generate_bivariate_normal_data_count: Generate data from bivariate normal covariates (count...

Description Usage Arguments Value Author(s)

Description

.. content for details ..

Usage

1
2
generate_bivariate_normal_data_count(n, rho, alphas, gamma, sigma, beta0, betaA,
  betaX, betaXA)

Arguments

n

Sample size

rho

correlation coefficient

alphas

True coefficients for the first and second treatment linear predictors. This vector should contain the intercept. alphas = c(alpha01, alphaXm1, alpha02, alphaXm2)

gamma

Ratio of the true coefficient for the second variable and the first variable.

sigma

scaling of all covariate effects. A higher value means stronger covariate effects, i.e., less clinical equipoise.

beta0

Outcome model intercept coefficient

betaA

Outcome model coefficient for I(A_i = 1) and I(A_i = 2)

betaX

Outcome model coefficient vector for covariates X_i

betaXA

Outcome model interaction coefficients for covariates. betaXA = c(betaXA1, betaXA2)

Value

a complete simulated data_frame

Author(s)

Kazuki Yoshida


kaz-yos/empeq3 documentation built on May 8, 2019, 7:29 a.m.