## Abstract Previous analysis of affection status in parents and siblings of 117 probands with panic disorder by a logβlinear model for binary pedigree data found a common concordance across biological firstβdegree relatives and no spouse association [Hopper JL, Judd FK, Derrick PL, Burrows GD: __G
Modelling sibship environment in the regressive logistic model for familial disease
β Scribed by Dr. John L. Hopper
- Publisher
- John Wiley and Sons
- Year
- 1989
- Tongue
- English
- Weight
- 389 KB
- Volume
- 6
- Category
- Article
- ISSN
- 0741-0395
No coin nor oath required. For personal study only.
β¦ Synopsis
Recently analytical models for pedigree disease data have been developed that combine genetic and epidemiological modelling techniques. The regressive logistic model [Bonney, Biometrics 42:611-625; 19861 relies on decomposing the likelihood of a pedigree into the product of conditional probabilities, one for each individual, by imposing a (natural) order on pedigree members. In addition to modelling measured epidemiological variables, vertical transmission, transmission of unmeasured ousiotypes (a special case being genotypes), and some modelling of sibship dependencies have been proposed. In this paper the model is extended to include an unmeasured sibship environment factor using a log-linear model for binary pedigree traits [Hopper et al., Genet Epidemiol 1: 183-188; 19841, which breaks the pedigree into conditionally independent groups. Statistical issues, such as designs for which these factors will be discernible and tests of fit, are discussed.
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For diseases with a genetic component, logistic regression models are presented that incorporate family history in a quantitative way. In the largest model, every type of relative has their own regression coefficient. The other two models are submodels, which incorporate family history either by the
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