Description Usage Arguments Value Author(s) References Examples

Calculates empirical variances for data sets with regularly or irregularly spaced time points, and plots the result

1 | ```
var.inspect(resid, timeVar, binwidth, numElems = 0, irregular = T)
``` |

`resid` |
a vector of empirical residuals |

`timeVar` |
a vector for the time variable |

`binwidth` |
a numerical value for the bin length, to be used for irregularly spaced data |

`numElems` |
a numerical value for the elimination of the bins with less than that number of elements |

`irregular` |
a character string, |

Returns mid values and variances of the bins, and numbers of elements falling into the bins for `irregular = TRUE`

,
and unique time points and variances, and number of the elements for the time points for `irregular = FALSE`

.

Ozgur Asar, Peter J. Diggle

Asar O, Ritchie J, Kalra P, Diggle PJ (2015) Acute kidney injury amongst chronic kidney disease patients: a case-study in statistical modelling. To be submitted.

Diggle PJ, Sousa I, Asar O (2015) Real time monitoring of progression towards renal failure in primary care patients.
*Biostatistics*, 16(3), 522-536.

1 2 3 4 5 6 7 8 9 10 | ```
# loading the data set and subsetting it for the first 20 patients
# for the sake illustration of the usage of the functions
data(data.sim.ibm)
data.sim.ibm.short <- data.sim.ibm[data.sim.ibm$id <= 20, ]
# obtaining empirical residuals by a linear model
# and calculating the empirical variances
lm.fit <- lm(log.egfr ~ sex + bage + fu + pwl, data = data.sim.ibm.short)
var.inspect(resid = resid(lm.fit), timeVar = data.sim.ibm.short$fu, binwidth = 0.1,
numElems = 20, irregular = TRUE)
``` |

lmenssp documentation built on May 29, 2017, 10:33 p.m.

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