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Realism and Uncertainty of Unobservable Common Causes in Factor Analysis

Noûs 50 (2):329-355 (2016)

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Causal complexity and psychological measurement.Markus Ilkka Eronen - forthcoming - Philosophical Psychology.details Psychological measurement has received strong criticism throughout the history of psychological science. Nevertheless, measurements of attributes such as emotions or intelligence continue to be widely used in research and society. I address this puzzle by presenting a new causal perspective to psychological measurement. I start with assumptions that both critics and proponents of psychological measurement are likely to accept: a minimal causal condition and the observation that most psychological concepts are ill-defined or ambiguous. Based on this, I argue that psychological (...) Download Export citation Bookmark
Methodological empiricism and the choice of measurement models in social sciences.Clayton Peterson - 2018 - European Journal for Philosophy of Science 8 (3):831-854.details Realism is generally assumed as the correct position with regards to psychological research and the measurement of psychological attributes in psychometrics. Borsboom et al., 203–219 2003), for instance, argued that the choice of a reflective measurement model necessarily implies a commitment to the existence of psychological constructs as well as a commitment to the belief that empirical testing of measurement models can justify their correspondence with real causal structures. Hood :739–761 2013) deemphasized Borsboom et al.’s position and argued that the (...) Download Export citation Bookmark 1 citation
Intervention and Identifiability in Latent Variable Modelling.Jan-Willem Romeijn & Jon Williamson - 2018 - Minds and Machines 28 (2):243-264.details We consider the use of interventions for resolving a problem of unidentified statistical models. The leading examples are from latent variable modelling, an influential statistical tool in the social sciences. We first explain the problem of statistical identifiability and contrast it with the identifiability of causal models. We then draw a parallel between the latent variable models and Bayesian networks with hidden nodes. This allows us to clarify the use of interventions for dealing with unidentified statistical models. We end by (...) Download Export citation Bookmark 1 citation
Accommodation, prediction and replication: model selection in scale construction.Clayton Peterson - 2019 - Synthese 196 (10):4329-4350.details In psychology, measurement instruments are constructed from scales, which are obtained on the grounds of exploratory and confirmatory factor analysis. Looking at the literature, one can find various recommendations regarding how these techniques should be used during the scale construction process. Some authors suggest to use exploratory factor analysis on the entire data set while others advice to perform an internal cross-validation by randomly splitting the data set in two and then either perform exploratory factor analysis on both parts or (...) Download Export citation Bookmark 1 citation

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