Martin Hecht
Biographic Data
| ID | 4461980 |
|---|---|
| NAME | Martin Hecht |
| GIVEN NAMES | Martin |
| FAMILY NAME | Hecht |
| SIGNATURE | HECHT M |
| AFFILIATIONS | Helmut Schmidt University |
| ORCID | 0000-0002-5168-4911 |
| VERIFIED | Yes |
| TOTAL WORKS | 25 |
| TOTAL CITATIONS | 3 |
| AUTHOR COUNT | 25 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1998 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Fast-Track Your Abstract Screening
Research syntheses, such as systematic reviews and meta-analyses, are crucial for synthesizing research to support evidence-based decision-making. However, the abstract-screening phase, during which researchers evaluate titles and abstracts for inclusion, is highly time-consuming and often results in cognitive biases and fatigue. To address these challenges, machine-learning-assisted tools, particularly those using active learning, have gained pr…
Bayesian Hierarchical Moderated Factor Analysis for Testing Measurement Invariance in Multilevel Data
Comparing machine learning methods for predicting dark triad personality traits using social media text data
The Dark Triad (DT) personality traits, characterized by manipulativeness, callousness, and egocentrism, are linked to both negative outcomes such as aggression and delinquency, as well as positive outcomes like career success. This study aims to compare different machine learning models for predicting DT traits − Narcissism, Machiavellianism, and Psychopathy − using social media text data from Facebook status updates and personality questionnair…
Multilevel Multigroup Structural Equation Modeling In A Single-Level Framework
Studying Between-Subject Differences in Trends and Dynamics
The recently proposed continuous-time latent curve model with structured residuals (CT-LCM-SR) addresses several challenges associated with longitudinal data analysis in the behavioral sciences. First, it provides information about process trends and dynamics. Second, using the continuous-time framework, the CT-LCM-SR can handle unequally spaced measurement occasions and describes processes independently of the length of the time intervals used i…
Finding the Optimal Number of Persons ( N ) and Time Points ( T ) for Maximal Power in Dynamic Longitudinal Models Given a Fixed Budget
Planning longitudinal studies can be challenging as various design decisions need to be made. Often, researchers are in search for the optimal design that maximizes statistical power to test certain parameters of the employed model. We provide a user-friendly Shiny app OptDynMo available at https://shiny.psychologie.hu-berlin.de/optdynmo that helps to find the optimal number of persons (N) and the optimal number of time points (T) for which the p…
Quantifying Individual Personality Change More Accurately by Regression-Based Change Scores
We investigated three different approaches for quantifying individual change and reporting it back to persons: (a) the common change score, which is obtained by first computing scale scores from two consecutive measurements and then subtract these scores from one another, (b) the ad-hoc approach, which is similar to the former approach but uses regression scores instead of scale scores, and (c) Kelley’s approach, which computes the change score d…
To Be Long or To Be Wide
A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect these approaches to perform similarly. However, the two data formats yield data matrices with different numbers of columns and rows, and their cols : rows is related to the magnitude of eigenvalue bias in sample covariance matrices. Previous studies have s…
Novick Meets Bayes
The assessment of individual students is not only crucial in the school setting but also at the core of educational research. Although classical test theory focuses on maximizing insights from student responses, the Bayesian perspective incorporates the assessor's prior belief, thereby enriching assessment with knowledge gained from previous interactions with the student or with similar students. We propose and illustrate a formal Bayesian approa…
Reducing Loneliness through the Power of Practicing Together
Loneliness has become a pressing topic, especially among young adults and during the COVID-19 pandemic. In a randomized controlled trial with 253 healthy adults, we evaluated the differential efficacy of two 10-week app-delivered mental training programs: one based on classic mindfulness and one on an innovative partner-based socio-emotional practice (Affect Dyad). We show that the partner-based training resulted in greater reductions in loneline…
Shrinking Small Sample Problems in Multilevel Structural Equation Modeling via Regularization of the Sample Covariance Matrix
