Use of the extreme groups approach: a critical reexamination and new recommendations.

By Kristopher J Preacher, Derek D. Rucker, R. Maccallum, W. Alan Nicewander. Psychological methods, 2005

720 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e5dbb4bbb1c9889b94e631ec5127b56ab6d53bd2

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In Computer Networks and Communications

In Statistics and Probability

Citations in the corpus

Investigating the structure of semantic networks in low and high creative persons (2014, background): “However, recent objections have been raised at this method, especially when measuring continuous variables such as creative ability (Preacher et al., 2005).”
Splitting a Predictor at the Upper Quarter or Third and the Lower Quarter or Third (2009, background): “…results are not new; similar calculations have been performed by psychometricians to address the question of designing a study that will be summarized by a difference; see Kelley (1928, 1939), Cureton (1957), Feldt (1961), D’Agostino and Cureton (1975), Fowler (1992), and Preacher et al. (2005).”
An investigation of appraisals in individuals vulnerable to excessive worry: the role of intolerance of uncertainty (2008, positive): “Although it is common practice in quasi-experimental psychological research to divide individuals into groups along a specific cut-point on a scale for the purposes of comparison on the dependent variable(s), methodologists and statisticians have cautioned about the limitations of this practice (see”
It’s about Time! CEOs’ Temporal Dispositions, Temporal Leadership, and Corporate Entrepreneurship (2017, methodology): “To further clarify the differential effects of CEOs’ early-action, steady-action, and deadline-action styles on temporal leadership, we conducted subgroup analysis (HSD test) (Preacher et al., 2005).”
Do Food Image and Food Neophobia Affect Tourist Intention to Visit a Destination? The Case of Australia (2019, methodology): “…who are “clearly” food-neophobic versus novelty seekers, a broadly adopted percentile split and extreme group approach were used, splitting the overall sample (n = 500) into two subgroups based on the upper quartile (75th percentile) and the lower quartile (25th percentile) (Preacher et al. 2005).”
Examining the association between parenting and childhood anxiety: a meta-analysis. (2007, result): “However, this pattern of findings could also be explained by the tendency for “extreme-groups” designs to yield larger statistical effects than full-range correlational designs ( Preacher, Rucker, MacCallum, & Nicewander, 2005 ).”
When do job demands particularly predict burnout?: The moderating role of job resources (2007, methodology): “However, this technique can only lead to cautious conclusions regarding the standardized effect size in terms of the percentage of variance explained, as well as regarding the generalizability of the findings to the general population ( Preacher et al., 2005 ).”
Best Practices for Using Median Splits, Artificial Categorization, and their Continuous Alternatives (2011, background): “In addition, both extreme group analysis and post-hoc subgrouping have undesirable side effects, such as distorting effect sizes, reducing scale reliabilities, and making it difficult to observe nonlinear relations between variables (Preacher et al., 2005).”
Individual differences in risk-propensity: Associations between personality and behavioral measures of risk (2011, neutral): “(Preacher et al., 2005).”
Process mining techniques for analysing patterns and strategies in students’ self-regulated learning (2013, background): “In absence of prior research and knowledge about detailed expected effects, an analysis of extreme groups is a suitable approach (Preacher et al. 2005).”
Cognitive Neuroscience Approaches to Individual Differences in Working Memory and Executive Control: Conceptual and Methodological Issues (2010, methodology): “While practical considerations make it difficult to overcome many of these limitations (e.g., collecting data from much larger samples is often not viable, from a financial perspective), a number of different approaches have been used to increase detection power and/or support stronger inferences…”