OutcomeModel: Outcome generator

In phuchonguyen/mpower: Power Analysis via Monte Carlo Simulation for Correlated Data

Outcome generator

Description

This function creates a generative model of the outcome given a matrix of predictors.

Usage

OutcomeModel(f, family = "gaussian", sigma = 1, f_args = list())

Arguments

f	A string that describes the relationships between the predictors and outcome or a function that takes an input matrix and returns a vector of outcome: E(y|x) = g(f(x)) where g is a link function that depends on the family argument.
family	A string, 'gaussian', 'binomial', or 'poisson' for continuous, binary, or count outcomes.
sigma	A number, Gaussian noise standard deviation if applicable.
f_args	A named list of additional arguments to f

Value

An OutcomeModel object. Attributes:

f	mean function.
sigma	a number for the Gaussian observation noise.
family	a string 'gaussian' or 'binomial'.

Examples

# Define BMI as a ratio of weight and height plus random Gaussian error with standard deviation 1.
bmi_model <- mpower::OutcomeModel(f = 'weight/(height^2)', sigma = 1, family = 'gaussian')

phuchonguyen/mpower documentation built on Oct. 2, 2022, 7:57 p.m.