Transforms effect-sizes and their standard errors to the response scale.
Usage
log_back(beta, se, sim)
logit_back(beta, se, sim)
probit_back(beta, se, sim)
inverse_back(beta, se, sim)
square_back(beta, se, sim)
cube_back(beta, se, sim)
identity_back(beta, se, sim)
power_back(beta, se, sim, n)
divide_back(beta, se, sim, n)
square_root_back(beta, se, sim)Arguments
- beta
Analyst beta estimate
- se
Standard error of analyst's effect size estimate \(\beta\) or out-of-sample prediction estimate \(y_i\).
- sim
numeric vector of length 1. number of simulations.
- n
Denominator used by analyst to divide the response variable.
Details
We assume analysts' estimates are normally distributed. Each function uses a normal distribution to simulate the a distribution of effect-sizes and their standard errors. Next this distribution is back-transformed to the desired response scale. The mean m_est, standard error se_est, and quantiles (lower and upper) of the back-transformed distribution are returned within a dataframe.
Functions
log_back(): Back transform beta estimates for models with log-linklogit_back(): Back transform beta estimates for models with logit-linkprobit_back(): Back transform beta estimates for models with probit-linkinverse_back(): Back transform beta estimates for models with \(1/x\) linksquare_back(): Back transform beta estimates for models with \(x^2\)-linkcube_back(): Back transform beta estimates for models with \(x^3\)-linkidentity_back(): Back transform beta estimates for models with identity-linkpower_back(): Back transform beta estimates for models with power-linkdivide_back(): Back transform beta estimates or out-of-sample predictions from models whose response variable has been divided by some number,n.square_root_back(): Back transform beta estimates or out-of-sample predictions from models whose response variable has been transformed by the square root
See also
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
Other Back-transformation:
assign_transformation_type(),
back_transform_response_vars_yi(),
clean_response_transformation(),
conversion(),
conversion_2(),
convert_predictions(),
rename_prediction_cols()
