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Last data update: 2014.03.03

R: Computing Missing Rate

missing.rate

R Documentation

Computing Missing Rate

Description

Computes the missing rate from acceleromater data.

Usage

missing.rate(label, flag, mark.missing = 0, time.range = c("09:00", "20:59"))

Arguments

`label`	an N by 2 matrix including the labels corresponding to `PA` matrix. The first column, `label[,1]`, includes the person id, and the second column, `label[,2]`, includes the day label of 1 to 7, indicating Sunday to Saturday.
`flag`	an N by T matrix with the values of either 1 or 0 which indicating wearing or missing. This matrix can be created from `create.flag()`.
`mark.missing`	If `mark.missing = 0` (default), the nonwearing time is marked by 0 while the wearing time is marked by 1 in flag matrix. If `mark.missing = 1`, it is the opposite.
`time.range`	Define the time range during which the missing rate is computed. Default is 9am-9pm, coded by `time.range = c("09:00", "20:59")`.

Value

Numeric value of a missing rate between 0 to 1. The output is a list of

`total`	total missing rate during the time range
`table`	missing rate table by subject

Author(s)

Jung Ae Lee <jungaeleeb@gmail.com>

References

[1] Lee JA, Gill J (2016). Missing value imputation for physical activity data measured by accelerometer. Statistical Methods in Medical Research.

Examples

## missing rate calculation: uncomment and run the code below
# data(acceldata); attach(acceldata)
# missing.rate(label, flag, mark.missing=0, time.range=c("09:00", "20:59"))$total  

## create missing flag by 60 min criterion
# flag60 = create.flag(PA, window=60, mark.missing=0)
# mr = missing.rate(label, flag60, mark.missing=0, time.range=c("09:00", "20:59"))
# mr$total  #28.1 percent

## missing proportion by days
# mean(mr$table < 0.1)   # 45.8 percent