Angélique O J Cramer
Biographic Data
| ID | 3426441 |
|---|---|
| NAME | Angélique O J Cramer |
| GIVEN NAMES | Angélique O J |
| FAMILY NAME | Cramer |
| SIGNATURE | CRAMER A O J |
| AFFILIATIONS | University of Amsterdam |
| ORCID | 0000-0003-2128-0331 |
| VERIFIED | Yes |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 35 |
| AUTHOR COUNT | 14 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 1 |
Investigating the Utility of Fixed-margin Sampling in Network Psychometrics
Steinley, Hoffman, Brusco, and Sher (2017) proposed a new method for evaluating the performance of psychological network models: fixed-margin sampling. The authors investigated LASSO regularized Ising models (eLasso) by generating random datasets with the same margins as the original binary dataset, and concluded that many estimated eLasso parameters are not distinguishable from those that would be expected if the data were generated by chance. W…
Brain disorders? Not really: Why network structures block reductionism in psychopathology research
In the past decades, reductionism has dominated both research directions and funding policies in clinical psychology and psychiatry. The intense search for the biological basis of mental disorders, however, has not resulted in conclusive reductionist explanations of psychopathology. Recently, network models have been proposed as an alternative framework for the analysis of mental disorders, in which mental disorders arise from the causal interpla…
Personalized Network Modeling in Psychopathology: The Importance of Contemporaneous and Temporal Connections
Recent literature has introduced (a) the network perspective to psychology and (b) collection of time series data to capture symptom fluctuations and other time varying factors in daily life. Combining these trends allows for the estimation of intraindividual network structures. We argue that these networks can be directly applied in clinical research and practice as hypothesis generating structures. Two networks can be computed: a temporal netwo…
Mental disorders as networks of problems: A review of recent insights
PURPOSE: The network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years. METHODS: This paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three m…
Moving Forward: Challenges and Directions for Psychopathological Network Theory and Methodology
Since the introduction of mental disorders as networks of causally interacting symptoms, this novel framework has received considerable attention. The past years have resulted in over 40 scientific publications and numerous conference symposia and workshops. Now is an excellent moment to take stock of the network approach: What are its most fundamental challenges, and what are potential ways forward in addressing them? After a brief conceptual in…
Major Depression as a Complex Dynamic System
In this paper, we characterize major depression (MD) as a complex dynamic system in which symptoms (e.g., insomnia and fatigue) are directly connected to one another in a network structure. We hypothesize that individuals can be characterized by their own network with unique architecture and resulting dynamics. With respect to architecture, we show that individuals vulnerable to developing MD are those with strong connections between symptoms: e.…
Problems Attract Problems: A Network Perspective on Mental Disorders
What is the nature of mental disorders such as major depression and panic disorder? Are mental disorders analogous to tumors, in that they exist as separate entities somewhere in people's minds? Do mental disorders cause symptoms such as insomnia and fatigue? Until very recently, it was exactly this sort of thinking that (implicitly) permeated many, if not all, research paradigms in clinical psychology and psychiatry. However, in recent years, a …
From loss to loneliness: The relationship between bereavement and depressive symptoms.
Spousal bereavement can cause a rise in depressive symptoms. This study empirically evaluates 2 competing explanations concerning how this causal effect is brought about: (a) a traditional latent variable explanation, in which loss triggers depression which then leads to symptoms; and (b) a novel network explanation, in which bereavement directly affects particular depression symptoms which then activate other symptoms. We used data from the Chan…
State of the aRt personality research: A tutorial on network analysis of personality data in R
Deconstructing the construct: A network perspective on psychological phenomena
Network Analysis: An Integrative Approach to the Structure of Psychopathology
In network approaches to psychopathology, disorders result from the causal interplay between symptoms (e.g., worry → insomnia → fatigue), possibly involving feedback loops (e.g., a person may engage in substance abuse to forget the problems that arose due to substance abuse). The present review examines methodologies suited to identify such symptom networks and discusses network analysis techniques that may be used to extract clinically and scien…
Dimensions of Normal Personality as Networks in Search of Equilibrium: You Can't like Parties if you Don't like People
In one currently dominant view on personality, personality dimensions (e.g. extraversion) are causes of human behaviour, and personality inventory items (e.g. ‘I like to go to parties’ and ‘I like people’) are measurements of these dimensions. In this view, responses to extraversion items correlate because they measure the same latent dimension. In this paper, we challenge this way of thinking and offer an alternative perspective on personality a…
Qgraph: Network Visualizations of Relationships in Psychometric Data
We present the qgraph package for R, which provides an interface to visualize data through network modeling techniques. For instance, a correlation matrix can be represented as a network in which each variable is a node and each correlation an edge; by varying the width of the edges according to the magnitude of the correlation, the structure of the correlation matrix can be visualized. A wide variety of matrices that are used in statistics can b…
Comorbidity: A network perspective
The pivotal problem of comorbidity research lies in the psychometric foundation it rests on, that is, latent variable theory , in which a mental disorder is viewed as a latent variable that causes a constellation of symptoms. From this perspective, comorbidity is a (bi)directional relationship between multiple latent variables. We argue that such a latent variable perspective encounters serious problems in the study of comorbidity, and offer a ra…
