abs_dif: Test for intrapair phenotypic differences based on pair-level...

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/abs_dif.R

Description

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).

Usage

1
abs_dif(formula, regression = "linear", data, ...)

Arguments

formula

an object of class formula (or one that can be coerced to that class): a symbolic description of the model to be fitted. See formula.

regression

the type of regression model to be fitted. Use either 'linear' (default) or 'logistic'.

data

a data frame containing the variables in the model.

...

additional arguments to be passed to either ols (linear regression) or lrm (logistic model), from the rms package.

Details

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).

Value

abs_dif returns an object of class "rms", along with either c("ols", "lm") (linear models) or c("lrm", "glm") (logistic models).

Author(s)

Inspired by Berg (1994). Developed by Aldo Cordova-Palomera. See Cordova-Palomera et al. (2014).

References

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.

See Also

rms, ols, lrm

Examples

 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'))

AldoCP/mztwinreg documentation built on May 5, 2019, 1:36 p.m.