Create a formatted table of results

The function generates a formatted table with both means and medians of the metrics obtained following the physical behavior measurement.

Usage

create_flextable_summary(
  results_summary_means,
  results_summary_medians,
  language = c("en", "fr"),
  metrics = c("all", "volume", "step_acc", "int_distri"),
  epoch_label = "60s"
)

Arguments

results_summary_means

A dataframe with mean results obtained using the prepare_dataset, mark_wear_time, mark_intensity, recap_by_day, and then the average_results functions.

results_summary_medians

A dataframe with median results obtained using the prepare_dataset, mark_wear_time, mark_intensity, recap_by_day, and then the average_results functions.

language

A character value for setting the language with which the figure should be created: en for english; fr for french.

metrics

A character value for setting the metrics to be shown in the figure. "volume" refers to "activity volume" metrics, step_acc" refers to "step accumulation" metrics, and "int_distri" refers to intensity distribution metrics. By default, the function provides all computed metrics.

epoch_label

A character value to be pasted into the names of the variables to build the figure

Value

A flextable object

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", 
    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
results_summary_means <- average_results(
    data = summary_by_day, 
    minimum_wear_time = 10, 
    fun = "mean"
    )
results_summary_medians <- average_results(
    data = summary_by_day, 
    minimum_wear_time = 10, 
    fun = "median"
    )
create_flextable_summary(
    results_summary_means,
    results_summary_medians, 
    language = "en"
    )
Metric
Daily mean | median
Number of valid days
5
Wear time (min)
767.8 (12:47:48) | 770.0 (12:50:00)
Axis 1 total counts
513108.6 | 359125.0
VM total counts
970344.6 | 806592.1
Axis 1 mean (counts/min)
686.7 | 498.8
VM mean (counts/min)
1290.6 | 1047.5
SED time (min)
283.0 (04:43:00) | 292.0 (04:52:00)
LPA time (min)
391.8 (06:31:48) | 407.0 (06:47:00)
MPA time (min)
57.8 (00:57:48) | 51.0 (00:51:00)
VPA time (min)
35.2 (00:35:12) | 4.0 (00:04:00)
MVPA time (min)
93.0 (01:33:00) | 77.0 (01:17:00)
SED wear time proportion (%)
36.9 | 40.0
LPA wear time proportion (%)
50.6 | 50.2
MPA wear time proportion (%)
7.6 | 7.1
VPA wear time proportion (%)
4.9 | 0.6
MVPA wear time proportion (%)
12.4 | 10.7
Ratio MVPA / SED
0.33 | 0.27
Total MVPA MET-hr
8.63 | 5.56
Total kcal
1730.04 | 1548.93
PAL
1.99 | 1.78
Total steps
14869 | 14056
Max step acc. 60 min (steps/min)
57.85 | 50.90
Max step acc. 30 min (steps/min)
70.05 | 71.63
Max step acc. 20 min (steps/min)
74.29 | 83.05
Max step acc. 5 min (steps/min)
95.20 | 112.80
Max step acc. 1 min (steps/min)
109.00 | 118.00
Peak step acc. 60 min (steps/min)
74.60 | 70.88
Peak step acc. 30 min (steps/min)
86.60 | 86.73
Peak step acc. 20 min (steps/min)
91.75 | 97.70
Peak step acc. 5 min (steps/min)
105.24 | 117.20
Peak step acc. 1 min (steps/min)
109.00 | 118.00
Intensity gradient
-1.51 | -1.36
M1/3 (counts/60s)
229.9 | 200.9
M120 (counts/60s)
3089.0 | 2064.0
M60 (counts/60s)
4040.2 | 3054.7
M30 (counts/60s)
4978.6 | 4721.2
M15 (counts/60s)
5730.7 | 5763.9
M5 (counts/60s)
6558.7 | 6160.1
# }