Jana Holtmann
Biographic Data
| ID | 6098474 |
|---|---|
| NAME | Jana Holtmann |
| GIVEN NAMES | Jana |
| FAMILY NAME | Holtmann |
| SIGNATURE | HOLTMANN J |
| AFFILIATIONS | Leipzig University |
| ORCID | 0000-0002-7949-0772 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 4 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Unique Contributions of Dynamic Affect Indicators – Beyond Static Variability
Indicators of affect dynamics (IADs) capture temporal dependencies and instability in affective trajectories over time. However, the relevance of IADs for the prediction of time-invariant outcomes (e.g., depressive symptoms) was recently challenged due to results suggesting low predictive utility beyond intraindividual means and variances. We argue that these results may in part be explained by mathematical redundancies between IADs and static va…
Modeling Heterogeneity in Temporal Dynamics: Extending Latent State-Trait Autoregressive and Cross-lagged Panel Models to Mixture Distribution Models
Longitudinal models suited for the analysis of panel data, such as cross-lagged panel or autoregressive latent-state trait models, assume population homogeneity with respect to the temporal dynamics of the variables under investigation. This assumption is likely to be too restrictive in a myriad of research areas. We propose an extension of autoregressive and cross-lagged latent state-trait models to mixture distribution models. The models allow …
The Impact of Non-Normality on Causal Effect Estimates in Structural Equation Models with Ordered Categorical Variables
Consistency and Specificity of Attachments to Parents, Friends, and Romantic Partners in Emerging Adulthood
The idea of a general working model of attachment suggests a high consistency among the attachments to different attachment figures. However, many empirical results show that attachments to different attachment figures differ substantially. In this study, 512 emerging adults rated their attachment quality to one parent, the romantic partner, and several friends over three measurement occasions. We used a multilevel structural equation model to ex…
A Monte Carlo Simulation Study on the Influence of Unequal Group Sizes on Parameter Estimation in Multilevel Confirmatory Factor Analysis
Unequal group sizes (imbalance) and small sample sizes are common in multilevel confirmatory factor analyses (ML-CFA). This simulation study examined the influence of imbalance combined with small sample sizes on both levels on estimation performance in ML-CFA. Imbalance did not influence estimation performance given the minimum sample size requirements. Greater sample sizes on one level compensated for smaller sample sizes on the respective othe…
A Comparison of ML, WLSMV, and Bayesian Methods for Multilevel Structural Equation Models in Small Samples: A Simulation Study
Multilevel structural equation models are increasingly applied in psychological research. With increasing model complexity, estimation becomes computationally demanding, and small sample sizes pose further challenges on estimation methods relying on asymptotic theory. Recent developments of Bayesian estimation techniques may help to overcome the shortcomings of classical estimation techniques. The use of potentially inaccurate prior information m…
I’m lonely, can’t you tell? Convergent validity of self- and informant ratings of loneliness
A Comparison of ML, WLSMV, and Bayesian Methods for Multilevel Structural Equation Models in Small Samples: A Simulation Study
Multilevel structural equation models are increasingly applied in psychological research. With increasing model complexity, estimation becomes computationally demanding, and small sample sizes pose further challenges on estimation methods relying on asymptotic theory. Recent developments of Bayesian estimation techniques may help to overcome the shortcomings of classical estimation techniques. The use of potentially inaccurate prior information m…
I’m lonely, can’t you tell? Convergent validity of self- and informant ratings of loneliness
A Monte Carlo Simulation Study on the Influence of Unequal Group Sizes on Parameter Estimation in Multilevel Confirmatory Factor Analysis
Unequal group sizes (imbalance) and small sample sizes are common in multilevel confirmatory factor analyses (ML-CFA). This simulation study examined the influence of imbalance combined with small sample sizes on both levels on estimation performance in ML-CFA. Imbalance did not influence estimation performance given the minimum sample size requirements. Greater sample sizes on one level compensated for smaller sample sizes on the respective othe…
Consistency and Specificity of Attachments to Parents, Friends, and Romantic Partners in Emerging Adulthood
The idea of a general working model of attachment suggests a high consistency among the attachments to different attachment figures. However, many empirical results show that attachments to different attachment figures differ substantially. In this study, 512 emerging adults rated their attachment quality to one parent, the romantic partner, and several friends over three measurement occasions. We used a multilevel structural equation model to ex…
Modeling Heterogeneity in Temporal Dynamics: Extending Latent State-Trait Autoregressive and Cross-lagged Panel Models to Mixture Distribution Models
Longitudinal models suited for the analysis of panel data, such as cross-lagged panel or autoregressive latent-state trait models, assume population homogeneity with respect to the temporal dynamics of the variables under investigation. This assumption is likely to be too restrictive in a myriad of research areas. We propose an extension of autoregressive and cross-lagged latent state-trait models to mixture distribution models. The models allow …
The Impact of Non-Normality on Causal Effect Estimates in Structural Equation Models with Ordered Categorical Variables
Unique Contributions of Dynamic Affect Indicators – Beyond Static Variability
Indicators of affect dynamics (IADs) capture temporal dependencies and instability in affective trajectories over time. However, the relevance of IADs for the prediction of time-invariant outcomes (e.g., depressive symptoms) was recently challenged due to results suggesting low predictive utility beyond intraindividual means and variances. We argue that these results may in part be explained by mathematical redundancies between IADs and static va…
Mathematics (6 works) · Psychology (5 works) · Computer Science (4 works) · Econometrics (4 works) · Statistics (4 works) · Structural equation modeling (4 works) · Categorical variable (3 works) · Mental Health Research Topics (3 works) · Psychometric Methodologies and Testing (3 works) · Advanced Causal Inference Techniques (2 works)