Evidence map›Paper›PMID 27418716›Full record

ArticleSequential analysis

Generalized Sequential Probability Ratio Test for Separate Families of Hypotheses.

Xiaoou Li, Jingchen Liu, Zhiliang Ying

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sequential analysis. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xiaoou LiDepartment of Statistics, Columbia University, New York, NY 10027, USA.
Jingchen LiuDepartment of Statistics, Columbia University, New York, NY 10027, USA.
Zhiliang YingDepartment of Statistics, Columbia University, New York, NY 10027, USA.

Funding

STATISTICAL METHODS IN CURRENT CANCER RESEARCHR01CA082659 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIN, DANYU · 2000 to 2016
$3.7M
Semiparametric Regression Analysis of Censored DataR37GM047845 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIN, DANYU · 2005 to 2014
$3.3M
NCI NIH HHS R01 CA082659NIGMS NIH HHS R37 GM047845
6 · The paper itself

Abstract

In this paper, we consider the problem of testing two separate families of hypotheses via a generalization of the sequential probability ratio test. In particular, the generalized likelihood ratio statistic is considered and the stopping rule is the first boundary crossing of the generalized likelihood ratio statistic. We show that this sequential test is asymptotically optimal in the sense that it achieves asymptotically the shortest expected sample size as the maximal type I and type II error probabilities tend to zero.

Indexed as

boundary crossinggeneralized likelihood ratio testsequential testtesting separate families of hypotheses

Identifiers

PMID27418716
PMCPMC4941833

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.