Blog Archives

Quick Example of Latent Profile Analysis in R

April 19, 2019
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Quick Example of Latent Profile Analysis in R

Latent Profile Analysis (LPA) tries to identify clusters of individuals (i.e., latent profiles) based on responses to a series of continuous variables (i.e., indicators). LPA assumes that there are unobserved latent profiles that generate patterns of responses on indicator items. Here, I will go through a quick example of LPA to identify groups of people based on their interests/hobbies. The...

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Network Analysis of Emotions

March 17, 2019
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Network Analysis of Emotions

In this month’s post, I set out to create a visual network of emotions. Emotion Dynamics tells us that different emotions are highly interconnected, such that one emotion morphs into another and so on. I’ll be using a large dataset from an original study published in PLOS ONE by Trampe, Quoidbach, and Taquet (2015). Thanks to Google Dataset Search,...

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The Face of (Dis)Agreement – Intraclass Correlations

February 3, 2019
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The Face of (Dis)Agreement – Intraclass Correlations

I was recently introduced to Google Dataset Search, an extension that searches for open access datasets. There I stumbled upon this dataset on childrens’ and adult’s ratings of facial expressions. The data comes from a published article by Vesker et al. (2018). Briefly, this study involved having adults and 9-year-old children rate a series of 48 faces on two...

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Plotting the Affect Circumplex in R

January 14, 2019
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Plotting the Affect Circumplex in R

I’m a strong adherent to the circumplex model of emotions introduced by James Russell in the late 1980s. Russell argued that all emotional experience can be boiled down to two dimensions: valence and arousal, with valence being how positive or negative you feel and arousal being how sluggish or emotionally activated you feel. The emotions we commonly label as...

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A New Way to Handle Multivariate Outliers

January 9, 2019
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A New Way to Handle Multivariate Outliers

Psychologists often have a standoffish attitude toward outliers. Developmental psychologists, in particular, seem uncomfortable with removing cases because of the challenges inherent in obtaining data in the first place. However, the process of identifying and (sometimes) removing outliers is not a witch hunt to cleanse datasets of “weird” cases; rather, dealing with outliers is an important step toward solid,...

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