TwoRegression (version 1.1.1)

TwoRegression-Package: Develop and Apply Two-Regression Algorithms

Description

The TwoRegression package is designed to make working with two-regression algorithms quick, easy, and accurate.

Associated References

Hibbing PR, LaMunion SR, Kaplan AS, & Crouter SE (2018). Estimating energy expenditure with ActiGraph GT9X Inertial Measurement Unit. Medicine and Science in Sports and Exercise. 50(5), 1093-1102. doi: 10.1249/MSS.0000000000001532

Crouter, S. E., Clowers, K. G., & Bassett Jr, D. R. (2006). A novel method for using accelerometer data to predict energy expenditure. Journal of Applied Physiology, 100(4), 1324-1331.

Crouter, S. E., Kuffel, E., Haas, J. D., Frongillo, E. A., & Bassett Jr, D. R. (2010). Refined Two-Regression Model for the ActiGraph Accelerometer. Medicine and Science in Sports and Exercise, 42(5), 1029.

Crouter, S. E., Horton, M., & Bassett Jr, D. R. (2012). Use of a Two-regression model for estimating energy expenditure in children. Medicine and Science in Sports and Exercise, 44(6), 1177.

Details

Originally, the package was designed to house the algorithms created by Hibbing et al. (2018). Since then, support has been added for other algorithms, including Crouter et al. (2006), Crouter et al. (2010), and Crouter et al. (2012). Functionality has also been added to develop and cross-validate new two-regression algorithms. The package RcppRoll has also been invoked to speed up rolling coefficient of variation calculations.

Examples

# \donttest{

## Datasets

  data(count_data, package = "TwoRegression")
  data(all_data, package = "TwoRegression")

## Crouter 2006-2012 models

  TwoRegression(
    count_data, "Crouter 2006",
    movement_var = "Axis1", time_var = "time"
  )

  TwoRegression(
    count_data, "Crouter 2010",
    movement_var = "Axis1", time_var = "time"
  )

  TwoRegression(
    count_data, "Crouter 2012", movement_var = "Axis1",
    time_var = "time", model = "VA", check = FALSE
  )

  TwoRegression(
    count_data, "Crouter 2012", movement_var = "Vector.Magnitude",
    time_var = "time", model = "VM", check = FALSE
  )

## Hibbing 2018 models (can be vectorized)

  all_data$ENMO_CV10s <- NULL
  all_data$GVM_CV10s  <- NULL
  all_data$Direction  <- NULL

  result <- TwoRegression(
    all_data, "Hibbing 2018", gyro_var = "Gyroscope_VM_DegPerS",
    direction_var = "mean_magnetometer_direction",
    site = c("Left Ankle", "Right Ankle"), algorithm = 1:2
  )

  utils::head(result)

# }