Description Usage Arguments Details Value Author(s) References See Also Examples
Regression models to test whether the intrapair phenotypic differences are due to factors that are identical for both co-twins (i.e., a genotype). It is based on the work on "variability genes", by Berg, K. (1994).
1 |
formula |
an object of class |
regression |
the type of regression model to be fitted. Use either |
data |
a data frame containing the variables in the model. |
... |
additional arguments to be passed to either |
Inspired by the "variability gene" concept by Berg, K. (1994), these regression models (linear and logistic) allow determining whether a pair-level variable (i.e., a genotype, which is identical for both co-twins). Further usage details are explained by Cordova-Palomera, A. et al. (2014).
abs_dif
returns an object of class
"rms", along with either c("ols", "lm") (linear models) or c("lrm", "glm") (logistic models).
Inspired by Berg (1994). Developed by Aldo Cordova-Palomera. See Cordova-Palomera et al. (2014).
Berg, K. (1994). Gene-environment interaction: variability gene concept. In Genetic factors in coronary heart disease (pp. 373-383). Springer Netherlands.
Cordova-Palomera, A., Fatjo-Vilas, M., Kebir, O., Gasto, C., Krebs, M. O., & Fananas, L. (2014). Polymorphic variation in the epigenetic gene DNMT3B modulates the environmental impact on cognitive ability: A twin study. European Psychiatry.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | data(flu_weight)
# The linear regression below tests whether the intrapair differences in
# DNA methylation (outcome) depend on pair-specific variables such as gender,
# age or both.
# The conceptual justification of the working hypothesis is partly inspired
# by Fraga, M. F., et al. (2005) Proceedings of the National Academy of
# Sciences of the United States of America, 102(30), 10604-10609.
(variability_linear <- abs_dif(DNAmeth ~ Gender + Age, data=flu_weight, regression='linear'))
# The logistic regression below tests whether or not there was an
# increased/decreased rate of phenotypic differences in flu liability during
# childhood in males, compared with females.
# Namely, it evaluates there were more intrapair differences in flu liability
# in one of the genders (male or female).
(variability_logistic <- abs_dif(FluChild ~ Gender, data=flu_weight, regression='logistic'))
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