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Reanalysis of CVD Risk Factors Via Likelihood Methods

Primary Purpose

Cardiovascular Diseases, Heart Diseases, Atherosclerosis

Status
Completed
Phase
Locations
Study Type
Observational
Intervention
Sponsored by
National Heart, Lung, and Blood Institute (NHLBI)
About
Eligibility
Locations
Outcomes
Full info

About this trial

This is an observational trial for Cardiovascular Diseases

Eligibility Criteria

undefined - 100 Years (Child, Adult, Older Adult)MaleDoes not accept healthy volunteers

No eligibility criteria

Sites / Locations

    Outcomes

    Primary Outcome Measures

    Secondary Outcome Measures

    Full Information

    First Posted
    May 25, 2000
    Last Updated
    March 15, 2016
    Sponsor
    National Heart, Lung, and Blood Institute (NHLBI)
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    1. Study Identification

    Unique Protocol Identification Number
    NCT00005408
    Brief Title
    Reanalysis of CVD Risk Factors Via Likelihood Methods
    Study Type
    Observational

    2. Study Status

    Record Verification Date
    May 2000
    Overall Recruitment Status
    Completed
    Study Start Date
    July 1992 (undefined)
    Primary Completion Date
    undefined (undefined)
    Study Completion Date
    April 1994 (Actual)

    3. Sponsor/Collaborators

    Name of the Sponsor
    National Heart, Lung, and Blood Institute (NHLBI)

    4. Oversight

    5. Study Description

    Brief Summary
    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.
    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.

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Cardiovascular Diseases, Heart Diseases, Atherosclerosis

    7. Study Design

    10. Eligibility

    Sex
    Male
    Maximum Age & Unit of Time
    100 Years
    Accepts Healthy Volunteers
    No
    Eligibility Criteria
    No eligibility criteria

    12. IPD Sharing Statement

    Citations:
    PubMed Identifier
    8314059
    Citation
    Williams CJ, Wijesiri UW. Lipid data from NHLBI veteran twins: interpreting genetic analyses when model assumptions fail. Genet Epidemiol. 1993;10(6):551-6. doi: 10.1002/gepi.1370100637.
    Results Reference
    background
    PubMed Identifier
    8369388
    Citation
    Williams CJ. On the covariance between parameter estimates in models of twin data. Biometrics. 1993 Jun;49(2):557-68.
    Results Reference
    background
    PubMed Identifier
    7598664
    Citation
    Wijesiri UW, Williams CJ. Approximate solutions for the maximum-likelihood estimates in models of univariate human twin data. Behav Genet. 1995 May;25(3):211-6. doi: 10.1007/BF02197179. Erratum In: Behav Genet 1997 Jan;27(1):83.
    Results Reference
    background

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    Reanalysis of CVD Risk Factors Via Likelihood Methods

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