# Impact Measurement Toolkit

## Documentation for package ‘imt’ version 1.0.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

.combineColumns | Combine and Unite Columns
.randomize_internal | Add a Random Treatment Indicator Column to a Data Frame
balancePlot | Create a Baseline Balance Plot.
blm | Bayesian Linear Model Factory
calcProb | Calculate Probability of Posterior Draws Falling Within a Range
calculateEffectSizes | Calculate Effect Sizes for Treatment vs. Control
checkBaseline | Check Baseline Equivalency.
cleanData | Cleans and prepares data for analysis
countMissing | Count missing values (NA) in a dataframe
coxsIndex | Cox's Proportional Hazards Index (Cox's C)
createData | Converts a dataframe into a named list to provide data to a Stan model
credibleInterval | Calculate credible interval from MCMC draws
fit | Fits Stan model.
getStanParameter | Extracts parameter from Stan model.
hedgesG | Hedges' g Effect Size with Pooled Standard Deviation
logit | Bayesian Logit Model Factory
logitRng | Calculate logit link and sample from binomial distribution
mcmcChecks | MCMC Checks
metaAnalysis | Create a Meta-Analysis Object Using Data From Previous Studies
negativeBinomial | Bayesian Negative Binomial Model Factory
pointEstimate | Calculate Point Estimate (Median or Mean) as Percentage
randomize | Randomly Assign Treatment While Controlling for Baseline Equivalency
randomizer | Randomization Class for Treatment Assignment
validate_logical_vector | Validate a Logical Subgroup Vector