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)
|
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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