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Abstract. Researchers use latent class (LC) analysis to derive meaningful clusters from sets of categorical variables. However, especially when the number of classes required to obtain a good fit is large, interpretation of the latent classes may not be straightforward. To overcome this problem, we propose an alternative way of performing LC analysis, Latent Class Tree (LCT) modeling. For this purpose, a recursive partitioning procedure similar to divisive hierarchical cluster analysis is used: classes are split until a certain criterion indicates that the fit does not improve. The advantage of the LCT approach compared to the standard LC approach is that it gives a clear insight into how the latent classes are formed and how solutions with different numbers of classes relate. We also propose measures to evaluate the relative importance of the splits. The practical use of the approach is illustrated by the analysis of a data set on social capital.

PurposeAs the current “one size fits all” research approach is likely to be ineffective in identifying the conditions that promote the entrepreneurial career of the solo self-employed, this paper advances the current understanding of the heterogeneity among the solo self-employed.Design/methodology/approachA person-centered approach is used to identify groups among the solo self-employed based on their starting motives and to examine their engagement in proactive career behaviors.FindingsUsing Latent Class Analysis (LCA), six groups displaying distinct motivational profiles are identified: (1) the pushed by necessity, (2) entrepreneurs by heart, (3) control-seekers, (4) occupationally-driven, (5) challenge-seekers and (6) the family business-driven. In line with the argument that starting motives affect behavior because they reflect the future work selves that individuals aim for, results show that solo self-employed with distinct motivational profiles differ in their engagement in proactive career behaviors. For future research, it is recommended to examine the role of demographic characteristics in the engagement in proactive career behaviors.Originality/valueAlthough starting motives among self-employed people have been studied frequently, this research applies an innovative methodological approach by using LCA. Hereby, a potentially more advanced configuration of starting motives is explored. Additionally, this study applies a career perspective towards the domain of solo self-employment by exploring how solo self-employed with distinct motivational profiles differ in terms of managing their entrepreneurial careers.

Typewriting studies which compare novice and expert typists have suggested that highly trained typing skills involve cognitive process with an inner and outer loop, which regulate keystrokes and words, respectively. The present study investigates these loops longitudinally, using multi-level modeling of 1,091,707 keystroke latencies from 62 children (M age=12.6 yr.) following an online typing course. Using finger movement repetition as indicator of the inner loop and words typed as indicator of the outer loop, practicing keystroke latencies resulted in different developmental curves for each loop. Moreover, based on plateaus in the developmental curves, the inner loop seemed to require less practice to develop than the outer loop.

Traditional personality disorder (PD) taxonomies have been developed for adult populations. We aimed to identify an adolescent hierarchical tree typology of PD indicators to provide classification into broad severity classes but also more fine-grained classification within those classes. A large sample of community adolescents (N = 1,940) completed a validated dimensional measure that covers a comprehensive range of pathologically formulated personality traits, the Personality Inventory for DSM-5. Latent class tree modeling suggested three classes at the first level of the tree representing high, medium, and low PD-trait levels-thus spanning the range between normal and pathological personality. These classes were divided into subclasses lower in the hierarchy, which suggested subclinical variants of patterns that are often found in clinical samples, medium levels of externalizing and internalizing behaviors, and differential profiles of thriving in the low-risk classes. The identified classes had promising initial criterion validity based on meaningful relations with self-and peerreported measures of friendship and social functioning with peers. Our hierarchical PD tree typology may represent groups at differential risk for developing PDs and could therefore be useful for preventive purposes.