R: Average annual per cent change in segmented trend analysis

aapc {segmented} | R Documentation

## Average annual per cent change in segmented trend analysis

### Description

Computes the average annual per cent change to summarize piecewise linear relationships in segmented regression models.

### Usage

    aapc(ogg, parm, exp.it = FALSE, conf.level = 0.95, wrong.se = TRUE)

### Arguments

`ogg` | the fitted model returned by `segmented`.
`parm` | the single segmented variable of interest. It can be missing if the model includes a single segmented covariate. If missing and t`ogg` includes several segmented variables, the first one is considered.
`exp.it` | logical. If `TRUE`, the per cent change is computed, namely exp(mu)-1 where mu=∑_j bjwj, see ‘Details’.
`conf.level` | the confidence level desidered.
`wrong.se` | logical, if `TRUE`, the 'wrong” standard error (as discussed in Clegg et al. (2009)) ignoring uncertainty in the breakpoint estimate is returned as an attribute `"wrong.se"`.

### Details

To summarize the fitted piecewise linear relationship, Clegg et al. (2009) proposed the 'average annual per cent change' (AAPC) computed as the sum of the slopes (beta_j) weighted by corresponding covariate sub-interval width (w_j), namely mu=sum_j beta_j w_j. Since the weights are the breakpoint differences, the standard error of the AAPC should account for uncertainty in the breakpoint estimate, as discussed in Muggeo (2010) and implemented by `aapc()`.

### Value

`aapc` returns a numeric vector including point estimate, standard error and confidence interval for the AAPC relevant to variable specified in `parm`.

### Note

`exp.it=TRUE` would be appropriate only if the response variable is the log of (any) counts.

### Author(s)

Vito M. R. Muggeo, vito.muggeo@unipa.it

### References

Clegg LX, Hankey BF, Tiwari R, Feuer EJ, Edwards BK (2009) Estimating average annual per cent change in trend analysis. Statistics in Medicine, 28; 3670-3682

Muggeo, V.M.R. (2010) Comment on ‘Estimating average annual per cent change in trend analysis’ by Clegg et al., Statistics in Medicine; 28, 3670-3682. Statistics in Medicine, 29, 1958–1960.

### Examples

    x<-1:20
    y<-2-.5*x+.7*pmax(x-9,0)-.8*pmax(x-15,0)+rnorm(20)*.3
    o<-lm(y~x)
    os<-segmented(o, psi=c(5,10))
    aapc(os)

[Package segmented version 0.5-3.0 Index]