data_summary_coverage: Obtain the non-zero coverage for both two conditions and the...
In dfConn: Dynamic Functional Connectivity Analysis

Description Usage Arguments Value Examples

Summarize the data from dynamic functional connectivity linear mixed modeling.

1	data_summary_coverage(dataList.CI, save_res = FALSE, output_dir = NULL)

`dataList.CI`	list, a list of data matrices which include the confidence interval estimates obtained from linear mixed models.
`save_res`	logical, whether to save the result or not, if true, an output directory should be provided
`output_dir`	character, directory for output files

A list which contains 9 data frames:

coverage.zero.cond.diff: Percentage of estimates for condition difference that are within 95% confidence interval with a center of zero.
coverage.zero.cond.1: Percentage of estimates for condition 1 that are within 95% confidence interval with a center of zero.
coverage.zero.cond.2: Percentage of estimates for condition 2 that are below 95% confidence interval with a center of zero.
coverage.below.zero.cond.2: Percentage of estimates for condition 2 that are below 95% confidence interval with a center of zero.
coverage.below.zero.cond.diff: Percentage of estimates for condition difference that are below 95% confidence interval with a center of zero.
coverage.below.zero.cond.1: Percentage of estimates for condition 1 that are below 95% confidence interval with a center of zero.
coverage.above.zero.cond.diff: Percentage of estimates for condition difference that are above 95% confidence interval with a center of zero.
coverage.above.zero.cond.1: Percentage of estimates for condition 1 that are above 95% confidence interval with a center of zero.
coverage.above.zero.cond.2: Percentage of estimates for condition 1 that are above 95% confidence interval with a center of zero.

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# Summarize the output of linear mixed effect model for dynamic functional connectivity
data(DynModel_results)
data_summary_coverage(DynModel_results$est_CI)