Calculate the proportion of maximum (POM) score given a minimum and maximum score.
Details
The minimum and maximum score for calculating the proportion of maximum could be the possible or observed minimum and maximum, respectively. Using the possible minimum and maximum would yield the proportion of maximum possible score. Using the observed minimum and maximum would yield the proportion of minimum and maximum observed score. If the minimum and maximum possible scores are not specified, the observed minimum and maximum are used.
See also
Other conversion:
convert.magic()
,
convertHoursAMPM()
,
convertToHours()
,
convertToMinutes()
,
convertToSeconds()
,
percentileToTScore()
Examples
# Prepare Data
v1 <- sample(1:9, size = 1000, replace = TRUE)
# Calculate Proportion of Maximum Possible (by specifying the minimum and maximum possible)
pom(v1, min = 0, max = 10)
#> [1] 0.2 0.2 0.7 0.1 0.5 0.8 0.2 0.5 0.4 0.7 0.9 0.1 0.4 0.7 0.2 0.9 0.5 0.9
#> [19] 0.9 0.8 0.7 0.4 0.9 0.2 0.1 0.2 0.5 0.6 0.5 0.5 0.2 0.3 0.5 0.4 0.7 0.1
#> [37] 0.5 0.1 0.3 0.6 0.2 0.8 0.1 0.1 0.5 0.2 0.2 0.4 0.2 0.9 0.3 0.7 0.1 0.6
#> [55] 0.6 0.9 0.1 0.9 0.3 0.7 0.6 0.9 0.8 0.7 0.8 0.1 0.2 0.5 0.9 0.1 0.5 0.4
#> [73] 0.8 0.5 0.6 0.7 0.4 0.9 0.4 0.9 0.6 0.5 0.9 0.7 0.5 0.9 0.6 0.4 0.4 0.1
#> [91] 0.6 0.1 0.9 0.1 0.6 0.4 0.2 0.1 0.7 0.5 0.1 0.1 0.3 0.8 0.2 0.8 0.7 0.2
#> [109] 0.9 0.4 0.8 0.4 0.8 0.8 0.2 0.7 0.9 0.7 0.6 0.9 0.9 0.3 0.7 0.9 0.3 0.1
#> [127] 0.6 0.8 0.1 0.1 0.9 0.9 0.2 0.7 0.3 0.5 0.5 0.9 0.5 0.7 0.6 0.7 0.8 0.8
#> [145] 0.4 0.9 0.6 0.4 0.1 0.9 0.6 0.3 0.9 0.5 0.6 0.2 0.4 0.2 0.3 0.5 0.5 0.3
#> [163] 0.1 0.2 0.5 0.6 0.4 0.1 0.9 0.4 0.1 0.2 0.8 0.2 0.3 0.4 0.6 0.1 0.4 0.7
#> [181] 0.4 0.9 0.8 0.4 0.6 0.9 0.8 0.3 0.8 0.9 0.5 0.1 0.6 0.3 0.6 0.6 0.6 0.8
#> [199] 0.2 0.9 0.2 0.2 0.6 0.3 0.1 0.6 0.1 0.4 0.1 0.5 0.8 0.4 0.6 0.5 0.9 0.9
#> [217] 0.6 0.8 0.4 0.4 0.4 0.6 0.1 0.7 0.8 0.8 0.4 0.4 0.7 0.6 0.7 0.1 0.7 0.1
#> [235] 0.6 0.7 0.7 0.8 0.5 0.4 0.2 0.7 0.2 0.8 0.5 0.7 0.8 0.8 0.7 0.4 0.9 0.2
#> [253] 0.2 0.4 0.4 0.9 0.9 0.1 0.9 0.7 0.5 0.9 0.2 0.8 0.6 0.9 0.2 0.8 0.6 0.4
#> [271] 0.7 0.9 0.6 0.8 0.1 0.3 0.2 0.5 0.9 0.9 0.5 0.9 0.4 0.6 0.3 0.3 0.3 0.8
#> [289] 0.1 0.6 0.6 0.4 0.6 0.6 0.5 0.1 0.7 0.8 0.9 0.7 0.1 0.4 0.7 0.5 0.9 0.5
#> [307] 0.6 0.6 0.4 0.8 0.6 0.3 0.4 0.8 0.7 0.5 0.6 0.8 0.9 0.7 0.8 0.2 0.8 0.2
#> [325] 0.5 0.4 0.2 0.6 0.5 0.8 0.4 0.7 0.8 0.3 0.7 0.7 0.2 0.3 0.8 0.5 0.9 0.1
