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


METHODS
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.


RESULTS
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.


CONCLUSIONS
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.
Shevlin
Mark
M
School of Psychology, University of Ulster at Magee Campus, Londonderry, N Ireland. m.shevlin@ulster.ac.uk
Adamson
Gary
G
Vollebergh
Wilma
W
de Graaf
Ron
R
van Os
Jim
J
D000293:Adolescent; D000328:Adult; D003625:Data Collection / Q000295:instrumentation; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008960:Models, Psychological; D009426:Netherlands / Q000453:epidemiology; D011594:Psychometrics; D011618:Psychotic Disorders / Q000175:diagnosis* / Q000453:epidemiology; D012111:Residence Characteristics
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