (VM) approach to generating non-normal mul- tivariate data involves the use of Fleishman polynomials applied to an underly- ing Gaussian random vector. This method has been extensively used in Monte Carlo ...
    • On the errors committed by sequences of estimator functionals 

      Grønneberg, Steffen; Hjort, Nils Lid (Journal article; Peer reviewed, 2011)
      Consider a sequence of estimators ˆ n which converges almost surely to 0 as the sample size n tends to infinity. Under weak smoothness conditions, we identify the asymptotic limit of the last time ˆ n is further than " ...
    • Testing Model Fit by Bootstrap Selection 

      Grønneberg, Steffen; Foldnes, Njål (Journal article; Peer reviewed, 2018)
      Over the last few decades, many robust statistics have been proposed in order to assess the fit of structural equation models. To date, however, no clear recommendations have emerged as to which test statistic performs ...
    • The asymptotic covariance matrix and its use in simulation studies 

      Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2017)
      The asymptotic performance of structural equation modeling tests and standard errors are influenced by two factors: the model and the asymptotic covariance matrix Γ of the sample covariances. Although most simulation studies ...
    • The copula information criteria 

      Grønneberg, Steffen; Hjort, Nils Lid (Journal article; Peer reviewed, 2014)
      We derive two types of Akaike information criterion (AIC)-like model-selection formulae for the semiparametric pseudo-maximum likelihood procedure. We first adapt the arguments leading to the original AIC formula, related ...