A convenient wrapper for the `plot`

function with the addition
of error bars, e.g. to create caterpillar plots.

1 2 | ```
caterpillar(y, x, qtlow, qtup, xlab = "", ylab = "", xlim = NULL,
ylim = NULL, main = "")
``` |

`y` |
A numerical vector specifying the |

`x` |
A numerical vector specifying the |

`qtlow` |
A numerical vector (e.g. of lower-quantiles) to be used to plot lower error bars. |

`qtup` |
A numerical vector (e.g. of upper-quantiles) to be used to upper plot error bars. |

`xlab` |
A label for the |

`ylab` |
A label for the |

`xlim` |
The |

`ylim` |
The y limits of the plot; see |

`main` |
A main title for the plot; see |

Zhang, Z., Charlton, C.M.J., Parker, R.M.A., Leckie, G., and Browne, W.J. (2016) Centre for Multilevel Modelling, University of Bristol, U.K.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
## Not run:
library(R2MLwiN)
# NOTE: if MLwiN not saved where R2MLwiN defaults to:
# options(MLwiN_path = 'path/to/MLwiN vX.XX/')
# If using R2MLwiN via WINE, the path may look like:
# options(MLwiN_path = '/home/USERNAME/.wine/drive_c/Program Files (x86)/MLwiN vX.XX/')
# Example using tutorial dataset
data(tutorial, package = 'R2MLwiN')
(mymodel <- runMLwiN(normexam ~ 1 + (1 | school) + (1 | student),
estoptions = list(resi.store = TRUE),
data = tutorial))
# For each school, calculate the CIs...
residuals <- mymodel@residual$lev_2_resi_est_Intercept
residualsCI <- 1.96 * sqrt(mymodel@residual$lev_2_resi_var_Intercept)
residualsRank <- rank(residuals)
rankno <- order(residualsRank)
caterpillar(y = residuals[rankno], x = 1:65, qtlow = (residuals - residualsCI)[rankno],
qtup = (residuals + residualsCI)[rankno], xlab = 'Rank', ylab = 'Intercept')
## End(Not run)
``` |

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