Based on the observation that frequentist confidence intervals and Bayesian credible intervals sometimes happen to have the same numerical boundaries (under very specific conditions), Albers et al. (2018) proposed to adopt the heuristic according to which they can usually be treated as equivalent. We argue that this heuristic can be misleading by showing that it does not generalise well to more complex (realistic) situations and models. Instead of pragmatism, we advocate for the use of parsimony in deciding which statistics to report. In a word, we recommend that a researcher interested in the Bayesian interpretation simply reports credible intervals
It is shown that all the Frequentist methods are equivalent from astatistical point of view, but the...
Scientists and Bayesian statisticians often study hypotheses that they know to be false. This create...
Interval estimates – estimates of parameters that include an allowance for sampling uncertainty – ha...
Based on the observation that frequentist confidence intervals and Bayesian credible intervals somet...
Based on the observation that frequentist confidence intervals and Bayesian credible intervals somet...
The debate between Bayesians and frequentist statisticians has been going on for decades. Whilst the...
I agree with Rob Kass’ point that we can and should make use of statistical methods developed under ...
The debate between Bayesians and frequentist statisticians has been going on for decades. Whilst the...
Tomorrow, for the final lecture of the Mathematical Statistics course, I will try to illustrate - us...
We marshall the arguments for preferring Bayesian hypothesis testing and confidence sets to frequent...
‘The fallacy of placing confidence in confidence intervals’ (Morey et al., 2016, Psychonomic Bulleti...
In frequentist statistics, point-null hypothesis testing based on significance tests and confidence ...
It is well known that one of the conflicts between Bayesian and frequentist approach to inference li...
Frequentist confidence intervals were compared with Bayesian credible intervals under a variety of s...
Interval estimates – estimates of parameters that include an allowance for sampling uncertainty – ha...
It is shown that all the Frequentist methods are equivalent from astatistical point of view, but the...
Scientists and Bayesian statisticians often study hypotheses that they know to be false. This create...
Interval estimates – estimates of parameters that include an allowance for sampling uncertainty – ha...
Based on the observation that frequentist confidence intervals and Bayesian credible intervals somet...
Based on the observation that frequentist confidence intervals and Bayesian credible intervals somet...
The debate between Bayesians and frequentist statisticians has been going on for decades. Whilst the...
I agree with Rob Kass’ point that we can and should make use of statistical methods developed under ...
The debate between Bayesians and frequentist statisticians has been going on for decades. Whilst the...
Tomorrow, for the final lecture of the Mathematical Statistics course, I will try to illustrate - us...
We marshall the arguments for preferring Bayesian hypothesis testing and confidence sets to frequent...
‘The fallacy of placing confidence in confidence intervals’ (Morey et al., 2016, Psychonomic Bulleti...
In frequentist statistics, point-null hypothesis testing based on significance tests and confidence ...
It is well known that one of the conflicts between Bayesian and frequentist approach to inference li...
Frequentist confidence intervals were compared with Bayesian credible intervals under a variety of s...
Interval estimates – estimates of parameters that include an allowance for sampling uncertainty – ha...
It is shown that all the Frequentist methods are equivalent from astatistical point of view, but the...
Scientists and Bayesian statisticians often study hypotheses that they know to be false. This create...
Interval estimates – estimates of parameters that include an allowance for sampling uncertainty – ha...