Synthesis by linear regression after transformation of a dependent variable

Generates univariate synthetic data using linear regression of an outcome variable transformed by natural logarithm (lognorm), square root (sqrtnorm) or cube root (cubertnorm).

Usage

syn.lognorm(y, x, xp, proper = FALSE, ...)
syn.sqrtnorm(y, x, xp, proper = FALSE, ...)
syn.cubertnorm(y, x, xp, proper = FALSE, ...)

Arguments

y

an original data vector of length n.

x

a matrix (n x p) of original covariates.

xp

a matrix (k x p) of synthesised covariates.

proper

a logical value specifying whether proper synthesis should be conducted. See details.

...

additional parameters.

Details

Generates synthetic values using the spread around the fitted linear regression line of transformed y given x. For proper synthesis first the regression coefficients are drawn from normal distribution with mean and variance from the fitted model. The synthetic values are transformed back to the original scale.

Value

A list with two components:

res

a vector of length k with synthetic values of y.

fit

a data frame with regression coefficients and error estimates.

See also

syn, syn.norm, syn.normrank