#> [343] 0.9 0.3 0.5 0.3 0.4 0.1 0.3 0.9 0.9 0.8 0.7 0.8 0.6 0.1 0.7 0.9 0.9 0.1
#> [361] 0.7 0.1 0.2 0.1 0.7 0.7 0.1 0.7 0.6 0.6 0.1 0.5 0.9 0.6 0.4 0.4 0.7 0.9
#> [379] 0.3 0.4 0.1 0.7 0.8 0.8 0.6 0.8 0.8 0.8 0.2 0.1 0.7 0.4 0.9 0.7 0.6 0.4
#> [397] 0.8 0.2 0.3 0.4 0.5 0.2 0.5 0.7 0.9 0.5 0.6 0.6 0.3 0.3 0.3 0.9 0.4 0.1
#> [415] 0.3 0.9 0.8 0.5 0.5 0.2 0.1 0.5 0.9 0.6 0.3 0.3 0.1 0.3 0.4 0.4 0.7 0.5
#> [433] 0.5 0.6 0.3 0.4 0.4 0.8 0.4 0.5 0.9 0.4 0.1 0.3 0.7 0.9 0.6 0.3 0.1 0.4
#> [451] 0.2 0.8 0.1 0.4 0.5 0.3 0.6 0.5 0.1 0.4 0.5 0.3 0.2 0.8 0.1 0.4 0.1 0.9
#> [469] 0.3 0.8 0.7 0.6 0.8 0.5 0.5 0.4 0.2 0.7 0.3 0.1 0.5 0.8 0.4 0.1 0.5 0.8
#> [487] 0.5 0.6 0.8 0.7 0.7 0.6 0.5 0.4 0.9 0.8 0.9 0.6 0.7 0.6 0.1 0.3 0.1 0.4
#> [505] 0.4 0.9 0.4 0.6 0.4 0.3 0.7 0.9 0.9 0.7 0.7 0.4 0.9 0.2 0.8 0.9 0.7 0.5
#> [523] 0.1 0.9 0.5 0.7 0.8 0.7 0.6 0.9 0.2 0.7 0.7 0.5 0.3 0.8 0.5 0.9 0.5 0.1
#> [541] 0.8 0.6 0.6 0.4 0.1 0.3 0.7 0.2 0.4 0.1 0.2 0.9 0.4 0.1 0.2 0.6 0.2 0.6
#> [559] 0.7 0.6 0.9 0.9 0.7 0.8 0.1 0.1 0.4 0.5 0.5 0.4 0.7 0.8 0.1 0.3 0.2 0.4
#> [577] 0.7 0.8 0.7 0.5 0.1 0.9 0.1 0.4 0.4 0.4 0.2 0.8 0.5 0.7 0.7 0.2 0.9 0.3
#> [595] 0.3 0.8 0.2 0.3 0.4 0.3 0.6 0.3 0.9 0.8 0.2 0.4 0.7 0.6 0.4 0.1 0.5 0.5
#> [613] 0.6 0.8 0.3 0.2 0.6 0.4 0.4 0.2 0.3 0.9 0.1 0.1 0.4 0.6 0.1 0.5 0.2 0.5
#> [631] 0.2 0.6 0.9 0.4 0.2 0.6 0.2 0.1 0.9 0.8 0.7 0.3 0.3 0.9 0.7 0.1 0.4 0.7
#> [649] 0.3 0.6 0.9 0.7 0.9 0.6 0.2 0.9 0.9 0.2 0.1 0.8 0.4 0.9 0.2 0.4 0.6 0.8
#> [667] 0.3 0.1 0.2 0.4 0.5 0.5 0.6 0.1 0.7 0.9 0.6 0.7 0.5 0.8 0.9 0.2 0.6 0.4
#> [685] 0.4 0.4 0.4 0.2 0.3 0.3 0.8 0.6 0.8 0.2 0.8 0.7 0.8 0.4 0.7 0.8 0.3 0.4
#> [703] 0.7 0.5 0.8 0.5 0.7 0.9 0.2 0.6 0.1 0.5 0.5 0.7 0.6 0.5 0.3 0.9 0.3 0.3
#> [721] 0.5 0.7 0.3 0.5 0.3 0.2 0.4 0.6 0.6 0.7 0.4 0.9 0.9 0.4 0.3 0.3 0.3 0.3
#> [739] 0.9 0.3 0.6 0.9 0.8 0.7 0.7 0.5 0.3 0.2 0.9 0.7 0.9 0.9 0.7 0.1 0.7 0.2
#> [757] 0.5 0.3 0.4 0.6 0.6 0.7 0.4 0.7 0.3 0.4 0.4 0.4 0.7 0.5 0.1 0.2 0.2 0.7
#> [775] 0.9 0.6 0.6 0.4 0.4 0.4 0.6 0.9 0.9 0.8 0.2 0.6 0.1 0.3 0.5 0.6 0.6 0.1
#> [793] 0.7 0.5 0.6 0.4 0.1 0.1 0.5 0.6 0.7 0.5 0.2 0.8 0.3 0.5 0.7 0.3 0.7 0.2
#> [811] 0.7 0.8 0.8 0.6 0.3 0.1 0.5 0.3 0.3 0.6 0.1 0.8 0.1 0.1 0.3 0.4 0.9 0.4
#> [829] 0.3 0.4 0.5 0.2 0.1 0.8 0.8 0.3 0.6 0.2 0.8 0.5 0.1 0.1 0.3 0.7 0.2 0.2
#> [847] 0.4 0.5 0.3 0.1 0.6 0.3 0.5 0.5 0.1 0.6 0.2 0.3 0.4 0.4 0.4 0.9 0.1 0.6
#> [865] 0.8 0.7 0.4 0.8 0.4 0.3 0.4 0.2 0.1 0.6 0.2 0.9 0.4 0.6 0.8 0.8 0.6 0.1
