Bayesian methods for data analysis.
By Bradley P. Carlin, T. Louis, Boca Raton. American journal of ophthalmology-glaucoma, 2010
519 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/46988994191259834cbf32d842e9a8e21c90f53d
Citations in the corpus
- The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective (2017, unknown): “…of clinical equivalence,” “range of equivalence,” “equivalence interval,” “indifference zone,” “smallest effect size of interest,” and “good-enough belt” (e.g. Carlin & Louis, 2009; Freedman, Lowe, & Macaskill, 1984; Hobbs & Carlin, 2008; Lakens, 2014; Schuirmann, 1987; Serlin & Lapsley, 1985,…”
- Automatic Guide Generation for Stan via NumPyro (2021, unknown): “The Stan probabilistic language [Carpenter et al. 2017] enjoys broad adoption by the statistics and social sciences communities [Carlin and Louis 2008; Gelman and Hill 2006; Gelman et al. 2013].”
- Bayesian estimation supersedes the t test. (2013, unknown): “The use of a ROPE is described further by Kruschke (2011a, 2011b), and in additional settings by Carlin and Louis (2009), Freedman, Lowe, and Macaskill (1984), Hobbs and Carlin (2008), and Spiegelhalter, Freedman, and Parmar (1994).”
- Rejecting or Accepting Parameter Values in Bayesian Estimation (2018, unknown): “…indifference zone, range of equivalence, equivalence margin, margin of noninferiority, smallest effect size of interest, and good-enough belt (e.g., Carlin & Louis, 2009; Freedman, Lowe, & Macaskill, 1984; Hobbs & Carlin, 2008; Lakens, 2014, 2017; Serlin & Lapsley, 1985, 1993; Spiegelhalter,…”
- Improving Transparency and Replication in Bayesian Statistics: The WAMBS-Checklist (2017, unknown): “For a full introduction to Bayesian modeling, we refer the novice reader to, among many others: Bolstad (2007); Carlin and Louis (2009); Christensen, Johnson, Branscum, and Hanson (2010); Depaoli and Boyajian, (2014); Gelman and Hill (2007); Kaplan, 2014; Kruschke (2010); Jackman (2009); Lynch…”
- Compiling Stan to generative probabilistic languages and extension to deep probabilistic programming (2021, unknown): “These languages enjoy broad adoption by the statistics and social sciences communities [6, 10, 11].”
- Least Squares Estimation Without Priors or Supervision (2011, unknown): “This form is particularly useful in cases where it proves difficult to develop a stable nonparametric approximation of the ratio in equation 3.5 (Carlin & Louis, 2009).”