# localInfluence.glmgee: Local Influence for Generalized Estimating Equations In glmtoolbox: Set of Tools to Data Analysis using Generalized Linear Models

## Description

Computes some measures and, optionally, display graphs of them to perform influence analysis based on the approaches described in Cook (1986) and Jung (2008).

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```## S3 method for class 'glmgee' localInfluence( object, type = c("total", "local"), perturbation = c("cw-clusters", "cw-observations", "response", "covariate"), covariate, coefs, plot.it = FALSE, identify, ... ) ```

## Arguments

 `object` an object of class glmgee obtained from the fit of a generalized estimating equation. `type` an (optional) character string indicating the type of approach to study the local influence. The options are: the absolute value of the elements of the eigenvector which corresponds to the maximum absolute eigenvalue ("local"); and the absolute value of the elements of the main diagonal ("total"). By default, `type` is set to be "total". `perturbation` an (optional) character string indicating the perturbation scheme to apply. The options are: case weight perturbation of clusters ("cw-clusters"); Case weight perturbation of observations ("cw-observations"); perturbation of covariates ("covariate"); and perturbation of response ("response"). By default, `perturbation` is set to be "cw-clusters". `covariate` an character string which (partially) match with the names of one of the parameters in the linear predictor. This is only appropriate if `perturbation="covariate"`. `coefs` an (optional) character string which (partially) match with the names of some of the parameters in the linear predictor. `plot.it` an (optional) logical indicating if the plot of the measures of local influence is required or just the data matrix in which that plot is based. By default, `plot.it` is set to be FALSE. `identify` an (optional) integer indicating the number of clusters/observations to identify on the plot of the measures of local influence. This is only appropriate if `plot.it=TRUE`. `...` further arguments passed to or from other methods. If `plot.it=TRUE` then `...` may be used to include graphical parameters to customize the plot. For example, `col`, `pch`, `cex`, `main`, `sub`, `xlab`, `ylab`.

## Value

A matrix as many rows as clusters/observations in the sample and one column with the values of the measures of local influence.

## References

Cook D. (1986) Assessment of Local Influence. Journal of the Royal Statistical Society: Series B (Methodological) 48, 133-155.

Jung K.-M. (2008) Local Influence in Generalized Estimating Equations. Scandinavian Journal of Statistics 35, 286-294.

## Examples

 ```1 2 3 4``` ```mod <- size ~ poly(days,4) + treat fit <- glmgee(mod, id=tree, family=Gamma("log"), corstr="AR-1", data=spruces) summary(fit) localInfluence(fit,type="total",perturbation="cw-clusters",coefs="treat",plot.it=TRUE) ```

glmtoolbox documentation built on Oct. 4, 2021, 9:08 a.m.