EstimateScoreBin: Estimate summary confounder scores (binary logistic model)

In kaz-yos/distributed: Examine Privacy Preserving Data Analysis Methods in Simulated Distributed Data Network

Description

Estimate propensity score or disease risk score depending on the model specification. This is for binary outcomes.

Usage

EstimateScoreBin(formula, data, newdata)

Arguments

formula	formula to specify the model used to estimate the summary score. For propensity score, specify the treatment model. For disease risk score, specify the outcome model in the absence of treatment.
data	data frame of data for model building. Specify the entire dataset for propensity score estimation. Specify the untreated subset for disease risk score estimation.
newdata	data frame of data for prediction. Specify the entire dataset.

Value

vector of summary scores predicted for newdata.

Author(s)

Kazuki Yoshida

kaz-yos/distributed documentation built on May 27, 2019, 4:50 a.m.