Heritability of Systolic Blood Pressure. Analysis of Variance in MZ Twin Parents and Their Children

1980 ◽  
Vol 29 (2) ◽  
pp. 143-149 ◽  
Author(s):  
R. J. Rose ◽  
D. W. Fulker ◽  
J. Z. Miller ◽  
C. E. Grim ◽  
J. C. Christian
Keyword(s):  
Blood Pressure ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Systolic Blood Pressure ◽  
Analysis Of Variance ◽  
Environmental Effects ◽  
Environmental Parameters ◽  
Likelihood Estimation ◽  
Age And Sex ◽  
Pressure Analysis

Systolic blood pressure, standardized for age and sex, was measured in 76 MZ twin pairs and their 341 children. Maximum likelihood estimation of genetical and environmental parameters from the independent parental and offspring ANOVAs indicated a complete absence of both maternal and shared environmental effects, together with a heritability of 63%. These results are shown to be reasonably consistent with those from previous studies.

Prevalence data—models, likelihood, and binomial regression

2020 ◽  
pp. 47-63
Author(s):  
Bendix Carstensen
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Statistical Model ◽  
Likelihood Estimation ◽  
Data Models ◽  
Epidemiological Methods ◽  
Prevalence Data ◽  
Binomial Regression ◽  
Disease Condition ◽  
Age And Sex

This chapter examines prevalence data, using a dataset which contains the number of diabetes patients and the total number of persons in Denmark as of January 1, 2010, classified by age and sex. Prevalence of a disease condition in a population is merely the proportion of affected people. The chapter uses prevalence to illustrate core modelling concepts: the model itself, the likelihood, the maximum likelihood estimation principle, and the properties of the results, all of which underlies most modern epidemiological methods. It also explains the concept of a statistical model leading to the distinction between empirical and theoretical prevalences. The chapter then focuses on the task of comparing different models for the same data, models that describe data in various degrees of detail.

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