Social Psychiatry and Psychiatric Epidemiology

, Volume 42, Issue 10, pp 771–779 | Cite as

An application of item response mixture modelling to psychosis indicators in two large community samples

  • Mark Shevlin
  • Gary Adamson
  • Wilma Vollebergh
  • Ron de Graaf
  • Jim van Os



Previous research has suggested that psychosis is better described as a continuum rather than a dichotomous entity. This study aimed to describe the distribution of positive psychosis-like symptoms in two large community samples using an item response mixture model.


An item response mixture model was used to explain the pattern of psychosis-like symptom endorsement. This model incorporated two elements. First, a continuous non-normal latent variable to explain the observed pattern of data. Second, a categorical latent variable to explain the variation in the continuous non-normal latent variable.


For both samples, representing broadly and narrowly defined psychosis, the best fitting model was a four-class solution. In both cases, the classes differed quantitatively rather than qualitatively.


The analysis showed that psychosis-like symptoms at the population level could be best explained by four classes that appeared to represent an underlying continuum.

Key words

psychosis IRT latent class analysis hybrid model 


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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Mark Shevlin
    • 1
  • Gary Adamson
    • 1
  • Wilma Vollebergh
    • 2
  • Ron de Graaf
    • 2
  • Jim van Os
    • 3
    • 4
  1. 1.School of PsychologyUniversity of Ulster at Magee CampusLondonderryN. Ireland
  2. 2.Netherlands Institute of Mental Health and Addiction, Trimbos InstituteUtrechtThe Netherlands
  3. 3.Dept. of Psychiatry and Neuropsychology, South Limburg Mental Health Research and Teaching Network, EURONMaastricht UniversityMaastrichtThe Netherlands
  4. 4.Division of Psychological MedicineInstitute of PsychiatryLondonUK

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