Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Effects of implicit parameters in segregation analysis.

J J Tai1, C K Hsiao

  • 1Division of Biostatistics, Institute of Epidemiology, National Taiwan University, Taipei, Taiwan, ROC.

Human Heredity
|April 5, 2001
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Association of older paternal age with earlier onset among co-affected schizophrenia sib-pairs.

Psychological medicine·2015
Same author

Akt1 deficiency modulates reward learning and reward prediction error in mice.

Genes, brain, and behavior·2011
Same author

Item analysis for the written test of Taiwanese board certification examination in anaesthesiology using the Rasch model.

British journal of anaesthesia·2010
Same author

Robust quantitative trait association tests in the parent-offspring triad design: conditional likelihood-based approaches.

Annals of human genetics·2009
Same author

The effect of metabolic risk factors on the natural course of gastro-oesophageal reflux disease.

Gut·2008
Same author

A Bayesian spatial multimarker genetic random-effect model for fine-scale mapping.

Annals of human genetics·2008
Same journal

Comparative profiles of pediatric Mendeliome: A Single-Centre 572-Whole-Exome Sequencing Study in Xinjiang.

Human heredity·2026
Same journal

Erratum.

Human heredity·2026
Same journal

Exploratory Analysis of HMGB1 Genetic Variants and Their Potential Association with Lung Cancer Susceptibility and Chemotherapy Response in a Chinese Population.

Human heredity·2025
Same journal

Weighted Burden Analysis of Rare Genetic Variants Identifies Novel Genes with Effects on BMI.

Human heredity·2025
Same journal

Generalized Stable Population and Agent-Based Models of Phenotypic Transmission in Human Populations, with an Application to Body Size.

Human heredity·2025
Same journal

Proteinase-activated receptor 2 (PAR-2) expression and F2RL1 genetic variants are associated with asthma: a case-control study in the Chinese population.

Human heredity·2025
See all related articles

Human genetic analysis using ascertainment procedures can lead to biased estimations due to nonrandom sampling. This study identifies information loss from implicit parameters as the cause, proposing new likelihood approaches for segregation ratio estimation.

Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Human genetic analysis relies on ascertainment procedures, a multistage, nonrandom sampling method.
  • This sampling can introduce intractable bias in statistical estimations.
  • Understanding the causes of this bias is crucial for accurate genetic data analysis.

Purpose of the Study:

  • To investigate the underlying causes of the intractability problem in ascertained genetic data.
  • To define and classify parameters (target, design, nuisance; explicit, implicit) essential for likelihood formulation.
  • To propose methods for likelihood estimation of the segregation ratio with observed pedigree structures.

Main Methods:

  • Defined target, design, and nuisance parameters for likelihood formulation.

Related Experiment Videos

  • Classified parameters as explicit or implicit based on their representation in the likelihood function.
  • Identified sequential sampling and true pedigree structure as implicit parameters causing information loss.

    • Main Results:

    • The intractability of ascertained genetic data stems from the loss of information associated with implicit parameters.
    • Implicit design parameters (sequential sampling) and implicit nuisance parameters (pedigree structure) contribute to estimation bias.
    • Proposed novel approaches to construct likelihood functions for segregation ratio estimation.

    Conclusions:

    • The nonrandom nature of ascertainment procedures in human genetics leads to intractable bias.
    • Information loss from implicit parameters is the primary cause of this bias.
    • The proposed methods offer solutions for accurate segregation ratio estimation using observed pedigree data.