# mhglm_sim

From mbest v0.6
by Patrick Perry

##### 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.

- Keywords
- datagen

##### Usage

```
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

```
# NOT RUN {
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)
# }
```

*Documentation reproduced from package mbest, version 0.6, License: Apache License (== 2.0) | file LICENSE*

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