A better stopping rule for conventional statistical tests

A stopping rule for symbolic dynamic filtering

One of the key issues in symbolic dynamic filtering (SDF) is how to obtain a lower bound on the length of symbol blocks for computing the state probability vectors of probabilistic finite-state automata (PFSA). Having specified an absolute error bound at a confidence level, this short work formulates a stopping rule by making use of Markov chain Monte Carlo (MCMC) computations. © 2010 Elsevier ...

A Metacognitive Stopping Rule for Problem Solving

Although people expect to improve by investing effort in solving a problem, several studies have found negative timeconfidence correlations in various problem-solving tasks. The present study employed the metacognitive approach to illuminate why, despite lengthy thinking, people provide solutions in which they have only low confidence. According to the proposed Diminishing Criterion Model (DCM)...

A new stopping rule for surveys.

Non-response is a problem for most surveys. In the sample design, non-response is often dealt with by setting a target response rate and inflating the sample size so that the desired number of interviews is reached. The decision to stop data collection is based largely on meeting the target response rate. A recent article by Rao, Glickman, and Glynn (RGG) suggests rules for stopping that are ba...

Part III: Statistical Tests on the WJP Rule of Law Index Statistical Tests on the WJP Rule of Law Index

normality tests for statistical analysis: a guide for non-statisticians

statistical errors are common in scientific literature and about 50% of the published articles have at least one error. the assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. the aim of this commentary is to overview checking for normality in statistical analysis using spss.