Bayesian Statistical Inference for Psychological Research

By J. Weiss, David J. Weiss. 2008

601 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/c330e4cb0b522d912f8ab0cc56e91de4ccb69275

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In Experimental and Cognitive Psychology

Citations in the corpus

Bayes factor design analysis: Planning for compelling evidence (2016, background): “The consistency property ensures that BFs ultimately drift either towards 0 or towards ∞ and every study ends up producing compelling evidence – unless researchers run out of time, money, or participants (Edwards et al., 1963).”
Bayesian benefits with JASP (2017, unknown): “…to monitor the evidence as the data accumulate, for example in the form of a Bayes factor or a posterior distribution (e.g. Berger & Berry, 1988; Edwards, Lindman, & Savage, 1963; Kadane, Schervish, & Seidenfeld, 1996; Rouder, 2014; Schönbrodt et al., in press; Wagenmakers, Wetzels, Borsboom,…”
Surrogate Science (2015, background): “A cornerstone of that resurrection is Edwards, Lindman, and Savage’s (1963) Psychological Review article.”
Default Bayes factors for ANOVA designs (2012, background): “Yet, it has a subtle but pervasive implication that is often overlooked: significance tests overstate the case against the null (Berger & Berry, 1988; Edwards et al., 1963; Wagenmakers, 2007).”
Bayesian Analysis of Factorial Designs (2017, background): “Interested readers are referred to Berger and Berry (1988), Edwards, Lindman, and Savage (1963), Efron (2005), Gelman, Shor, Bafumi, and Park (2007), Jaynes (2003), Kruschke (2011), and Wagenmakers (2007) among others.”
Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations (2016, background): “…P -values against certain quantities (likelihood ratios and Bayes factors) that play a central role as evidence measures in Bayesian analysis (Edwards et al. 1963; Berger and Sellke 1987; Edwards 1992; Goodman and Royall 1988; Royall 1997; Sellke et al. 2001; Goodman 1992, 2005; Wagenmakers…”
Significance tests as sorcery: Science is empirical—significance tests are not (2012, background): “There is no substitute for what Edwards, Lindman, and Savage (1963), in their classic article, call the “interocular traumatic test,” which is when a relationship hits you right between the eyes.”
A practical solution to the pervasive problems ofp values (2007, background): “For more detailed introductions to Bayesian inference, see, for instance, Berger (1985), Bernardo and Smith (1994), W. Edwards et al. (1963), Gill (2002), Jaynes (2003), P. M. Lee (1989), and O’Hagan and Forster (2004).”
How the Maximal Evidence of P-Values Against Point Null Hypotheses Depends on Sample Size (2016, methodology): “For the class of normal priors on θ under H1, centered around θ0, the corresponding minimum Bayes factor is minBF(p) = {√ z exp(−z/2)√e for z = z(p) > 1 1 otherwise, (3) (see Edwards et al. 1963; Berger and Sellke 1987).”
When did Bayesian inference become "Bayesian"? (2006, background): “Savage’s introductory essay introduced many of the themes of modern Bayesian analysis including the role of the likelihood principle and the principle of “precise measurement” explored further in Edwards, Lindman and Savage (52).”
What Are the Odds? A Practical Guide to Computing and Reporting Bayes Factors (2014, background): “Several papers (Edwards et al., 1963; Gallistel, 2009; Gigerenzer, 1998; Myung & Pitt, 1997) discuss how obtaining a value beyond some threshold is not the point of the analysis, and suggest that one of the inherent problems with NHST is that it allows analysis without throughtful reflection on alte”
Statistical Inference (2003, unknown): “29 3.2.1 The Gamma Distributions . . . . . . . . . . . . . . . 30 3.2.2 The Chi-squared Distribution . . . . . . . . . . . . . 30 3.3 Sampling from a Normal Population . . . . . . . . . . . . . 31 3.4 The t-Distribution . . . . . . . . . . . . . . . . . . . . . . . 32 3.5 Confidence Intervals . . .…”
How cognitive modeling can benefit from hierarchical Bayesian models. (2011, methodology): “Calls for change, noting the clear superiority of Bayesian methods, date back at least to the seminal paper of Edwards, Lindman, and Savage (1963), and have grown more frequent and assertive in the past few years (e.g., Gallistel, 2009; Kruschke, 2010a; Lee & Wagenmakers, 2005; Wagenmakers, 2007).”
Herbert Simon's Decision-Making Approach: Investigation of Cognitive Processes in Experts (2010, background): “, Epstein, 1994; Sloman, 1996; Chaiken & Trope, 1999; Kahneman & Frederick, 2002; Stanovich & West, 2000). Note that some theorists propose that there are two types of processes instead of two subsystems (e.g., Evans, 2008). The dual-system models were criticized (see Keren & Schul, 2009; Gigerenzer”