Item response theory (IRT) and categorical data factor analysis (CDFA) are complementary methods for the analysis of the psychometric properties of psychiatric measures that purport to measure latent constructs. These methods have been applied to relatively few child and adolescent measures. We provide the first combined IRT and CDFA analysis of a clinical measure (the Short Mood and Feelings Questionnaire-SMFQ) in a community sample of 7-through 11-year-old children. Both latent variable models supported the internal construct validity of a single underlying continuum of severity of depressive symptoms. SMFQ items discriminated well at the more severe end of the depressive latent trait. Item performance was not affected by age, although age correlated significantly with latent SMFQ scores suggesting that symptom severity increased within the age period of 7-11. These results extend existing psychometric studies of the SMFQ and confirm its scaling properties as a potential dimensional measure of symptom severity of childhood depression in community samples.
KEY WORDS:Screening; childhood depression; SMFQ; item response theory; categorical data factor analysis.Over the last 40 years, the methods used to evaluate the psychometric basis of ability tests, health care surveys, and multi-item screening instruments has changed dramatically. Whilst the methodology of classical test theory (CTT) has served test development well, item response/latent trait theory (IRT) approaches have become more mainstream as the technical basis for measurement theory, test construction and scale evaluation (Embretson & Reise, 2000). Although moves towards adoption of more appropriate, non-linear and categorical data factor analysis (CDFA) models have been most apparent in ed- Costello, 2002;Cooke & Michie, 1997;Lambert et al., 2003;Patton, Carlin, Shao, Hibbert, & Bowes, 1997;Santor, Ramsay, & Zuroff, 1994). Currently there are very few reports that have applied such methodologies in samples of young children (Cheong & Raudenbush, 2000). One reason for the under-exploitation of such methodologies may be because researchers have not been introduced to the potential and practicalities of these methods (Rouse, Finger, & Butcher, 1999) and are therefore unaware of the advantages they offer over conventional (CTT) methods (van der Linden & Hambleton, 1997). Although CTT is often included in the curriculum of both clinical and applied psychologists, IRT is rarely taught, and has had less coverage in mainstream
380Sharp, Goodyer, and Croudace psychology journals (Embretson & Reise, 2000). We provide an application of IRT and categorical data factor analysis (CDFA) methods to a commonly used self-report measure of depressive symptoms in children, the Short Mood and Feelings Questionnaire (SMFQ; Angold et al., 1995). As such, the aim of this paper was to scrutinize the internal construct validity of the SMFQ. To this end, we used latent variable models implemented with both an IRT and appropriate factor analysis framework (CDFA). Within a lat...