2.2.6. Limitations
Despite the evidence for the value of the FIPI, single-item measures are subject to
some serious limitations. The first limitation is the psychometric cost of using short
measures. Compared with standard multi-item measures of the Big Five, the FIPI isless reliable, converges less strongly with other Big-Five measures, and has weaker
correlations with other variables.
The second limitation associated with the FIPI concerns its use in analyses involving
latent variables, such as structural equation modeling. Such analyses estimate the
error terms with which latent variables are measured by using multiple indicators of
the same latent variable. Single-item measures provide only a single estimate of the
latent variable so error terms must be estimated by other means. For example, researchers
may have to estimate the error terms from test–retest correlations, such
as the ones reported in Table 3.
In addition, unlike multi-item measures, which can balance positive and negative
items, single-item measures cannot assess or control for acquiescence bias. Nor do
single items permit researchers to check for errors (e.g., from data entry) using internal
consistency estimates or factor analysis.
Although the FIPI fared reasonably well compared to the BFI, there are clearly a
number of weakness associated with single-item measures. Therefore, we set out to
create a second brief measure of the Big-Five personality dimensions that avoided
the pitfalls associated with single-item scales.
2.2.6. LimitationsDespite the evidence for the value of the FIPI, single-item measures are subject tosome serious limitations. The first limitation is the psychometric cost of using shortmeasures. Compared with standard multi-item measures of the Big Five, the FIPI isless reliable, converges less strongly with other Big-Five measures, and has weakercorrelations with other variables.The second limitation associated with the FIPI concerns its use in analyses involvinglatent variables, such as structural equation modeling. Such analyses estimate theerror terms with which latent variables are measured by using multiple indicators ofthe same latent variable. Single-item measures provide only a single estimate of thelatent variable so error terms must be estimated by other means. For example, researchersmay have to estimate the error terms from test–retest correlations, suchas the ones reported in Table 3.In addition, unlike multi-item measures, which can balance positive and negativeitems, single-item measures cannot assess or control for acquiescence bias. Nor dosingle items permit researchers to check for errors (e.g., from data entry) using internalconsistency estimates or factor analysis.Although the FIPI fared reasonably well compared to the BFI, there are clearly anumber of weakness associated with single-item measures. Therefore, we set out tocreate a second brief measure of the Big-Five personality dimensions that avoidedข้อผิดพลาดเกี่ยวข้องกับเครื่องชั่งน้ำหนักสินค้าเดียว
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