genBinomialDV: Generate a binomial dependent variable
In jknowles/datasynthR: Generate synthetic data with known properties, on demand.

Description Usage Arguments Details Value Note Author(s)

Allow the user to specify a formula for generating a binomial dependent variable

1 2	genBinomialDV(df, form, errors, intercept, type = c("binary", "response"), na.rm = FALSE)

`df`	dataframe to generate the dependent variable from
`form`	A named list containing the variables in df to be used to calculate the binomial probability, and coefficients of those variables
`errors`	The way the error structure of the DGP formula should be established
`intercept`	An adjustment to the base probability
`type`	Indicate whether the binary response is desired or the probability
`na.rm`	a logical indicating whether to fit the distribution excluding missing values or to fail on missing values

Coefficients needs to be long enough to incorporate the factor levels

A binomial vector by a formula generated out of the elements of form

Yadda yadda yadda

Currently it can be easy for the user to build a formula that results in all 0 or 1 results. Use intercept to adjust accordingly. Additionally, coefficient scales don't make sense at the moment. Still need to add the ability to have confounders in place.

Jared E. Knowles

jknowles/datasynthR documentation built on May 19, 2019, 11:42 a.m.