Function reference • activAnalyzer

All functions

average_results(): Average results over valid days

compute_accumulation_metrics(): Compute activity accumulation metrics

compute_bmr(): Compute Basal Metabolic Rate (BMR)

compute_intensity_distri_metrics(): Compute intensity distribution metrics

compute_mets(): Compute metabolic equivalent of task (MET) values

compute_pro_actigraph_score(): Compute PROactive monitor-based physical activity score for C-PPAC tool

compute_pro_score_cppac(): Provide score for each question of the C-PPAC

compute_pro_score_dppac(): Provide score for each question of the D-PPAC

create_fig_mvpa(): Create a figure showing the mean daily MVPA time

create_fig_mx_by_day(): Create a radar plot for MX metrics relating to each day of the measurement of physical behavior

create_fig_mx_summary(): Create a radar plot for the mean or median MX metrics relating to the measurement of physical behavior

create_fig_pal(): Create a figure showing the mean daily Physical Activity Level (PAL)

create_fig_ratio_mvpa_sed(): Create a figure showing the mean daily MVPA/SED ratio

create_fig_res_by_day(): Create a figure with metrics shown for each day

create_fig_sed(): Create a figure showing the mean daily sedentary (SED) time

create_fig_steps(): Create a figure showing the mean daily step count

create_flextable_summary(): Create a formatted table of results

do_all_analyses(): Do all analyses at once

get_guidelines_status(): Get WHO physical activity guidelines status

get_ig_results(): Get intensity gradient values and graphics

get_pa_period_info(): Get relevant missing physical activity information indicated by the user of the app

get_pal_status(): Get FAO physical activity level (PAL) status (http://www.fao.org/3/y5686e/y5686e07.htm#bm07.3)

get_ratio_mvpa_sed_comment(): Get comment about the MVPA/SED ratio

mark_intensity(): Add intensity metrics

mark_wear_time(): Mark dataset for nonwear/wear time

plot_data(): Plot accelerometer data for each day

plot_data_with_intensity(): Plot accelerometer data for each day with both nonwear time and physical activity intensity categories

prepare_dataset(): Prepare accelerometer data

rasch_transform(): Compute Rasch transformation for PROactive scores

read_agd(): Read activity counts from an *.agd file

read_agd_raw(): Read an *.agd file, with no post-processing

recap_by_day(): Summarize results by day

run_app(): Run the Shiny Application