Man pages for ebenmichael/balancer
Matrix constraints for covariate balance
| balancer | balancer: A package for treatment effect heterogeneity and... |
| calibrate | Calibrate sample to target |
| check_args_treatment | Check that data is in right shape and hyparameters are... |
| check_args_treatment_kernel | Check that data is in right shape and hyparameters are... |
| check_data | Check that data is in right shape and hyparameters are... |
| check_data_cluster | Check that data is in right shape and hyparameters are... |
| check_data_multi | Check that data is in right shape and hyparameters are... |
| check_data_rct | Check that data is in right shape and hyparameters are... |
| check_data_surv | Check that data is in right shape, hyparameters are feasible,... |
| cluster_weights | Re-weight groups to target population means |
| compute_block_diag_kernel | Compute block diagonal kernel matrix |
| compute_cluster_maxsubset_se | Compute point estimate and standard error with clustered max... |
| compute_cluster_se | Compute point estimate and standard error with clustered... |
| compute_kernel | compute kernel matrix |
| create_constraints | Create the constraints for QP: l <= Ax <= u |
| create_constraints_cluster | Create the constraints for QP: l <= Ax <= u |
| create_constraints_l2 | Create the constraints for QP: l <= Ax <= u |
| create_constraints_multi | Create the constraints for QP: l <= Ax <= u |
| create_constraints_multi_kern | Create the constraints for QP: l <= Ax <= u |
| create_constraints_mundlak | Create the constraints for QP: l <= Ax <= u |
| create_constraints_rct | Create the constraints for QP: l <= Ax <= u |
| create_constraints_stochastic_int | Create the constraints for QP: l <= Ax <= u |
| create_constraints_treatment | Create the constraints for QP: l <= Ax <= u |
| create_constraints_treatment_kernel | Create the constraints for QP: l <= Ax <= u |
| create_I0_matrix | Create diagonal regularization matrix |
| create_I0_matrix_multi | Create diagonal regularization matrix |
| create_I0_matrix_surv | Create diagonal regularization matrix |
| create_I0_matrix_treatment | Create diagonal regularization matrix |
| create_I0_matrix_treatment_kernel | Create diagonal regularization matrix |
| create_P_matrix | Create the P matrix for an QP that solves min_x 0.5 * x'Px +... |
| create_P_matrix_cluster | Create the P matrix for an QP that solves min_x 0.5 * x'Px +... |
| create_P_matrix_multi | Create the P matrix for an QP that solves min_x 0.5 * x'Px +... |
| create_P_matrix_multi_kern | Create the P matrix for an QP that solves min_x 0.5 * x'Px +... |
| create_P_matrix_surv | Create the P matrix for an QP that solves min_x 0.5 * x'Px +... |
| create_P_matrix_treatment | Create the P matrix for an QP that solves min_x 0.5 * x'Px +... |
| create_P_matrix_treatment_kernel | Create the P matrix for an QP that solves min_x 0.5 * x'Px +... |
| create_q_vector | Create the q vector for an QP that solves min_x 0.5 * x'Px +... |
| create_q_vector_cluster | Create the q vector for an QP that solves min_x 0.5 * x'Px +... |
| create_q_vector_multi | Create the q vector for an QP that solves min_x 0.5 * x'Px +... |
| create_q_vector_multi_kern | Create the q vector for an QP that solves min_x 0.5 * x'Px +... |
| create_q_vector_mundlak | Create the q vector for an QP that solves min_x 0.5 * x'Px +... |
| create_q_vector_surv | Create the q vector for an QP that solves min_x 0.5 * x'Px +... |
| create_q_vector_treatment | Create the q vector for an QP that solves min_x 0.5 * x'Px +... |
| create_q_vector_treatment_kernel | Create the q vector for an QP that solves min_x 0.5 * x'Px +... |
| create_scaled_I_matrix | Create diagonal regularization matrix |
| get_uniform_weights | Get a set of uniform weights for initialization |
| get_uniform_weights_treatment | Get a set of uniform weights for initialization |
| get_uniform_weights_treatment_kernel | Get a set of uniform weights for initialization |
| l2_balance_internal | Re-weight data to a target with local and global constraints |
| maxsubset_weights | Find maximum effective sample size balanced set |
| maxsubset_weights_cluster | Find maximum effective sample size balanced set |
| multilevel_ate_qp | Re-weight treated and control sub-groups to sub-group means |
| multilevel_kernel_qp | Re-weight control sub-groups to treated sub-group with kernel... |
| multilevel_qp | Re-weight control sub-groups to treated sub-group means |
| mundlak_weights | Re-weight control sub-groups to treated sub-group means |
| standardize | Re-weight groups to target population means |
| standardize_indirect | Re-weight populations to group targets |
| standardize_indirect_z | Re-weight population to group z's target |
| standardize_rct | Re-weight groups to target population means |
| standardize_treatment | Re-weight groups to target population means |
| standardize_treatment_hybrid | Re-weight groups to target population means |
| standardize_treatment_kernel | Re-weight groups to target population means |
| stochastic_int | Balance towards a stochastic intervention |
| survival_qp | Re-weight control sub-groups to treated sub-group means |
