iqLearn (version 1.5)

plot.iqResids: Plot the standardized residuals

Description

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

Usage

# S3 method for iqResids
plot(x, ...)

Arguments

x

object of type iqResids

...

additional arguments to be passed to plot()

Value

Returns a normal QQ-plot of the standardized residuals.

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.

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.

See Also

iqResids

Examples

# NOT RUN {
## 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)
# }