The German Socio-Economic-Panel (SOEP) is a longitudinal study of German households. The core questions address economic issues, work, health, and well-being. However, additional questions are sometimes added. In 2005, the SOEP included a 15-item measure of the Big Five; the so-called BFI-S (Lang et al., 2011). As each personality dimension is measured with only three items, scale scores are rather unreliable measures of the Big Five. A superior way to examine personality in the SOEP is to build a measurement model that relates observed item scores to latent factors that represent the Big Five.

Anusic et al. (2009) proposed a latent variable model for an English version of the BFI-S.

The most important feature of this model is the modeling of method factors in personality ratings. An acquiescence factor accounts for general response tendencies independent of item content. In addition, a halo factor accounts for evaluative bias that inflates correlations between two desirable or two undesirable items and attenuates correlations between a desirable and an undesirable item. The Figure shows that the halo factor is bias because it correlates highly with evaluative bias in ratings of intelligence and attractiveness.

The model also includes a higher-order factor that accounts for a correlation between extraversion and openness.

Since the article was published I have modified the model in two ways. First, the Big Five are conceptualized as fully independent which is in accordance with the original theory. Rather than allowing for correlations among Big Five factors, secondary loadings are used to allow for relationships between extraversion and openness items. Second, halo bias is modeled as a characteristic of individual items rather than the Big Five. This approach is preferable because some items have low loadings on halo.

Figure 2 shows the new model.

I fitted this model to the 2005 data using MPLUS (syntax and output: https://osf.io/vpcfd/ ). The model had acceptable fit to the data, CFI = .962, RMSEA = .035, SRMR = .029.

Table 1 shows the factor loadings. It also shows the correlation of the sum scores with the latent factors.

Item# | N | E | O | A | C | EVB | ACQ | |

Neuroticism | ||||||||

worried | 5 | 0.49 | -0.02 | 0.19 | ||||

nervous | 10 | 0.64 | -0.31 | 0.18 | ||||

relaxed | 15 | -0.55 | 0.35 | 0.21 | ||||

SUM | 0.75 | 0.00 | 0.00 | 0.00 | 0.00 | -0.30 | 0.09 | |

Extraversion | ||||||||

talkative | 2 | 0.60 | 0.13 | 0.40 | 0.23 | |||

sociable | 8 | 0.64 | 0.37 | 0.22 | ||||

reserved | 12 | -0.52 | 0.20 | -0.11 | 0.19 | |||

SUM | 0.00 | 0.75 | 0.00 | -0.10 | 0.05 | 0.36 | 0.09 | |

Openess | ||||||||

original | 4 | 0.26 | 0.41 | -0.33 | 0.38 | 0.22 | ||

artistic | 9 | 0.15 | 0.36 | 0.29 | 0.17 | |||

imaginative | 14 | 0.30 | 0.55 | 0.22 | 0.21 | |||

SUM | 0.00 | 0.30 | 0.57 | -0.13 | 0.00 | 0.39 | 0.26 | |

Agreeableness | ||||||||

rude | 3 | 0.12 | -0.51 | -0.32 | 0.19 | |||

forgiving | 6 | 0.23 | 0.32 | 0.24 | ||||

considerate | 13 | 0.49 | 0.48 | 0.29 | ||||

SUM | 0.00 | -0.07 | 0.00 | 0.58 | 0.00 | 0.50 | 0.11 | |

Conscientiousness | ||||||||

thorough | 1 | 0.71 | 0.35 | 0.30 | ||||

lazy | 7 | -0.16 | -0.41 | -0.35 | 0.20 | |||

efficient | 11 | 0.39 | 0.48 | 0.28 | ||||

SUM | 0.00 | 0.00 | 0.00 | 0.09 | 0.64 | 0.51 | 0.11 |

The results show that all items load on their primary factor although some loadings are very small (e.g., forgiving). Secondary loadings tend to be small (< .2), although they are highly significant in the large sample. All items load on the evaluative bias factor, with some fairly large loadings for considerate, efficient, and talkative. Reserved is the most evaluatively neutral item. Acquiescence bias is rather weak.

The scale scores are most strongly related to the intended latent factor. The relationship is fairly strong for neuroticism and extraversion, suggesting that about 50% of the variance in scale scores reflects the intended construct. However, for the other three dimensions, correlations suggest that less than 50% of the variance reflects the intended construct. Moreover, the remaining variance is not just random measurement error. Evaluative bias contributes from 10% up to 25% of additional variance. Acquiescence bias plays a minor role because most scales have a reverse scored item. Openness is an exception and acquiescence bias contributes 10% of the variance in scores on the Openness scale.

Given the good fit of this model, I recommend it for studies that want to examine correlates of the Big Five or that want to compare groups. Using this model will produce better estimates of effect sizes and control for spurious relationships due to method factors.