#> [883] 0.9 0.7 0.2 0.8 0.9 0.9 0.2 0.7 0.2 0.7 0.4 0.5 0.8 0.7 0.2 0.8 0.9 0.1
#> [901] 0.4 0.2 0.1 0.6 0.6 0.3 0.2 0.5 0.2 0.5 0.5 0.4 0.1 0.6 0.3 0.5 0.8 0.2
#> [919] 0.7 0.6 0.6 0.5 0.1 0.5 0.5 0.1 0.6 0.5 0.2 0.7 0.8 0.7 0.7 0.5 0.5 0.5
#> [937] 0.3 0.4 0.6 0.5 0.4 0.6 0.1 0.3 0.5 0.8 0.1 0.7 0.4 0.8 0.1 0.7 0.3 0.1
#> [955] 0.4 0.5 0.6 0.4 0.2 0.7 0.3 0.8 0.1 0.8 0.4 0.7 0.5 0.1 0.2 0.3 0.6 0.3
#> [973] 0.7 0.4 0.2 0.2 0.6 0.4 0.6 0.5 0.3 0.3 0.3 0.3 0.6 0.1 0.7 0.1 0.1 0.6
#> [991] 0.8 0.3 0.6 0.9 0.7 0.8 0.9 0.3 0.7 0.2
# Calculate Proportion of Maximum Observed
pom(v1)
#> [1] 0.125 0.125 0.750 0.000 0.500 0.875 0.125 0.500 0.375 0.750 1.000 0.000
#> [13] 0.375 0.750 0.125 1.000 0.500 1.000 1.000 0.875 0.750 0.375 1.000 0.125
#> [25] 0.000 0.125 0.500 0.625 0.500 0.500 0.125 0.250 0.500 0.375 0.750 0.000
#> [37] 0.500 0.000 0.250 0.625 0.125 0.875 0.000 0.000 0.500 0.125 0.125 0.375
#> [49] 0.125 1.000 0.250 0.750 0.000 0.625 0.625 1.000 0.000 1.000 0.250 0.750
#> [61] 0.625 1.000 0.875 0.750 0.875 0.000 0.125 0.500 1.000 0.000 0.500 0.375
#> [73] 0.875 0.500 0.625 0.750 0.375 1.000 0.375 1.000 0.625 0.500 1.000 0.750
#> [85] 0.500 1.000 0.625 0.375 0.375 0.000 0.625 0.000 1.000 0.000 0.625 0.375
#> [97] 0.125 0.000 0.750 0.500 0.000 0.000 0.250 0.875 0.125 0.875 0.750 0.125
#> [109] 1.000 0.375 0.875 0.375 0.875 0.875 0.125 0.750 1.000 0.750 0.625 1.000
#> [121] 1.000 0.250 0.750 1.000 0.250 0.000 0.625 0.875 0.000 0.000 1.000 1.000
#> [133] 0.125 0.750 0.250 0.500 0.500 1.000 0.500 0.750 0.625 0.750 0.875 0.875
#> [145] 0.375 1.000 0.625 0.375 0.000 1.000 0.625 0.250 1.000 0.500 0.625 0.125
#> [157] 0.375 0.125 0.250 0.500 0.500 0.250 0.000 0.125 0.500 0.625 0.375 0.000
#> [169] 1.000 0.375 0.000 0.125 0.875 0.125 0.250 0.375 0.625 0.000 0.375 0.750
#> [181] 0.375 1.000 0.875 0.375 0.625 1.000 0.875 0.250 0.875 1.000 0.500 0.000
#> [193] 0.625 0.250 0.625 0.625 0.625 0.875 0.125 1.000 0.125 0.125 0.625 0.250
#> [205] 0.000 0.625 0.000 0.375 0.000 0.500 0.875 0.375 0.625 0.500 1.000 1.000
#> [217] 0.625 0.875 0.375 0.375 0.375 0.625 0.000 0.750 0.875 0.875 0.375 0.375
#> [229] 0.750 0.625 0.750 0.000 0.750 0.000 0.625 0.750 0.750 0.875 0.500 0.375
#> [241] 0.125 0.750 0.125 0.875 0.500 0.750 0.875 0.875 0.750 0.375 1.000 0.125
#> [253] 0.125 0.375 0.375 1.000 1.000 0.000 1.000 0.750 0.500 1.000 0.125 0.875
#> [265] 0.625 1.000 0.125 0.875 0.625 0.375 0.750 1.000 0.625 0.875 0.000 0.250
