bdotsFit: Fit nlme curves to grouped observations

In bdots: Bootstrapped Differences of Time Series

Fit nlme curves to grouped observations

Description

Creates observation level curves to use in bdotsBoot

Usage

bdotsFit(
  data,
  subject,
  time,
  y,
  group,
  curveType = doubleGauss(concave = TRUE),
  cor = TRUE,
  numRefits = 0,
  cores = 0,
  verbose = FALSE,
  ...
)

Arguments

data	Dataset used
subject	Column name of dataset containing subject identifiers
time	Column name containing time variable
y	Column name containing outcome of interest
group	Character vector containing column names of groups. Can be greater than one
curveType	See details/vignette
cor	Boolean. Autocorrelation?
numRefits	Integer indicating number of attempts to fit an observation if the first attempt fails
cores	number of cores. Default is 0, indicating half cores available
verbose	currently not used
...	Secret

Details

This is step one of the three step bdots process. Things should be more or less straight forward. The only tricky part involves curveType. For now know that one can use doubleGauss(concave = TRUE/FALSE) or logistic(). Should be passed in as a call. See the vignette on customizing this

Value

Object of class 'bdotsObj', inherits from data.table

Examples

## Not run: 
res <- bdotsFit(data = cohort_unrelated,
                subject = "Subject",
                time = "Time",
                y = "Fixations",
                group = c("Group", "LookType"),
                curveType = doubleGauss(concave = TRUE),
                cor = TRUE,
                numRefits = 2,
                cores = 0,
                verbose = FALSE)

## End(Not run)

bdots documentation built on Jan. 7, 2023, 1:18 a.m.