BACKGROUND: Molecular epidemiological studies of aging and longevity are focused on evaluating the effects of single genes on susceptibility to disease and death. The effects of all genetic factors on susceptibility can be evaluated from the analysis of survival data on related individuals. METHOD: The analyses of survival data on Danish monozygotic (MZ) and dizygotic (DZ) twins are performed using gamma, inverse Gaussian and three-parameter correlated frailty models. The semiparametric representations of the respective models are used to obtain maximum likelihood estimates of model parameters. The results are compared using the likelihood ratio test. RESULTS: The survival of Danish MZ and DZ twins can be characterised by the same marginal hazards and identical univariate frailty distributions for any of the three frailty models. In all three cases the genetic influence on frailty is statistically significant. CONCLUSION: All three models can be used to study genetic effects on susceptibility. The gamma and inverse Gaussian frailty models fit the Danish twin data equally well. Our analyses show that for the Danish twin data these two models are preferable to the three-parameter model.
BACKGROUND: Molecular epidemiological studies of aging and longevity are focused on evaluating the effects of single genes on susceptibility to disease and death. The effects of all genetic factors on susceptibility can be evaluated from the analysis of survival data on related individuals. METHOD: The analyses of survival data on Danish monozygotic (MZ) and dizygotic (DZ) twins are performed using gamma, inverse Gaussian and three-parameter correlated frailty models. The semiparametric representations of the respective models are used to obtain maximum likelihood estimates of model parameters. The results are compared using the likelihood ratio test. RESULTS: The survival of Danish MZ and DZ twins can be characterised by the same marginal hazards and identical univariate frailty distributions for any of the three frailty models. In all three cases the genetic influence on frailty is statistically significant. CONCLUSION: All three models can be used to study genetic effects on susceptibility. The gamma and inverse Gaussian frailty models fit the Danish twin data equally well. Our analyses show that for the Danish twin data these two models are preferable to the three-parameter model.