Small sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such as pilot studies or when populations are inherently small, increasing samples sizes is not feasible. As a remedy, we propose a two-stage regularized estimation approach designed for scenarios with both a small number of groups and small group sizes, an…
From Intellectual Investment Trait Theory to Dynamic Intellectual Investment Trait and State Theory
This paper introduces Dynamic Intellectual Investment Trait and State Theory, an extension of Intellectual Investment Trait Theory. Our theory extension (a) centers on dynamic within-person effects of cognitive performance states on intellectual investment personality states and vice versa (i.e., reciprocal effects), (b) integrates within-person dynamics and developmental trajectories in cognitive abilities and intellectual investment traits, and…
Modeling dynamic personality theories in a continuous‐time framework
OBJECTIVE: Personality psychology has traditionally focused on stable between-person differences. Yet, recent theoretical developments and empirical insights have led to a new conceptualization of personality as a dynamic system (e.g., Cybernetic Big Five Theory). Such dynamic systems comprise several components that need to be conceptually distinguished and mapped to a statistical model for estimation. METHOD: In the current work, we illustrate …
Tend‐and‐befriend and rally around the flag effects during the Covid‐19 pandemic
The COVID‐19 pandemic and its lockdowns have uniquely challenged our social lives. The current study seeks to explore changes in social cohesion on various psychological dimensions (trust, belonging, social interaction, social engagement) and social system levels (family, friends, neighbours, institutions, nations), assessed in 3522 Berlin residents before, during, and after the first lockdown, and four times during the second lockdown. The first…
Exploring the Structure and Interrelations of Time-Stable Psychological Resilience, Psychological Vulnerability, and Social Cohesion
The current study explores the relationship between three constructs of high relevance in the context of adversities which have, however, not yet been systematically linked on the level of psychological dispositions: psychological vulnerability, psychological resilience, and social cohesion. Based on previous theoretical and empirical frameworks, a collection of trait questionnaires was assessed in a Berlin sample of 3,522 subjects between 18 and…
Coping with the Covid-19 Pandemic
The COVID-19 pandemic and associated lockdowns have posed unique and severe challenges to our global society. To gain an integrative understanding of pervasive social and mental health impacts in 3522 Berlin residents aged 18 to 65, we systematically investigated the structural and temporal relationship between a variety of psychological indicators of vulnerability, resilience and social cohesion before, during and after the first lockdown in Ger…
Exploring the Unfolding of Dynamic Effects with Continuous-Time Models
Cross-lagged panel models have been commonly applied to investigate the dynamic interplay of variables. In such discrete-time models, the size of the cross-lagged effects depends on the length of the time interval between the measurement occasions. Continuous-time modeling allows to explore this interval dependence of cross-lagged effects and thus to identify the maximal “peak” cross-lagged effects. To detect these peak effects, sufficient statis…
Sample Size Recommendations for Continuous-Time Models
Autoregressive modeling has traditionally been concerned with time-series data from one unit ( N = 1). For short time series ( T T, another source of information is often available for model estimation, that is, the persons ( N > 1). In this work, we illustrate the N / T compensation effect: With an increasing number of persons N at constant T , the model estimation performance increases, and vice versa, with an increasing number of time points T…
On the Performance of Bayesian Approaches in Small Samples
This journal recently published a systematic review of simulation studies on the performance of Bayesian approaches for estimating latent variable models in small samples. The authors of this review highlighted that Bayesian approaches can perform poorly (i.e., by exhibiting bias) when the prior distributions are not thoughtfully constructed on the basis of previous knowledge. In this comment, we question whether the bias is the most important cr…
Reply to Jiang et al
How sure can we be that a student really failed? On the measurement precision of individual pass-fail decisions from the perspective of Item Response Theory
BACKGROUND: In high-stakes assessments in medical education, the decision to let a particular participant pass or fail has far-reaching consequences. Reliability coefficients are usually used to support the trustworthiness of assessments and their accompanying decisions. However, coefficients such as Cronbach's Alpha do not indicate the precision with which an individual's performance was measured. OBJECTIVE: Since estimates of precision need to …
