| get_capl_demo_data {capl} | R Documentation |
Generate CAPL-2 demo (fake) raw data.
Description
This function generates a data frame of CAPL-2 demo (fake) raw data containing the 60 required variables that the capl package needs to compute
scores and interpretations.
Usage
get_capl_demo_data(n = 500)
Arguments
n |
A numeric (integer) vector representing the number of rows of data to generate. By default, |
Value
Returns a data frame containing the 60 required variables that the capl package needs to compute scores and interpretations.
Examples
capl_demo_data <- get_capl_demo_data(10000)
str(capl_demo_data)
# 'data.frame': 10000 obs. of 60 variables:
# $ age : int 9 10 8 8 11 9 12 NA 10 7 ...
# $ gender : chr "Girl" "Boy" "Boy" "Girl" ...
# $ pacer_lap_distance : num 20 15 20 20 15 15 15 20 15 20 ...
# $ pacer_laps : int 5 112 150 46 51 82 43 189 55 91 ...
# $ plank_time : int 238 66 95 173 299 172 169 33 277 152 ...
# $ camsa_skill_score1 : int 9 3 7 NA 8 14 13 14 11 11 ...
# $ camsa_time1 : int 17 33 26 22 31 28 NA 24 12 11 ...
# $ camsa_skill_score2 : int 12 11 12 9 NA 9 7 10 14 11 ...
# $ camsa_time2 : int 15 13 15 20 12 15 29 12 12 18 ...
# $ steps1 : int 29663 30231 3157 5751 23362 28283 ...
# $ time_on1 : chr "05:00" "5:13am" "07:00" "8:00am" ...
# $ time_off1 : chr "11:57pm" "10:57 pm" "10:57 pm" "11:57pm" ...
# $ non_wear_time1 : int 38 47 38 40 36 32 36 82 25 51 ...
# $ steps2 : int 29703 9142 5424 23763 3645 28625 3019 ...
# $ time_on2 : chr "07:00" "07:48am" "6:07" "06:00" ...
# $ time_off2 : chr "22:00" "21:00" "8:17pm" "10:57 pm" ...
# $ non_wear_time2 : int 5 34 41 60 84 18 19 47 66 55 ...
# $ steps3 : int 20380 10987 5885 13518 14385 30680 14120 ...
# $ time_on3 : chr "07:00" "06:00" "6:07" "8:00am" ...
# $ time_off3 : chr "11:13pm" "11:57pm" "21:00" "08:30pm" ...
# $ non_wear_time3 : int 54 70 16 36 72 16 89 86 26 81 ...
# $ steps4 : int 13224 20817 19640 2326 16605 25783 23078 ...
# $ time_on4 : chr "07:48am" "5:13am" "5:13am" "6:07" ...
# $ time_off4 : chr "11:13pm" NA "22:00" "23:00" ...
# $ non_wear_time4 : int 2 48 61 NA 81 81 2 30 35 14 ...
# $ steps5 : int 28408 8845 5802 6966 24499 18561 13771 ...
# $ time_on5 : chr "5:13am" NA "06:00" "6:07" ...
# $ time_off5 : chr "11:13pm" NA "11:57pm" "11:13pm" ...
# $ non_wear_time5 : int 75 10 70 45 77 75 90 61 17 72 ...
# $ steps6 : int 9581 18237 6377 3282 16898 15649 19890 ...
# $ time_on6 : chr "6:13" "6:07" "07:00" "8:00am" ...
# $ time_off6 : chr "11:57pm" "21:00" "10:57 pm" "8:17pm" ...
# $ non_wear_time6 : int 13 14 37 28 14 86 89 19 78 40 ...
# $ steps7 : int 8205 15351 16948 19442 4026 10830 4644 ...
# $ time_on7 : chr "05:00" NA "07:48am" "6:07" ...
# $ time_off7 : chr NA "22:00" "08:30pm" "08:30pm" ...
# $ non_wear_time7 : int 84 40 42 34 13 58 67 86 64 46 ...
# $ self_report_pa : int 4 NA NA 7 1 1 6 7 6 6 ...
# $ csappa1 : int 2 1 1 1 2 1 4 3 3 3 ...
# $ csappa2 : int 3 3 1 4 4 2 3 1 4 4 ...
# $ csappa3 : int 1 2 4 1 2 4 1 4 4 1 ...
# $ csappa4 : int 4 1 3 4 2 3 1 2 2 4 ...
# $ csappa5 : int 2 4 2 2 4 1 1 1 3 1 ...
# $ csappa6 : int 2 2 2 3 4 3 2 3 1 1 ...
# $ why_active1 : int 5 2 5 5 2 5 1 1 5 1 ...
# $ why_active2 : int 4 5 2 4 3 1 5 1 4 1 ...
# $ why_active3 : int 2 1 4 3 1 2 1 5 3 3 ...
# $ feelings_about_pa1 : int 4 1 5 3 4 4 4 5 4 5 ...
# $ feelings_about_pa2 : int 5 3 4 4 1 2 5 2 1 3 ...
# $ feelings_about_pa3 : int 3 4 3 5 1 1 4 2 1 4 ...
# $ pa_guideline : int 1 3 3 1 4 1 1 4 4 2 ...
# $ crf_means: int 2 3 2 3 4 1 3 4 1 3 ...
# $ ms_means : int 1 1 4 2 4 4 2 1 1 3 ...
# $ sports_skill : int 3 1 1 4 1 3 1 1 3 2 ...
# $ pa_is : int 10 1 9 5 7 7 8 3 7 10 ...
# $ pa_is_also : int 7 1 7 9 1 6 3 4 3 7 ...
# $ improve : int 3 3 3 3 3 3 10 3 3 3 ...
# $ increase : int 8 8 10 4 8 8 8 9 8 8 ...
# $ when_cooling_down : int 5 2 2 2 2 2 4 2 3 7 ...
# $ heart_rate : int 4 9 7 4 4 4 4 4 5 7 ...
[Package capl version 1.42 Index]