Modeling Psychopathology: From Data Models to Formal Theories

Haslbeck, Jonas M B; Ryan, Oisín; Robinaugh, Donald J.; Waldorp, Lourens J.; Borsboom, Denny

doi:10.31234/osf.io/jgm7f

Cited by 88 publications

(136 citation statements)

References 77 publications

(96 reference statements)

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“…Formal models, in this context, should not be confused with "data models" that involve fitting parameters to data (e.g., correlational analysis, ANOVA, regression models; Haslbeck et al, 2019;Robinaugh et al, 2020). Instead of tools used to understand data, formal models are better seen as "thinking tools"; they allow us to track the consequences of our theoretical principles.…”

Section: Theory Construction Methodologymentioning

confidence: 99%

Theory Construction Methodology: A practical framework for theory formation in psychology

Borsboom¹,

Maas²,

Dalege³

et al. 2020

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This paper aims to improve theory formation in psychology by developing a practical methodology for constructing explanatory theories: Theory Construction Methodology (TCM). TCM is a sequence of five steps. First, the theorist identifies empirical phenomena to become the target of explanation. Second, the theorist constructs a proto-theory: a set of theoretical principles that potentially explain these phenomena. Third, the proto-theory is used to construct a formal model: a set of model equations or simulation models that encode the explanatory principles. Fourth, the theorist investigates this model’s explanatory adequacy. This is done by formalizing the empirical phenomena in terms of the model, and assessing whether the model indeed reproduces them. Fifth, the theorist studies the overall adequacy of the theory by evaluating whether phenomena are indeed reproduced faithfully, whether explanatory principles are parsimonious and substantively plausible, and whether the theory implies new predictions to promote further research. We illustrate TCM with an example taken from the intelligence literature (the mutualism model of intelligence), discuss the place of TCM in the larger scheme of scientific research, and propose an outline for a university curriculum that can systematically educate psychologists in the process of theory formation.

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Section: Theory Construction Methodologymentioning

confidence: 99%

Theory Construction Methodology: A practical framework for theory formation in psychology

Borsboom¹,

Maas²,

Dalege³

et al. 2020

Preprint

Self Cite

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“…As Cummins put it: "In psychology, we are overwhelmed with things to explain, and somewhat underwhelmed by things to explain them with" (Cummins, 2000). For this reason, many scholars have argued that psychology's attention to statistics and replicability has distracted from a problem that runs much deeper: a crisis of theory (Borsboom, 2013;Borsboom et al, 2020;Cummins, 2000;Guest & Martin, 2020;Haslbeck et al, 2019;Meehl, 1990b;Muthukrishna & Henrich, 2019;Phaf, 2020;Robinaugh, Haslbeck, et al, 2019;Smaldino, 2019;Szollosi et al, 2019;Vaidyanathan et al, 2015;Van Rooij & Baggio, 2020).…”

Section: Data Rich and Theory Poormentioning

confidence: 99%

“…Somewhat surprisingly, since starting to work on this paper in early 2019, numerous contributions in different areas of psychology have identified this crisis of theory as a crucial challenge moving forward (Borsboom et al, 2020;Burger et al, 2019;Gershman, 2019;Guest & Martin, 2020;Haslbeck et al, 2019;Kellen, 2019;Lakens & Debruine, 2020;Muthukrishna & Henrich, 2019;Oberauer & Lewandowsky, 2019;Robinaugh, Haslbeck, et al, 2019;Savi et al, 2019;Smaldino, 2019;Szollosi et al, 2019;Van Rooij & Baggio, 2020), and both the Journal of Abnormal Psychology and Perspective of Psychological Science have opened calls for special issues on theory.…”

Section: Putting the Theory Back Into Psychologymentioning

confidence: 99%

Lack of theory building and testing impedes progress in the factor and network literature

Fried¹

2020

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113

138

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The last decade has brought reforms to improve methodological practices, with the goal to increase the reliability and replicability of effects. However, explanations of effects remain scarce, and a growing chorus of scholars argues that the replicability crisis has distracted from a crisis of theory. In the same decade, the empirical literature using factor and network models has grown rapidly. I discuss three ways in which this literature falls short of theory building and testing. First, statistical and theoretical models are conflated, leading to invalid inferences such as the existence of psychological constructs based on factor models, or recommendations for clinical interventions based on network models. I demonstrate this inferential gap in a simulation study on statistical equivalence: excellent model fit does little to corroborate a theory, regardless of quality or quantity of data. Second, researchers fail to explicate theories about psychological constructs, but use implicit causal beliefs to guide inferences. These latent theories have led to problematic best practices in psychological research where inferences are drawn based on one specific causal model that is assumed, but not explicated. Third, explicated theories are often weak theories: narrative and imprecise descriptions vulnerable to hidden assumptions and unknowns. They fail to make clear predictions, and it remains unclear whether statistical effects corroborate such theories or not. Weak theories are immune to refutation or revision. I argue that these three challenges to theory building and testing are common and harmful, and impede theory formation, failure, and reform. A renewed focus on theoretical psychology and formal models offers a way forward.

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“…Recent work has highlighted the benefits of formal models in clinical psychology (e.g. Burger et al (2019);Haslbeck, Ryan, Robinaugh, Waldorp, and Borsboom (2019); Robinaugh, Haslbeck, et al (2019)). These models often take the form of a causal network, and, if accurate, have clear implications for the design of interventions.…”

Section: Controlling Psychological Network: Methodological Limitatiomentioning

confidence: 99%

On the control of psychological networks

Henry¹,

Robinaugh²,

Fried³

2020

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The combination of network theory and network psychometric methods have opened up a variety of new ways to conceptualize and study psychological disorders. The idea of psychological disorders as dynamic systems has sparked interest in developing interventions based on results of network analytic tools. However, estimating a network model is not sufficient for determining which symptoms might be most effective to intervene upon, and is not sufficient for determining the potential efficacy of any given intervention. In this paper, we attempt to remedy this gap by introducing fundamental concepts in control theory to both methodologists and applied psychologists. We show how two controllability measures, average and modal controllability, can be used to select the best set of intervention targets. We provide a statistical testing procedure for determining if the dynamical systems of different people have the same optimal intervention targets. Following that, we show how intervention scientists can probe the effects of both theoretical and empirical interventions on networks derived from real data; demonstrate how simulations can be used to account for intervention cost and the desire to reduce specific symptoms; introduce a metric for evaluating intervention efficacy, the intervention efficacy ratio (IER); and showcase how between subject heterogeneity in intervention response can be evaluated. Every step is illustrated using rich clinical EMA data from a sample of subjects undergoing treatment for complicated grief, with a focus on the outcome `Suicidal Ideation'. All methods are implemented in an open-source R package ''netcontrol'', and complete code for replicating the analyses in this manuscript is available at https://osf.io/f268v/.

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Modeling Psychopathology: From Data Models to Formal Theories

Cited by 88 publications

References 77 publications

Theory Construction Methodology: A practical framework for theory formation in psychology

Theory Construction Methodology: A practical framework for theory formation in psychology

Lack of theory building and testing impedes progress in the factor and network literature

On the control of psychological networks

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