Description Usage Arguments Details Value Author(s) References See Also Examples
Creates an object containing the standardized residuals from the contrast mean and variance modeling steps.
1 | iqResids(object)
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object |
object of type |
Creates an object containing the standardized residuals from the
contrast mean and variance modeling steps to be used with the plotting
function plot.iqResids. The choice of density estimator in the
next step of IQ-learning should be based on a QQ-plot of the
standardized residuals.
Returns object$stdResids from an object of type
learnIQ1var in the form of an object of type iqResids.
Kristin A. Linn <kalinn@ncsu.edu>, Eric B. Laber, Leonard A. Stefanski
Laber, E.B., Linn, K.A., and Stefanski, L.A. (2013). Interactive Q-learning. Submitted.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ## load in two-stage BMI data
data (bmiData)
bmiData$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]
## 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)
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