ham (version 1.0.0)

plot.assess: Prediction plot of treatment and control groups for DID and ITS models

Description

Provides partial prediction plots for treatment and control groups from difference-in-difference (DID) and interrupted time series (ITS) models. The graph will produce lines for treatment/intervention and control groups to gain understanding through a visual representation of the regression coefficients. The treatment/intervention group is represented with a blue line, the control group is represented with a red line, and the counterfactual line, when available, is a dashed line.

Usage

# S3 method for assess
plot(x, y, xlim = NULL, ylim = NULL, add.legend = NULL, ...)

Value

plot of partial predictions for treatment and control groups.

Arguments

x

assess object. Either difference-in-difference or interrupted time series model with no covariate adjustment.

y

type of model, specify either 'DID' (difference-in-difference) or 'ITS' (interrupted time series). Will not accept other models.

xlim

specify plot's x-axis limits with a 2 value vector.

ylim

specify plot's y-axis limits with a 2 value vector.

add.legend

add a legend by selecting the location as "bottomright", "bottom", "bottomleft", "left", "topleft", "top", "topright", "right", "center". No legend if nothing selected.

...

additional arguments.

Examples

am2 <- assess(formula= los ~ ., data=hosprog, intervention = "program",
topcode =NULL, int.time="month", regression="none", treatment= 5,
interrupt=c(5,9), did="many", its="two", newdata=TRUE, propensity=NULL)
plot(am2, "DID", add.legend="bottomleft", ylim=c(2, 8))  #DID model
plot(am2, "ITS", add.legend="top", ylim=c(2, 8))         #ITS model