This is a supporting function of the meanEquivTest function. It calculates the placebo coefficients and the absolute value of the mean of the placebo coefficients. It then calculates the critical value and p-values if an equivalence threshold is supplied for the test, according to Dette & Schumann (2024). If equivalence threshold is not supplied, it calculates the minimum equivalence threshold for which the null of non-negligible pre-trend differences can be rejected.
meanTest_func(
data,
equiv_threshold,
vcov,
cluster,
alpha,
n,
no_periods,
base_period,
is_panel_balanced
)#' An object of class "meanEquivTest" containing:
placebo_coefficientsA numeric vector of the estimated placebo coefficients,
abs_mean_placebo_coefsthe absolute value of the mean of the placebo coefficients,
var_mean_placebo_coefthe estimated variance of the mean placebo coefficient,
significance_levelthe significance level of the test,
num_individualsthe number of cross-sectional individuals in the data,
num_periodsthe number of periods in the data,
base_periodthe base period in the data,
num_observationsthe total number of observations in the data,
equiv_threshold_specifieda logical value indicating whether an equivalence threshold was specified.
is_panel_balanceda logical value indicating whether the panel data is balanced.
If is.null(equiv_threshold), then additionally minimum_equiv_threshold: the minimum equivalence threshold for which the null hypothesis of non-negligible (based on the equivalence threshold) trend-differnces can be rejected.
if !(is.null(equiv_threshold)), then additionally
mean_critical_value: the critical value at the alpha level,
p_value: the p-value of the test,
reject_null_hypothesis: A logical value indicating whether to reject the null hypothesis,
equiv_threshold: the equivalence threshold specified.
The data.frame object containing the data for the test. Should be of the form what is returned by the EquiTrends_dataconstr function.
The equivalence threshold for the test. If NULL, the minimum equivalence threshold for which the null hypothesis can be rejected is calculated.
The variance-covariance matrix estimator. See meanEquivTest for more information.
The cluster variable for the cluster-robust variance-covariance matrix estimator. See meanEquivTest for more information.
The significance level for the test. Only required if no equivalence threshold is supplied.
The number of cross-sectional individuals in the data.
The number of periods in the data.
The base period for the test. Must be one of the unique periods in the data.
A logical value indicating whether the panel data is balanced.
Dette, H., & Schumann, M. (2024). "Testing for Equivalence of Pre-Trends in Difference-in-Differences Estimation." Journal of Business & Economic Statistics, 1–13. DOI: tools:::Rd_expr_doi("10.1080/07350015.2024.2308121")