# summary.learnIQ1main: IQ-learning: main effect regression summary In iqLearn: Interactive Q-Learning

## Description

Output from the main effect term regression in IQ-learning.

## Usage

 ```1 2``` ```## S3 method for class 'learnIQ1main' summary(object, ...) ```

## Arguments

 `object ` object of type `learnIQ1main` `... ` additional arguments to be passed to `summary()`

## Details

Regression output and other summary statistics from the main effect term regression. See `summary.lm` for more details.

## Value

Computes and returns multiple summary statistics from the linear model in `object`. See `summary.lm` for a list of available summary statistics.

## 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.

`learnIQ1main`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```## 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] fitIQ2 = learnIQ2 (y ~ gender + parent_BMI + month4_BMI + A2*(parent_BMI + month4_BMI), data=bmiData, "A2", c("parent_BMI", "month4_BMI")) fitIQ1main = learnIQ1main (~ gender + race + parent_BMI + baseline_BMI + A1*(gender + parent_BMI), data=bmiData, "A1", c ("gender", "parent_BMI"), fitIQ2) summary (fitIQ1main) ```