| cfChange | Create or modify a set of counterfactuals |
| cfFactorial | Create a set of counterfactuals using a factorial design |
| cfFactorial | Create a set of counterfactuals using a factorial design |
| cfMake | Create or modify a set of counterfactuals |
| cfName | Create or modify a set of counterfactuals |
| concord.glm | Prediction-based goodness of fit measures for categorical models |
| concord.oprobit | Prediction-based goodness of fit measures for categorical models |
| extractdata | Extract from a dataframe all variables used in a formula |
| glue | Paste without separators |
| hetnormsimpv | Simulate quantities of interest and predictive intervals for heteroskedastic linear models |
| influencePlot | Create an interactive plot of studentized residuals against hat-values |
| lagpanel | Lag a variable with panel structure |
| ldvsimev | Simulate quantities of interest and confidence intervals for linear time series models including ARIMA or lagged dependent variable processes |
| ldvsimfd | Simulate quantities of interest and confidence intervals for linear time series models including ARIMA or lagged dependent variable processes |
| ldvsimpd | Simulate quantities of interest and confidence intervals for linear time series models including ARIMA or lagged dependent variable processes |
| ldvsimpr | Simulate quantities of interest and confidence intervals for linear time series models including ARIMA or lagged dependent variable processes |
| ldvsimpv | Simulate quantities of interest and confidence intervals for linear time series models including ARIMA or lagged dependent variable processes |
| ldvsimrr | Simulate quantities of interest and confidence intervals for linear time series models including ARIMA or lagged dependent variable processes |
| linearsimev | Simulate quantities of interest and confidence intervals for linear models |
| linearsimfd | Simulate quantities of interest and confidence intervals for linear models |
| linearsimrr | Simulate quantities of interest and confidence intervals for linear models |
| logBound | Log transform a variable, creating a dummy variable to record out of bound cases |
| logitBound | Logit transform a variable, creating dummy variables to record out of bound cases |
| logitsimev | Simulate quantities of interest and confidence intervals for binary logit |
| logitsimfd | Simulate quantities of interest and confidence intervals for binary logit |
| logitsimrr | Simulate quantities of interest and confidence intervals for binary logit |
| loglinsimev | Simulate quantities of interest and confidence intervals for loglinear models |
| loglinsimfd | Simulate quantities of interest and confidence intervals for loglinear models |
| loglinsimrr | Simulate quantities of interest and confidence intervals for loglinear models |
| makeFEdummies | Create a matrix of dummy variables |
| mlogitsimev | Simulate quantities of interest and confidence intervals for multinomial logit |
| mlogitsimfd | Simulate quantities of interest and confidence intervals for multinomial logit |
| mlogitsimrr | Simulate quantities of interest and confidence intervals for multinomial logit |
| oprobitsimev | Simulate quantities of interest and confidence intervals for ordered probit |
| oprobitsimfd | Simulate quantities of interest and confidence intervals for ordered probit |
| oprobitsimrr | Simulate quantities of interest and confidence intervals for ordered probit |
| pcp.glm | Prediction-based goodness of fit measures for categorical models |
| pcp.oprobit | Prediction-based goodness of fit measures for categorical models |
| probitsimev | Simulate quantities of interest and confidence intervals for binary probit |
| probitsimfd | Simulate quantities of interest and confidence intervals for binary probit |
| probitsimrr | Simulate quantities of interest and confidence intervals for binary probit |
| rpcf | Ratio-preserving counterfactuals |