The partitioning principle: a powerful tool in multiple decision theory
From MaRDI portal
Publication:1848971
DOI10.1214/aos/1031689023zbMath1029.62064OpenAlexW2068393255MaRDI QIDQ1848971
Klaus Strassburger, Helmut Finner
Publication date: 14 November 2002
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.aos/1031689023
multiple comparisonsdirectional errorsmultiple levelsformal closure principlestrong and weak multiple partitioning principles
Parametric hypothesis testing (62F03) Statistical decision theory (62C99) Statistical ranking and selection procedures (62F07) Paired and multiple comparisons; multiple testing (62J15)
Related Items (36)
A new user specific multiple testing method for business applications: the SiMaFlex procedure ⋮ Partitioning principle and selection of good treatments ⋮ A Bayesian decision-theoretic approach to logically-consistent hypothesis testing ⋮ Using the partitioning principle to construct confidence sets for the location of a disease gene ⋮ Identification of minimum effective dose based on ratio of a normally distributed data under heteroscedasticity ⋮ A stepwise procedure for toxicity studies based on ratio of two means ⋮ Simultaneous confidence regions for closed tests, including Holm-, Hochberg-, and Hommel-related procedures ⋮ Empirical likelihood based tests for stochastic ordering under right censorship ⋮ A new approach to address multiplicity in hypothesis testing with constraints ⋮ Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard ⋮ Shelf-life and its estimation in drug stability studies ⋮ The sequential rejection principle of familywise error control ⋮ Inference for the Dimension of a Regression Relationship Using Pseudo-Covariates ⋮ Interpreting tests of a hypothesis at multiple alpha levels within a Neyman-Pearson framework ⋮ On stepwise control of the generalized familywise error rate ⋮ Uniformly most powerful tests for simultaneously detecting a treatment effect in the overall population and at least one subpopulation ⋮ Hypothesis testing for arbitrary bounds ⋮ Rank verification for exponential families ⋮ Nonparametric testing for multiple survival functions with noninferiority margins ⋮ Tree based diagnostic procedures following a smooth test of goodness-of-fit ⋮ Testing for order among K populations: theory and examples ⋮ Partition testing in confirmatory adaptive designs with structured objectives ⋮ On hypothesis testing with a partitioned random alternative ⋮ Biostatistical assessment of mutagenicity studies: a stepwise confidence procedure ⋮ Multiple Comparisons with the Best Control in a One-Way Layout ⋮ Decision theory results for one-sided multiple comparison procedures ⋮ Ordered Multiple Comparisons with the Best and Their Applications to Dose–Response Studies ⋮ Rejoinder ⋮ Only closed testing procedures are admissible for controlling false discovery proportions ⋮ Basic ideas and concepts for multiple comparison procedures ⋮ General solutions to consistency problems in multiple hypothesis testing ⋮ Simultaneous confidence intervals for ranks using the partitioning principle ⋮ Logical and test consistency in pairwise multiple comparisons ⋮ Some aspects of response variable selection and estimation in multivariate linear regression ⋮ Closure properties of classes of multiple testing procedures ⋮ Testing is confidence estimation: partition multiple testing
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Control of directional errors with stagewise multiple test procedures
- Stepwise multiple comparisons with the best
- Closed subset selection procedures for selecting good populations
- Two-sided tests and one-sided confidence bounds
- Stepwise multiple test procedures and control of directional errors
- Duality between multiple testing and selecting
- Combining the advantages of one-sided and two-sided procedures for comparing several treatments with a control
- Multiple Comparisons
- A Theory of some Multiple Decision Problems, I
- A Theory of Some Multiple Decision Problems. II
- Some selection rules for comparing p processes with a standard
- On closed testing procedures with special reference to ordered analysis of variance
- Some subset selection problems
- On the Relationship Between Stepwise Decision Procedures and Confidence Sets
- Combining the Advantages of One-Sided and Two-Sided Test Procedures for Comparing Several Treatment Effects
- D-optimality of complete latin squares
- Simultaneous Test Procedures--Some Theory of Multiple Comparisons
- THE DISTRIBUTION OF RANGE IN SAMPLES FROM A NORMAL POPULATION, EXPRESSED IN TERMS OF AN INDEPENDENT ESTIMATE OF STANDARD DEVIATION
- Some recent developments in analysis of variance
This page was built for publication: The partitioning principle: a powerful tool in multiple decision theory
