# plot.iqResids: Plot the standardized residuals In iqLearn: Interactive Q-Learning

## Description

Plot the standardized residuals that arise from the contrast function mean and variance modeling.

## Usage

 ```1 2``` ```## S3 method for class 'iqResids' plot(x, ...) ```

## Arguments

 `x ` object of type `iqResids` `... ` additional arguments to be passed to `plot()`

## Details

Can be used to decide which density estimator ("norm" or "nonpar") should be used for the conditional density of the contrast function given first-stage history and treatment.

## Value

Returns a normal QQ-plot of the standardized residuals.

## Author(s)

Kristin A. Linn <[email protected]>, Eric B. Laber, Leonard A. Stefanski

## References

Linn, K. A., Laber, E. B., Stefanski, L. A. (2015) "iqLearn: Interactive Q-Learning in R", Journal of Statistical Software, 64(1), 1–25.

Laber, E. B., Linn, K. A., and Stefanski, L. A. (2014) "Interactive model building for Q-learning", Biometrika, 101(4), 831-847.

`iqResids`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31``` ```## load in two-stage BMI data data (bmiData) bmiData\$A1[which (bmiData\$A1=="MR")] = 1 bmiData\$A1[which (bmiData\$A1=="CD")] = -1 bmiData\$A2[which (bmiData\$A2=="MR")] = 1 bmiData\$A2[which (bmiData\$A2=="CD")] = -1 bmiData\$A1 = as.numeric (bmiData\$A1) bmiData\$A2 = as.numeric (bmiData\$A2) s1vars = bmiData[,1:4] s2vars = bmiData[,c (1, 3, 5)] a1 = bmiData[,7] a2 = bmiData[,8] ## define response y to be the negative 12 month change in BMI from ## baseline y = -(bmiData[,6] - bmiData[,4])/bmiData[,4] s2ints = c (2, 3) ## second-stage regression fitIQ2 = learnIQ2 (y ~ gender + parent_BMI + month4_BMI + A2*(parent_BMI + month4_BMI), data=bmiData, "A2", c("parent_BMI", "month4_BMI")) ## model conditional mean of contrast function fitIQ1cm = learnIQ1cm (~ gender + race + parent_BMI + baseline_BMI + A1*(gender + parent_BMI + baseline_BMI), data=bmiData, "A1", c ("gender", "parent_BMI", "baseline_BMI"), fitIQ2) ## variance modeling fitIQ1var = learnIQ1var (~ gender + race + parent_BMI + baseline_BMI + A1*(parent_BMI), data=bmiData, "A1", c ("parent_BMI"), "hetero", fitIQ1cm) ## plot standardized residuals fitResids = iqResids (fitIQ1var) plot (fitResids) ```