A dataset from a simulation study with 4 data-generating mechanisms, useful to illustrate custom input of confidence intervals to calculate coverage probability.
This simulation study aims to compare the t-test assuming pooled or unpooled variance in violation (or not) of the t-test assumptions: normality of data, and equality (or not) or variance between groups.
The true value of the difference between groups is -1.

tt

A data frame with 4,000 rows and 8 variables:

`diff`

The difference in mean between groups estimated by the t-test;

`se`

Standard error of the estimated difference;

`lower`

, `upper`

Confidence interval for the difference in mean as reported by the t-test;

`df`

The number of degrees of freedom assumed by the t-test;

`repno`

Identifies each replication, between 1 and 500;

`dgm`

Identifies each data-generating mechanism: 1 corresponds to normal data with equal variance between the groups, 2 is normal data with unequal variance, 3 and 4 are skewed data (simulated from a Gamma distribution) with equal and unequal variance between groups, respectively;

`method`

Analysis method: 1 represents the t-test with pooled variance, while 2 represents the t-test with unpooled variance.

## Note

Further details on this simulation study can be found in the R script used to generate this dataset, available on GitHub: https://github.com/ellessenne/rsimsum/blob/master/data-raw/tt-data.R

## Examples