sim.hdlmm {dlmtree} | R Documentation |

## Creates simulated data for HDLM & HDLMM

### Description

Method for creating simulated data for HDLM & HDLMM

### Usage

```
sim.hdlmm(
sim = "A",
n = 1000,
error = 1,
effect.size = 1,
exposure.data = NULL
)
```

### Arguments

`sim` |
character (A - E) specifying simulation scenario |

`n` |
sample size |

`error` |
positive scalar specifying error variance for Gaussian response |

`effect.size` |
the effect size of the window of susceptibility |

`exposure.data` |
exposure data. A matrix of exposure data for simulation A, B, C and a named list of exposure data for simulation D, E |

### Details

sim.hdlmm

Simulation scenarios:

Scenario A: Two subgroups with early/late windows determined by continuous and binary modifiers

Scenario B: Two subgroups with scaled effect determined by a continuous modifier

Scenario C: No heterogeneity i.e., same effect on all individuals

Scenario D: Three subgroups with three corresponding exposures. Subgroups are determined by continuous and binary modifiers

Scenario E: Two subgroups with two exposures. First group is associated with the scaled main effect and lagged interaction while the second group is only associated with the scaled main effect, no interaction.

### Value

Simulated data and true parameters

### Examples

```
sim.hdlmm(sim = "A", n = 1000)
```

*dlmtree*version 1.0.0 Index]