Compare Repeated Measurements by Group

Takes data and returns a summary table of continuous variable based on a categorical variable. This summary is repeat by time groups to help describe a circadian pattern.

circ_compare_groups(data, x, y, time)

Arguments

data	Dataframe containing all the following variables
x	Continuous variable of interest (x ~ y)
y	Grouping variable to apply to the cvar (x ~ y). Must be binary for t-test, otherwise will return data set without pvalues
time	Name of the time-dependent variable, usually hours

Value

Returns a dataframe that has the time variable, the categorical variable, and the statistics (including p-value) of the continuous variable

Details

Applies a simple data transformation to identify the summary statistics of the data frame by the stated variables. Results in a mean, standard deviation, and standard error term. This data is also used for making a t-test based table, which can then also be graphed in ggcircadian.

Examples

data("twins")
circ_compare_groups(data = twins, x = "rDYX", y = "sad_cat", time = "hour")
#> # A tibble: 120 x 6
#>    hour  sad_cat  mean     n    sd     se
#>    <fct> <fct>   <dbl> <int> <dbl>  <dbl>
#>  1 8     bdi_I    3.22   426 0.780 0.0378
#>  2 9     bdi_I    3.24   417 0.810 0.0397
#>  3 10    bdi_I    3.28   379 0.799 0.0411
#>  4 11    bdi_I    3.19   324 0.808 0.0449
#>  5 12    bdi_I    3.00   338 0.807 0.0439
#>  6 13    bdi_I    2.89   434 0.681 0.0327
#>  7 14    bdi_I    2.95   449 0.689 0.0325
#>  8 15    bdi_I    3.05   459 0.749 0.0350
#>  9 16    bdi_I    3.02   469 0.730 0.0337
#> 10 17    bdi_I    2.85   469 0.724 0.0334
#> # … with 110 more rows