Description Usage Arguments Details Value Author(s) Examples

View source: R/DAMisc_functions.R

For objects of class `glm`

, it calculates the change in predicted responses, for maximal discrete changes in all covariates holding all other variables constant at typical values.

1 | ```
glmChange2(obj, varname, data, change=c("unit", "sd"), R=1500)
``` |

`obj` |
A model object of class |

`varname` |
Character string giving the variable name for which average effects are to be calculated. |

`data` |
Data frame used to fit |

`change` |
A string indicating the difference in predictor values to calculate the discrete change. |

`R` |
Number of simulations to perform. |

The function calculates the average effect discrete changes in the covariates, for objects of class `glm`

. This function works with polynomials specified with the `poly`

function.

A vector of values giving the average and 95 percent confidence bounds

Dave Armstrong (UW-Milwaukee, Department of Political Science)

1 2 3 4 5 6 7 8 |

```
Loading required package: car
Loading required package: effects
Loading required package: carData
Attaching package: 'carData'
The following objects are masked from 'package:car':
Guyer, UN, Vocab
lattice theme set by effectsTheme()
See ?effectsTheme for details.
mean lower upper
age -0.0426603 -0.06744547 -0.01781606
```

DAMisc documentation built on May 30, 2017, 8:12 a.m.

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