Modeling Booklet Effects for Nonequivalent Group Designs in Large-Scale Assessment
Multiple matrix designs are commonly used in large-scale assessments to distribute test items to students. These designs comprise several booklets, each containing a subset of the complete item pool. Besides reducing the test burden of individual students, using various booklets allows aligning the difficulty of the presented items to the assumed performance level of examined subgroups. While this may improve measurement precision and students’ t…
Effects of Design Properties on Parameter Estimation in Large-Scale Assessments
The selection of an appropriate booklet design is an important element of large-scale assessments of student achievement. Two design properties that are typically optimized are the balance with respect to the positions the items are presented and with respect to the mutual occurrence of pairs of items in the same booklet. The purpose of this study is to investigate the effects of these two design properties on bias and root mean square error of i…
Modernitat und Burgerlichkeit
Modernität und Bürgerlichkeit
Mit »Modernität und Bürgerlichkeit« legt Martin Hecht eine für die internationale Max-Weber-Forschung ungewöhnliche Schrift vor. Er vergleicht darin die politisch-philosophischen Ideen Max Webers mit denjenigen zweier praktischer Philosophen, die beide viel älteren geistesgeschichtlichen Epochen angehören: Jean-Jacques Rousseau und Alexis de Tocqueville. -- Über diese erstmalige Kontextualisierung Max Webers in größere Zusammenhänge der abendländ…
Shrinking Small Sample Problems in Multilevel Structural Equation Modeling via Regularization of the Sample Covariance Matrix
Small sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such as pilot studies or when populations are inherently small, increasing samples sizes is not feasible. As a remedy, we propose a two-stage regularized estimation approach designed for scenarios with both a small number of groups and small group sizes, an…
From Intellectual Investment Trait Theory to Dynamic Intellectual Investment Trait and State Theory
This paper introduces Dynamic Intellectual Investment Trait and State Theory, an extension of Intellectual Investment Trait Theory. Our theory extension (a) centers on dynamic within-person effects of cognitive performance states on intellectual investment personality states and vice versa (i.e., reciprocal effects), (b) integrates within-person dynamics and developmental trajectories in cognitive abilities and intellectual investment traits, and…
Tend‐and‐befriend and rally around the flag effects during the Covid‐19 pandemic
The COVID‐19 pandemic and its lockdowns have uniquely challenged our social lives. The current study seeks to explore changes in social cohesion on various psychological dimensions (trust, belonging, social interaction, social engagement) and social system levels (family, friends, neighbours, institutions, nations), assessed in 3522 Berlin residents before, during, and after the first lockdown, and four times during the second lockdown. The first…
Modernitat und Burgerlichkeit
Modernität und Bürgerlichkeit
Mit »Modernität und Bürgerlichkeit« legt Martin Hecht eine für die internationale Max-Weber-Forschung ungewöhnliche Schrift vor. Er vergleicht darin die politisch-philosophischen Ideen Max Webers mit denjenigen zweier praktischer Philosophen, die beide viel älteren geistesgeschichtlichen Epochen angehören: Jean-Jacques Rousseau und Alexis de Tocqueville. -- Über diese erstmalige Kontextualisierung Max Webers in größere Zusammenhänge der abendländ…
Modeling Booklet Effects for Nonequivalent Group Designs in Large-Scale Assessment
Multiple matrix designs are commonly used in large-scale assessments to distribute test items to students. These designs comprise several booklets, each containing a subset of the complete item pool. Besides reducing the test burden of individual students, using various booklets allows aligning the difficulty of the presented items to the assumed performance level of examined subgroups. While this may improve measurement precision and students’ t…
Effects of Design Properties on Parameter Estimation in Large-Scale Assessments
The selection of an appropriate booklet design is an important element of large-scale assessments of student achievement. Two design properties that are typically optimized are the balance with respect to the positions the items are presented and with respect to the mutual occurrence of pairs of items in the same booklet. The purpose of this study is to investigate the effects of these two design properties on bias and root mean square error of i…