Comorbidity: A network perspective
The pivotal problem of comorbidity research lies in the psychometric foundation it rests on, that is, latent variable theory , in which a mental disorder is viewed as a latent variable that causes a constellation of symptoms. From this perspective, comorbidity is a (bi)directional relationship between multiple latent variables. We argue that such a latent variable perspective encounters serious problems in the study of comorbidity, and offer a ra…
Dimensions of Normal Personality as Networks in Search of Equilibrium: You Can't like Parties if you Don't like People
In one currently dominant view on personality, personality dimensions (e.g. extraversion) are causes of human behaviour, and personality inventory items (e.g. ‘I like to go to parties’ and ‘I like people’) are measurements of these dimensions. In this view, responses to extraversion items correlate because they measure the same latent dimension. In this paper, we challenge this way of thinking and offer an alternative perspective on personality a…
Qgraph: Network Visualizations of Relationships in Psychometric Data
We present the qgraph package for R, which provides an interface to visualize data through network modeling techniques. For instance, a correlation matrix can be represented as a network in which each variable is a node and each correlation an edge; by varying the width of the edges according to the magnitude of the correlation, the structure of the correlation matrix can be visualized. A wide variety of matrices that are used in statistics can b…
Deconstructing the construct: A network perspective on psychological phenomena
Network Analysis: An Integrative Approach to the Structure of Psychopathology
In network approaches to psychopathology, disorders result from the causal interplay between symptoms (e.g., worry → insomnia → fatigue), possibly involving feedback loops (e.g., a person may engage in substance abuse to forget the problems that arose due to substance abuse). The present review examines methodologies suited to identify such symptom networks and discusses network analysis techniques that may be used to extract clinically and scien…
Problems Attract Problems: A Network Perspective on Mental Disorders
What is the nature of mental disorders such as major depression and panic disorder? Are mental disorders analogous to tumors, in that they exist as separate entities somewhere in people's minds? Do mental disorders cause symptoms such as insomnia and fatigue? Until very recently, it was exactly this sort of thinking that (implicitly) permeated many, if not all, research paradigms in clinical psychology and psychiatry. However, in recent years, a …
From loss to loneliness: The relationship between bereavement and depressive symptoms.
Spousal bereavement can cause a rise in depressive symptoms. This study empirically evaluates 2 competing explanations concerning how this causal effect is brought about: (a) a traditional latent variable explanation, in which loss triggers depression which then leads to symptoms; and (b) a novel network explanation, in which bereavement directly affects particular depression symptoms which then activate other symptoms. We used data from the Chan…
State of the aRt personality research: A tutorial on network analysis of personality data in R
Major Depression as a Complex Dynamic System
In this paper, we characterize major depression (MD) as a complex dynamic system in which symptoms (e.g., insomnia and fatigue) are directly connected to one another in a network structure. We hypothesize that individuals can be characterized by their own network with unique architecture and resulting dynamics. With respect to architecture, we show that individuals vulnerable to developing MD are those with strong connections between symptoms: e.…
Mental disorders as networks of problems: A review of recent insights
PURPOSE: The network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years. METHODS: This paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three m…
Moving Forward: Challenges and Directions for Psychopathological Network Theory and Methodology
Since the introduction of mental disorders as networks of causally interacting symptoms, this novel framework has received considerable attention. The past years have resulted in over 40 scientific publications and numerous conference symposia and workshops. Now is an excellent moment to take stock of the network approach: What are its most fundamental challenges, and what are potential ways forward in addressing them? After a brief conceptual in…
Personalized Network Modeling in Psychopathology: The Importance of Contemporaneous and Temporal Connections
Recent literature has introduced (a) the network perspective to psychology and (b) collection of time series data to capture symptom fluctuations and other time varying factors in daily life. Combining these trends allows for the estimation of intraindividual network structures. We argue that these networks can be directly applied in clinical research and practice as hypothesis generating structures. Two networks can be computed: a temporal netwo…
Brain disorders? Not really: Why network structures block reductionism in psychopathology research
In the past decades, reductionism has dominated both research directions and funding policies in clinical psychology and psychiatry. The intense search for the biological basis of mental disorders, however, has not resulted in conclusive reductionist explanations of psychopathology. Recently, network models have been proposed as an alternative framework for the analysis of mental disorders, in which mental disorders arise from the causal interpla…
Investigating the Utility of Fixed-margin Sampling in Network Psychometrics
Steinley, Hoffman, Brusco, and Sher (2017) proposed a new method for evaluating the performance of psychological network models: fixed-margin sampling. The authors investigated LASSO regularized Ising models (eLasso) by generating random datasets with the same margins as the original binary dataset, and concluded that many estimated eLasso parameters are not distinguishable from those that would be expected if the data were generated by chance. W…
Mental Health Research Topics (13 works) · Psychology (11 works) · Functional Brain Connectivity Studies (10 works) · Computer Science (9 works) · Artificial Intelligence (7 works) · Clinical Psychology (6 works) · Cognitive psychology (5 works) · Complex Network Analysis Techniques (5 works) · Perspective (graphical) (5 works) · Psychiatry (5 works)