#> [277] 0.125 0.500 1.000 1.000 0.500 1.000 0.375 0.625 0.250 0.250 0.250 0.875
#> [289] 0.000 0.625 0.625 0.375 0.625 0.625 0.500 0.000 0.750 0.875 1.000 0.750
#> [301] 0.000 0.375 0.750 0.500 1.000 0.500 0.625 0.625 0.375 0.875 0.625 0.250
#> [313] 0.375 0.875 0.750 0.500 0.625 0.875 1.000 0.750 0.875 0.125 0.875 0.125
#> [325] 0.500 0.375 0.125 0.625 0.500 0.875 0.375 0.750 0.875 0.250 0.750 0.750
#> [337] 0.125 0.250 0.875 0.500 1.000 0.000 1.000 0.250 0.500 0.250 0.375 0.000
#> [349] 0.250 1.000 1.000 0.875 0.750 0.875 0.625 0.000 0.750 1.000 1.000 0.000
#> [361] 0.750 0.000 0.125 0.000 0.750 0.750 0.000 0.750 0.625 0.625 0.000 0.500
#> [373] 1.000 0.625 0.375 0.375 0.750 1.000 0.250 0.375 0.000 0.750 0.875 0.875
#> [385] 0.625 0.875 0.875 0.875 0.125 0.000 0.750 0.375 1.000 0.750 0.625 0.375
#> [397] 0.875 0.125 0.250 0.375 0.500 0.125 0.500 0.750 1.000 0.500 0.625 0.625
#> [409] 0.250 0.250 0.250 1.000 0.375 0.000 0.250 1.000 0.875 0.500 0.500 0.125
#> [421] 0.000 0.500 1.000 0.625 0.250 0.250 0.000 0.250 0.375 0.375 0.750 0.500
#> [433] 0.500 0.625 0.250 0.375 0.375 0.875 0.375 0.500 1.000 0.375 0.000 0.250
#> [445] 0.750 1.000 0.625 0.250 0.000 0.375 0.125 0.875 0.000 0.375 0.500 0.250
#> [457] 0.625 0.500 0.000 0.375 0.500 0.250 0.125 0.875 0.000 0.375 0.000 1.000
#> [469] 0.250 0.875 0.750 0.625 0.875 0.500 0.500 0.375 0.125 0.750 0.250 0.000
#> [481] 0.500 0.875 0.375 0.000 0.500 0.875 0.500 0.625 0.875 0.750 0.750 0.625
#> [493] 0.500 0.375 1.000 0.875 1.000 0.625 0.750 0.625 0.000 0.250 0.000 0.375
#> [505] 0.375 1.000 0.375 0.625 0.375 0.250 0.750 1.000 1.000 0.750 0.750 0.375
#> [517] 1.000 0.125 0.875 1.000 0.750 0.500 0.000 1.000 0.500 0.750 0.875 0.750
#> [529] 0.625 1.000 0.125 0.750 0.750 0.500 0.250 0.875 0.500 1.000 0.500 0.000
#> [541] 0.875 0.625 0.625 0.375 0.000 0.250 0.750 0.125 0.375 0.000 0.125 1.000
#> [553] 0.375 0.000 0.125 0.625 0.125 0.625 0.750 0.625 1.000 1.000 0.750 0.875
#> [565] 0.000 0.000 0.375 0.500 0.500 0.375 0.750 0.875 0.000 0.250 0.125 0.375
#> [577] 0.750 0.875 0.750 0.500 0.000 1.000 0.000 0.375 0.375 0.375 0.125 0.875
#> [589] 0.500 0.750 0.750 0.125 1.000 0.250 0.250 0.875 0.125 0.250 0.375 0.250
#> [601] 0.625 0.250 1.000 0.875 0.125 0.375 0.750 0.625 0.375 0.000 0.500 0.500
#> [613] 0.625 0.875 0.250 0.125 0.625 0.375 0.375 0.125 0.250 1.000 0.000 0.000
#> [625] 0.375 0.625 0.000 0.500 0.125 0.500 0.125 0.625 1.000 0.375 0.125 0.625
