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Reanalysis of CVD Risk Factors Via Likelihood Methods

This study has been completed.
Sponsor:
ClinicalTrials.gov Identifier:
NCT00005408
First Posted: May 26, 2000
Last Update Posted: March 16, 2016
The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.
Information provided by:
National Heart, Lung, and Blood Institute (NHLBI)
  Purpose
To reanalyze data on risk factors for cardiovascular disease (CVD) including total cholesterol and high density lipoprotein (HDL) cholesterol for the subjects in the first, second, and third exams of the NHLBI Twin Study.

Condition
Cardiovascular Diseases Heart Diseases Atherosclerosis

Study Type: Observational

Further study details as provided by National Heart, Lung, and Blood Institute (NHLBI):

Study Start Date: July 1992
Study Completion Date: April 1994
Detailed Description:

BACKGROUND:

The results of these longitudinal analyses yielded new insights on genetic effects affecting CVD risk factors during the aging process.

DESIGN NARRATIVE:

The analyses utilized maximum likelihood estimators of genetic variance which were asymptotically more efficient than the method-of-moments estimators used in previous analyses. The models used incorporated terms to partition the variance in a trait from twin data into either i) additive genetic variance and unshared environmental variance (the AE model), ii) additive genetic variance, dominance genetic variance, and unshared environmental variance (the ADE model), or iii) additive genetic variance, shared environmental variance, and unshared environmental variance (the ACE model). The AE, ADE, and ACE models were fitted separately to data from each of the three exams to obtain a cross-sectional analysis. The investigators also extended these models for use with longitudinal data by incorporating terms to represent the covariance of variance components from different exams.

Two important additional objectives of this study were i) to introduce resistant estimation techniques in twin modeling, which trimmed the effect of outlier data points smoothly, and ii) to carefully study the performance of maximum likelihood and method-of-moments estimators when assumptions of the twin model were violated. The results of these parts of the study should yield a more complete understanding of the relative merits and limitations of twin modeling procedures.

The study completion date listed in this record was obtained from the "End Date" entered in the Protocol Registration and Results System (PRS) record.

  Eligibility

Information from the National Library of Medicine

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Ages Eligible for Study:   up to 100 Years   (Child, Adult, Senior)
Sexes Eligible for Study:   Male
Accepts Healthy Volunteers:   No
Criteria
No eligibility criteria
  Contacts and Locations
No Contacts or Locations Provided
  More Information