How sure can we be that a student really failed? On the measurement precision of individual pass-fail decisions from the perspective of Item Response Theory
BACKGROUND: In high-stakes assessments in medical education, the decision to let a particular participant pass or fail has far-reaching consequences. Reliability coefficients are usually used to support the trustworthiness of assessments and their accompanying decisions. However, coefficients such as Cronbach's Alpha do not indicate the precision with which an individual's performance was measured. OBJECTIVE: Since estimates of precision need to …
Exploring the Unfolding of Dynamic Effects with Continuous-Time Models
Cross-lagged panel models have been commonly applied to investigate the dynamic interplay of variables. In such discrete-time models, the size of the cross-lagged effects depends on the length of the time interval between the measurement occasions. Continuous-time modeling allows to explore this interval dependence of cross-lagged effects and thus to identify the maximal “peak” cross-lagged effects. To detect these peak effects, sufficient statis…
Sample Size Recommendations for Continuous-Time Models
Autoregressive modeling has traditionally been concerned with time-series data from one unit ( N = 1). For short time series ( T T, another source of information is often available for model estimation, that is, the persons ( N > 1). In this work, we illustrate the N / T compensation effect: With an increasing number of persons N at constant T , the model estimation performance increases, and vice versa, with an increasing number of time points T…
On the Performance of Bayesian Approaches in Small Samples
This journal recently published a systematic review of simulation studies on the performance of Bayesian approaches for estimating latent variable models in small samples. The authors of this review highlighted that Bayesian approaches can perform poorly (i.e., by exhibiting bias) when the prior distributions are not thoughtfully constructed on the basis of previous knowledge. In this comment, we question whether the bias is the most important cr…
Reply to Jiang et al
Exploring the Structure and Interrelations of Time-Stable Psychological Resilience, Psychological Vulnerability, and Social Cohesion
The current study explores the relationship between three constructs of high relevance in the context of adversities which have, however, not yet been systematically linked on the level of psychological dispositions: psychological vulnerability, psychological resilience, and social cohesion. Based on previous theoretical and empirical frameworks, a collection of trait questionnaires was assessed in a Berlin sample of 3,522 subjects between 18 and…
Coping with the Covid-19 Pandemic
The COVID-19 pandemic and associated lockdowns have posed unique and severe challenges to our global society. To gain an integrative understanding of pervasive social and mental health impacts in 3522 Berlin residents aged 18 to 65, we systematically investigated the structural and temporal relationship between a variety of psychological indicators of vulnerability, resilience and social cohesion before, during and after the first lockdown in Ger…
Modeling dynamic personality theories in a continuous‐time framework
OBJECTIVE: Personality psychology has traditionally focused on stable between-person differences. Yet, recent theoretical developments and empirical insights have led to a new conceptualization of personality as a dynamic system (e.g., Cybernetic Big Five Theory). Such dynamic systems comprise several components that need to be conceptually distinguished and mapped to a statistical model for estimation. METHOD: In the current work, we illustrate …
Tend‐and‐befriend and rally around the flag effects during the Covid‐19 pandemic
The COVID‐19 pandemic and its lockdowns have uniquely challenged our social lives. The current study seeks to explore changes in social cohesion on various psychological dimensions (trust, belonging, social interaction, social engagement) and social system levels (family, friends, neighbours, institutions, nations), assessed in 3522 Berlin residents before, during, and after the first lockdown, and four times during the second lockdown. The first…
Studying Between-Subject Differences in Trends and Dynamics
The recently proposed continuous-time latent curve model with structured residuals (CT-LCM-SR) addresses several challenges associated with longitudinal data analysis in the behavioral sciences. First, it provides information about process trends and dynamics. Second, using the continuous-time framework, the CT-LCM-SR can handle unequally spaced measurement occasions and describes processes independently of the length of the time intervals used i…
Finding the Optimal Number of Persons ( N ) and Time Points ( T ) for Maximal Power in Dynamic Longitudinal Models Given a Fixed Budget
