Description Usage Arguments Details Value See Also Examples

This functions helps to evaluate the consequences of ignoring a random slope at the cluster level.

1 2 3 4 |

`object` |
A |

The design effect (DEFT) is the ratio of the standard error from the correct three-level model to the standard error from the misspecified model omitting the cluster-level random slope. The standard error for the misspecified model is calculated by assuming that the cluster-level random slope variance is added to the subject-level random slope.

The approximate Type I error under the miss-specified model is also calculated.
The effect of wrongly ignoring a third-level random slope on the Type I errors, depends on
`n1, n2, n3, icc_slope`

, and, `var_ratio`

.

A `data.frame`

with the columns ```
n1, n2, n3, icc_slope,
var_ratio, DEFT
```

, and, `approx_type1`

. The number of rows of the
`data.frame`

will be equals to the number of
different combination of parameters values specified with study_parameters.

1 2 3 4 5 6 7 8 9 10 | ```
paras <- study_parameters(n1 = 11,
n2 = 30,
n3 = 3,
T_end = 10,
icc_pre_subject = 0.5,
icc_pre_cluster = 0,
icc_slope = c(0.01,0.05, 0.1),
var_ratio = 0.02)
get_DEFT(paras)
``` |

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