Description Usage Arguments Details Value Examples

Data is generated to ensure inter-cluster correlation 0, intra-cluster correlation in expectation ICC. The data generating process used in this function is specified at the following URL: https://stats.stackexchange.com/questions/263451/create-synthetic-data-with-a-given-intraclass-correlation-coefficient-icc

1 2 |

`mean` |
A number or vector of numbers, one mean per cluster. If none is provided, will default to 0. |

`N` |
(Optional) A number indicating the number of observations to be generated. Must be equal to length(clusters) if provided. |

`clusters` |
A vector of factors or items that can be coerced to clusters; the length will determine the length of the generated data. |

`sd` |
A number or vector of numbers, indicating the standard deviation of each cluster's error terms – standard deviation within a cluster (default 1) |

`sd_between` |
A number or vector of numbers, indicating the standard deviation between clusters. |

`total_sd` |
A number indicating the total sd of the resulting variable.
May only be specified if ICC is specified and |

`ICC` |
A number indicating the desired ICC. |

The typical use for this function is for a user to provide an `ICC`

and,
optionally, a set of within-cluster standard deviations, `sd`

. If the
user does not provide `sd`

, the default value is 1. These arguments
imply a fixed between-cluster standard deviation.

An alternate mode for the function is to provide between-cluster standard
deviations, `sd_between`

, and an `ICC`

. These arguments imply
a fixed within-cluster standard deviation.

If users provide all three of `ICC`

, `sd_between`

, and
`sd`

, the function will warn the user and use the provided standard
deviations for generating the data.

A vector of numbers corresponding to the observations from the supplied cluster IDs.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
# Divide observations into clusters
clusters = rep(1:5, 10)
# Default: unit variance within each cluster
draw_normal_icc(clusters = clusters, ICC = 0.5)
# Alternatively, you can specify characteristics:
draw_normal_icc(mean = 10, clusters = clusters, sd = 3, ICC = 0.3)
# Can specify between-cluster standard deviation instead:
draw_normal_icc(clusters = clusters, sd_between = 4, ICC = 0.2)
# Can specify total SD instead:
total_sd_draw = draw_normal_icc(clusters = clusters, ICC = 0.5, total_sd = 3)
sd(total_sd_draw)
# Verify that ICC generated is accurate
corr_draw = draw_normal_icc(clusters = clusters, ICC = 0.4)
summary(lm(corr_draw ~ as.factor(clusters)))$r.squared
``` |

DeclareDesign/fabricatr documentation built on May 6, 2019, 1:57 p.m.

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