Planning longitudinal studies can be challenging as various design decisions need to be made. Often, researchers are in search for the optimal design that maximizes statistical power to test certain parameters of the employed model. We provide a user-friendly Shiny app OptDynMo available at https://shiny.psychologie.hu-berlin.de/optdynmo that helps to find the optimal number of persons (N) and the optimal number of time points (T) for which the p…
Quantifying Individual Personality Change More Accurately by Regression-Based Change Scores
We investigated three different approaches for quantifying individual change and reporting it back to persons: (a) the common change score, which is obtained by first computing scale scores from two consecutive measurements and then subtract these scores from one another, (b) the ad-hoc approach, which is similar to the former approach but uses regression scores instead of scale scores, and (c) Kelley’s approach, which computes the change score d…
To Be Long or To Be Wide
A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect these approaches to perform similarly. However, the two data formats yield data matrices with different numbers of columns and rows, and their cols : rows is related to the magnitude of eigenvalue bias in sample covariance matrices. Previous studies have s…
Novick Meets Bayes
The assessment of individual students is not only crucial in the school setting but also at the core of educational research. Although classical test theory focuses on maximizing insights from student responses, the Bayesian perspective incorporates the assessor's prior belief, thereby enriching assessment with knowledge gained from previous interactions with the student or with similar students. We propose and illustrate a formal Bayesian approa…
Reducing Loneliness through the Power of Practicing Together
Loneliness has become a pressing topic, especially among young adults and during the COVID-19 pandemic. In a randomized controlled trial with 253 healthy adults, we evaluated the differential efficacy of two 10-week app-delivered mental training programs: one based on classic mindfulness and one on an innovative partner-based socio-emotional practice (Affect Dyad). We show that the partner-based training resulted in greater reductions in loneline…
Shrinking Small Sample Problems in Multilevel Structural Equation Modeling via Regularization of the Sample Covariance Matrix
Small sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such as pilot studies or when populations are inherently small, increasing samples sizes is not feasible. As a remedy, we propose a two-stage regularized estimation approach designed for scenarios with both a small number of groups and small group sizes, an…
From Intellectual Investment Trait Theory to Dynamic Intellectual Investment Trait and State Theory
This paper introduces Dynamic Intellectual Investment Trait and State Theory, an extension of Intellectual Investment Trait Theory. Our theory extension (a) centers on dynamic within-person effects of cognitive performance states on intellectual investment personality states and vice versa (i.e., reciprocal effects), (b) integrates within-person dynamics and developmental trajectories in cognitive abilities and intellectual investment traits, and…
Multilevel Multigroup Structural Equation Modeling In A Single-Level Framework
Fast-Track Your Abstract Screening
Research syntheses, such as systematic reviews and meta-analyses, are crucial for synthesizing research to support evidence-based decision-making. However, the abstract-screening phase, during which researchers evaluate titles and abstracts for inclusion, is highly time-consuming and often results in cognitive biases and fatigue. To address these challenges, machine-learning-assisted tools, particularly those using active learning, have gained pr…
Bayesian Hierarchical Moderated Factor Analysis for Testing Measurement Invariance in Multilevel Data
Comparing machine learning methods for predicting dark triad personality traits using social media text data
The Dark Triad (DT) personality traits, characterized by manipulativeness, callousness, and egocentrism, are linked to both negative outcomes such as aggression and delinquency, as well as positive outcomes like career success. This study aims to compare different machine learning models for predicting DT traits − Narcissism, Machiavellianism, and Psychopathy − using social media text data from Facebook status updates and personality questionnair…
Mathematics (14 works) · Statistics (13 works) · Computer Science (12 works) · Psychology (11 works) · Psychometric Methodologies and Testing (9 works) · Social Psychology (9 works) · Econometrics (8 works) · Mental Health Research Topics (6 works) · Clinical Psychology (5 works) · Medicine (5 works)