#> [637] 0.125 0.000 1.000 0.875 0.750 0.250 0.250 1.000 0.750 0.000 0.375 0.750
#> [649] 0.250 0.625 1.000 0.750 1.000 0.625 0.125 1.000 1.000 0.125 0.000 0.875
#> [661] 0.375 1.000 0.125 0.375 0.625 0.875 0.250 0.000 0.125 0.375 0.500 0.500
#> [673] 0.625 0.000 0.750 1.000 0.625 0.750 0.500 0.875 1.000 0.125 0.625 0.375
#> [685] 0.375 0.375 0.375 0.125 0.250 0.250 0.875 0.625 0.875 0.125 0.875 0.750
#> [697] 0.875 0.375 0.750 0.875 0.250 0.375 0.750 0.500 0.875 0.500 0.750 1.000
#> [709] 0.125 0.625 0.000 0.500 0.500 0.750 0.625 0.500 0.250 1.000 0.250 0.250
#> [721] 0.500 0.750 0.250 0.500 0.250 0.125 0.375 0.625 0.625 0.750 0.375 1.000
#> [733] 1.000 0.375 0.250 0.250 0.250 0.250 1.000 0.250 0.625 1.000 0.875 0.750
#> [745] 0.750 0.500 0.250 0.125 1.000 0.750 1.000 1.000 0.750 0.000 0.750 0.125
#> [757] 0.500 0.250 0.375 0.625 0.625 0.750 0.375 0.750 0.250 0.375 0.375 0.375
#> [769] 0.750 0.500 0.000 0.125 0.125 0.750 1.000 0.625 0.625 0.375 0.375 0.375
#> [781] 0.625 1.000 1.000 0.875 0.125 0.625 0.000 0.250 0.500 0.625 0.625 0.000
#> [793] 0.750 0.500 0.625 0.375 0.000 0.000 0.500 0.625 0.750 0.500 0.125 0.875
#> [805] 0.250 0.500 0.750 0.250 0.750 0.125 0.750 0.875 0.875 0.625 0.250 0.000
#> [817] 0.500 0.250 0.250 0.625 0.000 0.875 0.000 0.000 0.250 0.375 1.000 0.375
#> [829] 0.250 0.375 0.500 0.125 0.000 0.875 0.875 0.250 0.625 0.125 0.875 0.500
#> [841] 0.000 0.000 0.250 0.750 0.125 0.125 0.375 0.500 0.250 0.000 0.625 0.250
#> [853] 0.500 0.500 0.000 0.625 0.125 0.250 0.375 0.375 0.375 1.000 0.000 0.625
#> [865] 0.875 0.750 0.375 0.875 0.375 0.250 0.375 0.125 0.000 0.625 0.125 1.000
#> [877] 0.375 0.625 0.875 0.875 0.625 0.000 1.000 0.750 0.125 0.875 1.000 1.000
#> [889] 0.125 0.750 0.125 0.750 0.375 0.500 0.875 0.750 0.125 0.875 1.000 0.000
#> [901] 0.375 0.125 0.000 0.625 0.625 0.250 0.125 0.500 0.125 0.500 0.500 0.375
#> [913] 0.000 0.625 0.250 0.500 0.875 0.125 0.750 0.625 0.625 0.500 0.000 0.500
#> [925] 0.500 0.000 0.625 0.500 0.125 0.750 0.875 0.750 0.750 0.500 0.500 0.500
#> [937] 0.250 0.375 0.625 0.500 0.375 0.625 0.000 0.250 0.500 0.875 0.000 0.750
#> [949] 0.375 0.875 0.000 0.750 0.250 0.000 0.375 0.500 0.625 0.375 0.125 0.750
#> [961] 0.250 0.875 0.000 0.875 0.375 0.750 0.500 0.000 0.125 0.250 0.625 0.250
#> [973] 0.750 0.375 0.125 0.125 0.625 0.375 0.625 0.500 0.250 0.250 0.250 0.250
#> [985] 0.625 0.000 0.750 0.000 0.000 0.625 0.875 0.250 0.625 1.000 0.750 0.875
#> [997] 1.000 0.250 0.750 0.125