# Surrogate Outcome Regression Analysis

## Documentation for package ‘SurrogateRegression’ version 0.6.0.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

SurrogateRegression-package | SurrogateRegression: Surrogate Outcome Regression Analysis
bnr-class | Bivariate Regression Model
CheckInit | Check Initiation
CheckTestSpec | Check Test Specification
coef.bnr | Extract Coefficients from Bivariate Regression Model
CovInfo | Covariance Information Matrix
CovTab | Tabulate Covariance Parameters
CovUpdate | Covariate Update
FitBNEM | Fit Bivariate Normal Regression Model via Expectation Maximization.
FitBNLS | Fit Bivariate Normal Regression Model via Least Squares
FitBNR | Fit Bivariate Normal Regression Model
fitOLS | Ordinary Least Squares
FormatOutput | Format Output
IterUpdate | Update Iteration
matDet | Matrix Determinant
matInv | Matrix Inverse
matIP | Matrix Inner Product
matOP | Matrix Outer Product
matQF | Quadratic Form
MMP | Matrix Matrix Product
ObsLogLik | Observed Data Log Likelihood
ParamInit | Parameter Initialization
PartitionData | Partition Data by Outcome Missingness Pattern.
print.bnr | Print for Bivariate Regression Model
rBNR | Simulate Bivariate Normal Data with Missingness
RegInfo | Regression Information
RegTab | Tabulate Regression Coefficients
RegUpdate | Regression Update
residuals.bnr | Extract Residuals from Bivariate Regression Model
SchurC | Schur complement
ScoreBNEM | Score Test via Expectation Maximization.
show-method | Show for Bivariate Regression Model
SurrogateRegression | SurrogateRegression: Surrogate Outcome Regression Analysis
TestBNR | Test Bivariate Normal Regression Model.
tr | Matrix Trace
UpdateEM | EM Update
vcov.bnr | Extract Covariance Matrix from Bivariate Normal Regression Model
WaldBNEM | Wald Test via Expectation Maximization.
WaldBNLS | Wald Test via Least Squares.