R: Methods and Examples from Introduction to the Theory of Observational Studies

# Methods and Examples from Introduction to the Theory of Observational Studies

## Documentation for package ‘iTOS’ version 1.0.3

- DESCRIPTION file

## Help Pages

iTOS-package | Methods and Examples from Introduction to the Theory of Observational Studies
addcaliper | Add a Caliper to an Existing Cost Matrix
addinteger | Add an Integer Penalty to an Existing Distance Matrix
addMahal | Rank-Based Mahalanobis Distance Matrix
addNearExact | Add a Near-exact Penalty to an Exisiting Distance Matrix.
addquantile | Cut a Covariate at Quantiles and Add a Penalty for Different Quantile Categories
aHDL | Alcohol and HDL Cholesterol
amplify | Amplification of sensitivity analysis in observational studies.
binge | Binge Drinking and High Blood Pressure
bingeM | Binge Drinking and High Blood Pressure - Matched With Two Control Groups
computep | Computes individual and pairwise treatment assignment probabilities.
ev | Computes the null expectation and variance for one stratum.
evalBal | Evaluate Covariate Balance in a Matched Sample
evall | Compute expectations and variances for one stratum.
gconv | Convolution of Two Probability Generating Functions
iTOS | Methods and Examples from Introduction to the Theory of Observational Studies
makematch | Two-Criteria Matching
makenetwork | Make the Network Used for Matching with Two Criteria
noether | Sensitivity Analysis Using Noether's Test for Matched Pairs
startcost | Initialize a Distance Matrix.
zeta | zeta function in sensitivity analysis