mhglm_sim function

Simulate response patterns

Simulate response patterns for generalized linear models of gaussian or binomial families, with both an intercept and slope covariate. Used primarily for testing purposes.

mhglm_sim(n, m_per_level, sd_intercept, sd_slope,
          family = c("gaussian", "binomial"), seed)

Arguments

• n: an integer scalar, the number of observations at the lowest grouping level.
• m_per_level: an integer vector, the number of grouping levels nested under the level above.
• sd_intercept: a numeric vector, the standard deviations of the intercept random effects.
• sd_slope: a numeric vector, the standard deviations of the slope random effects.
• family: a character scalar, either "gaussian" or "binomial".
• seed: a single value, interpreted as an integer, or NULL as in set.seed.

Details

returns a data.frame with design matrix, response, and group levels.

Examples

mhglm_sim(n = 2, m_per_level = c(3, 3), sd_intercept = c(1, 2), 
        sd_slope = c(2, 1), family = "gaussian", seed = 123)

mhglm_sim(n = 2, m_per_level = c(3, 3), sd_intercept = c(1, 2), 
        sd_slope = c(2, 1), family = "binomial", seed = 123)