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Holm Step-Down Familywise Error Control
1 · Prerequisites
- Binary Operations, Monoids, Groups and Subgroups
- Conditional Distributions and Regular Conditional Probability
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Estimators and Randomized Procedures
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- limsup, liminf, and Subsequential Limits
- Loss, Risk and Decision Theory
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Pointwise Extended-Real Function Products
- Polynomial Rings, the Division Algorithm and Roots
- Probability Spaces Random Variables and Expectation
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Sigma Algebras and Borel Sets
- Simple Field Extensions and the Construction of the Complex Numbers
- Statistical Experiments, Models and Identifiability
- Suprema and Infima
- Tests, Neyman–Pearson and Valid P-values
- The Lebesgue Integral and the Convergence Theorems
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Valid p-values, Bonferroni, simultaneous coverage
2 · Summary
This page defines Holm's step-down procedure for a finite hypothesis family fixed before observing the data, verifies that its rejection events are measurable, and proves strong familywise error control. The proof identifies the earliest-ranked true null: any false rejection forces that null's p-value below , where is the number of true nulls. Bonferroni control on the true-null subfamily then gives an error probability at most , with no independence assumption. The guarantee concerns false rejections; the procedure itself does not provide simultaneous confidence intervals. Choosing the family after seeing the p-values is outside the theorem unless validity remains established for that selection.
3 · Logical flowchart
4 · Definitions, theorems and proofs
Holm step-down procedure
Definition
For , fix a finite family of null hypotheses , , before observing the data, and let be p-value statistics valid for their respective nulls in the sense of Null-valid p-values and familywise and false-discovery error rates. Given and an observation , order the indices by the pairs in lexicographic order. This gives a unique permutation with ; ties are ordered by increasing index.
Set The rejected-index set is . Reject exactly when ; equivalently, compare sequentially to , stop at the first failed comparison, and reject only the preceding ranks.
For , extend the procedure to the empty input by returning the empty rejected set. For , every denominator in a tested rank is positive. The ordering is a unique finite permutation, and the finite set defining contains , so the output is well-defined.
Holm rejection events are measurable
Statement
Let , let be p-value statistics on a measurable data space , and fix . Define by the lexicographic ordering and passing-prefix formulas of Holm step-down procedure, applied here to these statistics whether or not they are null-valid. These formulas are well-defined for every input in : the ordering is unique, the tested denominators are positive, and the admissible prefix lengths include . Then each rejection event belongs to .
Facts & Assumptions
Given: A measurable data space, finitely many p-value statistics , and .
Valid p-values: a p-value statistic is a statistic , where carries the trace of the Borel sigma-algebra.
Statistics and estimators: a statistic is a measurable map from the data space to its target measurable space.
The ordering and prefix formulas of Holm step-down procedure order the pairs lexicographically and return the prefix whose rank cutoffs all pass. Here these formulas define on all the given measurable inputs; on null-valid inputs they agree with the cited procedure. Null validity is not needed for measurability.
Arithmetic and lattice operations preserve measurability whenever they are defined: sums and scalar multiples of measurable real-valued functions are measurable whenever defined; hence differences of measurable real-valued functions are measurable.
A measurable function between measurable spaces: a map is measurable when the preimage of each measurable target set belongs to the source sigma-algebra.
Sigma-algebras: a sigma-algebra is closed under finite intersections and finite unions.
Proof
By [F1] and [F2], each is measurable into with its Borel trace. For indices , the difference is measurable by [F4], so and are measurable preimages by [F5] of the Borel half-lines and . For each permutation , its ordering cell is the finite intersection over positions of if and otherwise. These cells are measurable by [F6], and every belongs to exactly one because lexicographic ordering with index tie-breaking gives a unique permutation by [F3]. For rank , let ; this pass event and its failure event are measurable preimages of Borel half-lines by [F1], [F2], and [F5]. For , intersect with the pass events for and, when , the failure event at . Empty intersections are omitted when or . The resulting measurable cell is exactly the event that the order is and the returned prefix length is , by [F3]; these finitely many cells partition .
The event is the union of the cells from step 1.1 over all permutations and prefix lengths with . This is a finite union because there are permutations and prefix lengths. By [F6], for every .
Holm step-down controls strong FWER
Statement
Let and let a fixed finite family of null hypotheses and valid p-value statistics be as in Null-valid p-values and familywise and false-discovery error rates. For , let be the rejected-index set from Holm step-down procedure, and let be the true-null index set defined there. By Holm rejection events are measurable, the rejection events are measurable, so the familywise error rate is well-defined as Then for every . This is strong familywise error control and requires no independence or other restriction on the joint distribution of the p-values.
Facts & Assumptions
Given: A statistical experiment, a fixed finite family with valid p-values in the sense of Null-valid p-values and familywise and false-discovery error rates, and . The Holm rejected set is the initial ordered prefix passing its step-down cutoffs.
Null-valid p-values and familywise and false-discovery error rates: for each , validity means for every and .
Null-valid p-values and familywise and false-discovery error rates: and FWER is the probability of at least one rejected true null.
Holm step-down procedure: the procedure orders p-values, compares rank with , and rejects exactly the prefix whose comparisons all pass.
Holm rejection events are measurable: each Holm rejection event is measurable, so the FWER definition in [F2] applies.
Strong familywise error control by Bonferroni: the equal-weight one-step Bonferroni rule on any fixed family of valid p-values has strong FWER at most when it rejects at cutoff , under arbitrary dependence.
Proof
Fix and put and . By [F4], the Holm rejection events are measurable, so the FWER from [F2] is defined. If , no true null can be rejected. Otherwise, let be the least rank occupied by a true null in the ordering from [F3]; it exists because is finite and nonempty. Since [F3] rejects only a prefix, any rejection of a true null forces rank to be rejected. Thus . All true nulls occur at ranks , so and . Hence any false rejection implies .
If , fix and consider the fixed subfamily indexed by ; it has members, all true under this , and it is not selected from the observed p-values. By [F1] its p-values are valid. Applying the Bonferroni theorem [F5] to this subfamily at level bounds the probability of its threshold-union event by . This contains the Holm false-rejection event from step 1.1, so . If , step 1.1 gives FWER zero. Since was arbitrary, the control is strong.
5 · Examples, counterexamples and false statements
None yet.
Sources
- Jelle J. Goeman and Aldo Solari, The sequential rejection principle of familywise error control, The Annals of Statistics 38(6) (2010), Section 3
- Gary W. Oehlert, A First Course in Design and Analysis of Experiments, Chapter 5, Sections 5.1–5.2
- John K. Hunter, Measure Theory, Definitions 3.1–3.3
- Jelle J. Goeman and Aldo Solari, The sequential rejection principle of familywise error control, The Annals of Statistics 38(6) (2010), Theorem 1 and Section 3