Summarise effects using their joint covariance

Computes a linear combination with the full covariance matrix. For staggered estimates, the default is the backend's overall ATT and its own weighting, rather than an equally weighted mean of dynamic estimates.

Usage

lamp_effect_summary(estimate, terms = NULL, weights = NULL, level = 0.95)

Arguments

estimate

A lamp_estimate.

terms

Coefficient names; NULL selects all elasticity lags, post-event coefficients for an event study, or the treatment coefficient.

weights

Numeric weights in the order of terms. Defaults to one for elasticity lags and equal averaging weights otherwise. Supplied weights are used as supplied, without normalisation.

level

Confidence level between zero and one.

Value

A one-row tibble with estimate, standard error, interval, confidence level and the aggregation definition. Unsupported joint covariance is an error, rather than an independence approximation.

See also

Other diagnostics: lamp_design_audit(), lamp_elasticity_robustness(), lamp_placebo(), lamp_pretrends(), lamp_trend_sensitivity()

Examples

sim <- lamp_simulate(design = "continuous", seed = 1)
lamp_effect_summary(lamp_elasticity(sim, lags = 0:1))
#> # A tibble: 1 × 6
#>   estimate std_error conf_low conf_high level definition                       
#>      <dbl>     <dbl>    <dbl>     <dbl> <dbl> <chr>                            
#> 1   -0.176    0.0620   -0.298   -0.0545  0.95 1 * .log_s_lag0 + 1 * .log_s_lag1