Goldberg’s ‘IPIP’ Big-Five factor markers: Internal consistency and concurrent validation in Scotland
Introduction
Personality assessment is important in a variety of situations, from academic research to clinical settings. Individual differences in human personality are often described as being quite comprehensively described by 5 higher-order factors (Matthews, Deary, & Whiteman, 2003), although an increasing body of evidence suggests that additional factors are required to account for important individual variation beyond that assessed within more traditional 5-factor frameworks (Paunonen & Jackson, 2000); a recent review of 8 psycholexical studies found support for a 6-factor model across seven languages (Ashton et al., 2004). For the purposes of the current study, however, a 5-factor model is employed due to the general consensus that exists about what those factors are; models with a higher number of factors are not entirely in agreement about what a 6th, 7th or nth factor would be.
Section snippets
Recent debate and Goldberg’s proposal
Goldberg (1999) has argued that scientific progress within the development of personality inventories has been “dismally slow” (p. 7). He attributes this to the fact that most of the broad-bandwidth personality inventories developed are proprietary instruments (such as the NEO PI-R/FFI: Costa & McCrae, 1992), possibly leading to a lack of improvement as researchers require permission from the copyright holders and are charged for each questionnaire used. However, Costa and McCrae (1999)
The IPIP Big-Five factor markers
The IPIP contains not only versions of proprietary scales, but also a number of items known collectively as the Big-Five factor markers (Goldberg, 2001). The starting point for the creation of these items was Goldberg’s (1992) 100 unipolar Big-Five factor markers (derived from early lexical studies in English). These trait-descriptive adjectives had been used in a number of studies (Goldberg, 1992) and suggested 5 broad factors (very similar to those recovered from questionnaire studies),
The current study
Goldberg’s IPIP Big-Five factor markers are examined in two stages. The 1st investigates the factorial structure of the IPIP items and the internal consistency of the IPIP scales in three samples of different ages. In addition, age differences in IPIP scales are examined. The 2nd stage correlates IPIP scales with the NEO-FFI and the EPQ-R Short Form scales in a sample of middle-aged individuals, in order to assess the IPIP’s concurrent validity.
IPIP Big-Five factor markers (Goldberg, 2001)
The IPIP Big-Five factor markers consist of a 50 or 100-item inventory that can be freely downloaded from the internet for use in research (Goldberg, 2001). The current study makes use of the 50-item version consisting of 10 items for each of the Big-Five personality factors: Extraversion (E), Agreeableness (A), Conscientiousness (C), Emotional Stability (ES) and Intellect (I). For each of the items, which are in sentence fragment form (e.g., “Am the life of the party”), “I” was added at the
Student sample
From the PCA, the overall measure of sampling adequacy (MSA) was 0.74, whilst the item values were within acceptable limits (the lowest being. 59). This suggests the PCA could be conducted without having to remove any unsuitable items. The scree plot produced suggested the extraction of 6 factors accounting for 46.7% of the variance. This is not reported here (details are available from the authors on request), as the 6-factor solution results mainly from a split of the Intellect factor into
Discussion
The results of the current study are encouraging with regard to the IPIP 50-item Big-Five factor markers. In the 3 samples the 5-factor structure proposed by Goldberg has been confirmed, with only minor deviations from the expected item loadings. The 5 IPIP scales have high internal consistencies comparable to those previously cited (Goldberg, 2001). Cross-sectional changes with age are reported for the scales for the first time, and these generally follow the patterns seen in previous work
Acknowledgement
The authors would like to thank Christine Braehler, Sarah Chalmers, Helen Fletcher and Ruth Turner for their assistance in distributing the IPIP to the student sample, and collating the responses. Alan Gow holds a Royal Society of Edinburgh/Lloyds TSB Foundation for Scotland Studentship. Ian Deary is the recipient of a Royal Society-Wolfson Research Merit Award.
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