Published in Behavior Research Methods
Growth mixture models (GMMs) are prevalent for modeling unknown population heterogeneity via distinct latent classes. However, GMMs are riddled with convergence issues, often requiring researchers to atheoretically alter the model with cross-class constraints simply to obtain convergence. We discuss how within-class random effects in GMMs exacerbat...
Published in Behavior Research Methods
In social and behavioral sciences, data are typically not normally distributed, which can invalidate hypothesis testing and lead to unreliable results when being analyzed by methods developed for normal data. The existing methods of generating multivariate non-normal data typically create data according to specific univariate marginal measures such...
Published in Behavior research methods
Lexical-gustatory (LG) synesthesia is an intriguing neurological condition in which individuals experience phantom tastes when hearing, speaking, reading, or thinking about words. For example, the word "society" might flood the mouth of an LG synesthete with the flavor of fried onion. The condition is usually verified in individuals by obtaining ve...
Published in Behavior Research Methods
Best–worst scaling is a judgment format in which participants are presented with K items and must choose the best and worst items from that set, along some underlying latent dimension. Best–worst scaling has seen recent use in natural-language processing and psychology to collect lexical semantic norms. In such applications, four items have always ...
Published in Behavior Research Methods
We describe a sequential qualitative ➔ quantitative mixed-method procedure used to construct conceptually grounded quantitative metrics of interpersonal behavior from continuous spatiotemporal data. Metrics were developed from data collected during an experiment in which racially diverse participants interacted with self-resembling avatars at socia...
Published in Behavior Research Methods
This paper introduces the R package WRS2 that implements various robust statistical methods. It elaborates on the basics of robust statistics by introducing robust location, dispersion, and correlation measures. The location and dispersion measures are then used in robust variants of independent and dependent samples t tests and ANOVA, including be...
Published in Behavior Research Methods
Nonparametric multiple comparisons are a powerful statistical inference tool in psychological studies. In this paper, we review a rank-based nonparametric multiple contrast test procedure (MCTP) and propose an improvement by allowing the procedure to accommodate various effect sizes. In the review, we describe relative effects and show how utilizin...
Published in Behavior research methods
The decision process in choice reaction time data is traditionally described in detail with diffusion models. However, the total reaction time is assumed to consist of the sum of a decision time (as modeled by the diffusion process) and the time devoted to nondecision processes (e.g., perceptual and motor processes). It has become standard practice...
Published in Behavior research methods
In the analysis of clustered or hierarchical data, a variety of statistical techniques can be applied. Most of these techniques have assumptions that are crucial to the validity of their outcome. Mixed models rely on the correct specification of the random effects structure. Generalized estimating equations are most efficient when the working corre...
Published in Behavior research methods
There is increasing evidence that hand gestures and speech synchronize their activity on multiple dimensions and timescales. For example, gesture's kinematic peaks (e.g., maximum speed) are coupled with prosodic markers in speech. Such coupling operates on very short timescales at the level of syllables (200 ms), and therefore requires high-resolut...
