tidy.AGGTEobj: Tidy an AGGTEobj into a data frame

In did: Treatment Effects with Multiple Periods and Groups

Tidy an AGGTEobj into a data frame

Description

Returns a tidy data frame of aggregated treatment effect estimates from an aggte() result.

Usage

## S3 method for class 'AGGTEobj'
tidy(x, ...)

Arguments

x	a model of class AGGTEobj produced by the aggte() function
...	Additional arguments to tidying method.

Details

The key distinction between conf.low/conf.high and point.conf.low/point.conf.high is that the former accounts for multiple testing across all estimates (simultaneous coverage), while the latter provides marginal (per-estimate) coverage only. Use the simultaneous bands when you want to make joint inferences across all event times or groups.

Value

A data frame whose columns depend on type:

type

the aggregation type: "simple", "dynamic", "group", or "calendar"

term

label for each estimate

estimate

point estimate

std.error

standard error

statistic

t-statistic (estimate / std.error)

p.value

two-sided pointwise p-value (2 * (1 - pnorm(abs(statistic)))). Marginal per-estimate; does not account for multiple testing across event times or groups.

conf.low, conf.high

simultaneous confidence band limits. When bstrap=TRUE and cband=TRUE these use the bootstrap uniform critical value (crit.val.egt); otherwise they equal the pointwise intervals. For type="simple" and the overall average row of type="group", a single scalar is returned so simultaneous and pointwise coincide.

point.conf.low, point.conf.high

pointwise confidence interval limits always using qnorm(1 - alp/2).

did documentation built on June 13, 2026, 5:07 p.m.