Average results over valid days

This function computes, using valid days only, the mean of each of the metrics obtained using the recap_by_day function. The median can also be obtained with an appropriate configuration of the function.

Usage

average_results(data, minimum_wear_time = 10, fun = c("mean", "median"))

Arguments

data

A dataframe obtained using the prepare_dataset, mark_wear_time, mark_intensity, and then the recap_by_day functions.

minimum_wear_time

A numeric value (in hours) to set the minimum wear time duration for validating a day.

fun

A character value indicating whether means or medians should be computed.

Value

A dataframe.

Examples

# \donttest{
file <- system.file("extdata", "acc.agd", package = "activAnalyzer")
mydata <- prepare_dataset(data = file)
mydata_with_wear_marks <- mark_wear_time(
    dataset = mydata, 
    TS = "TimeStamp", 
    to_epoch = 60,
    cts  = "vm",
    frame = 90, 
    allowanceFrame = 2, 
    streamFrame = 30
    )
#> frame is 90
#> streamFrame is 30
#> allowanceFrame is 2
mydata_with_intensity_marks <- mark_intensity(
    data = mydata_with_wear_marks, 
    col_axis = "vm", 
    equation = "Sasaki et al. (2011) [Adults]",
    sed_cutpoint = 200, 
    mpa_cutpoint = 2690, 
    vpa_cutpoint = 6167, 
    age = 32,
    weight = 67,
    sex = "male",
    )
#> You have computed intensity metrics with the mark_intensity() function using the following inputs: 
#>     axis = vm
#>     sed_cutpoint = 200 counts/min
#>     mpa_cutpoint = 2690 counts/min
#>     vpa_cutpoint = 6167 counts/min
#>     equation = Sasaki et al. (2011) [Adults]
#>     age = 32
#>     weight = 67
#>     sex = male
summary_by_day <- recap_by_day(
    data = mydata_with_intensity_marks, 
    age = 32, 
    weight = 67, 
    sex = "male",
    valid_wear_time_start = "07:00:00",
    valid_wear_time_end = "22:00:00"
    )$df_all_metrics
#> Joining with `by = join_by(date)`
#> Joining with `by = join_by(date)`
#> Joining with `by = join_by(date)`
#> You have computed results with the recap_by_day() function using the following inputs: 
#>          age = 32
#>          weight = 67
#>          sex = male
average_results(data = summary_by_day, minimum_wear_time = 10)
#> # A tibble: 1 × 38
#>   valid_days wear_time total_counts_axis1 total_counts_vm axis1_per_min
#>        <int>     <dbl>              <dbl>           <dbl>         <dbl>
#> 1          5      768.            513109.         970345.          687.
#> # ℹ 33 more variables: vm_per_min <dbl>, minutes_SED <dbl>, minutes_LPA <dbl>,
#> #   minutes_MPA <dbl>, minutes_VPA <dbl>, minutes_MVPA <dbl>,
#> #   percent_SED <dbl>, percent_LPA <dbl>, percent_MPA <dbl>, percent_VPA <dbl>,
#> #   percent_MVPA <dbl>, ratio_mvpa_sed <dbl>, mets_hours_mvpa <dbl>,
#> #   total_kcal <dbl>, pal <dbl>, total_steps <dbl>, max_steps_60min <dbl>,
#> #   max_steps_30min <dbl>, max_steps_20min <dbl>, max_steps_5min <dbl>,
#> #   max_steps_1min <dbl>, peak_steps_60min <dbl>, peak_steps_30min <dbl>, …
# }