# plotResidual: Estimate and Plot Empirical Distributions of Residuals in the... In MixtureRegLTIC: Mixture Regression Models for Left-Truncated and Interval-Censored Data

## Description

A function to estimate and plot estimated empirical distribution functions of the residuals in the fitted regression model.

## Usage

 ```1 2``` ```plotResidual(fit, xlab = NULL, ylab = NULL, main = NULL, col = NULL, lty = NULL, lwd = 1, axes = T) ```

## Arguments

 `fit` the output object from the fitted mixture regression model. `xlab` the title for x axis. `ylab` the title for y axis. `main` the main title of the plot. `col` a vector of colors. `lty` a vector of line types. `lwd` a numeric value specifies the line width. `axes` a logical value specifies whether axes should be drawn. If axes=FALSE, both x and y axes are not shown .

## References

Chen CH, Tsay YC, Wu YC and Horng CF. Logistic-AFT location-scale mixture regression models with nonsusceptibility for left-truncated and general interval-censored data. Statistics in Medicine, 2013; 32:4285<e2><80><93>4305.

`MixtureLogitAFT`
 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```data(simLTICdataA) ##### fit the logistic-AFT location-scale model for LTIC data fit=MixtureLogitAFT(formula=Surv(time1,time2,status)~1, eventprobreg=~X1,locationreg=~X1,scalereg=~X1, var.entry="entry",data=simLTICdataA) ##### plot the empirical distribution of residuals plot.res=plotResidual(fit) legend(-9.5,1,legend=plot.res\$legend,col=plot.res\$col,lty=plot.res\$lty, title=" Strata (Case / Total)") ```