> print(dml_pliv)
================= DoubleMLPLIV Object ==================


------------------ Data summary      ------------------
Outcome variable: Y
Treatment variable(s): D
Covariates: X1, X2, X3, X4, X5
Instrument(s): Z
Cluster variable(s): cluster_var_i, cluster_var_j
No. Observations: 100

------------------ Score & algorithm ------------------
Score function: partialling out
DML algorithm: dml2

------------------ Machine learner   ------------------
ml_g: regr.rpart
ml_m: regr.rpart
ml_r: regr.rpart

------------------ Resampling        ------------------
No. folds per cluster: 2
No. folds: 4
No. repeated sample splits: 1
Apply cross-fitting: TRUE

------------------ Fit summary       ------------------
 Estimates and significance testing of the effect of target variables
  Estimate. Std. Error t value Pr(>|t|)    
D    1.0138     0.1667    6.08  1.2e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



