TPI_cutoff: Identification of Careless Response Using Time Per Item

In manateelab/EMAeval-R-Package: Identification of Careless Responses and Responders in EMA Data

Description

TPI_cutoff returns dataframe of assessment flagged by Time Per Item per assessment cutoff value.

Usage

TPI_cutoff(
  data,
  cutoff,
  condition,
  ttc.colnames,
  number.items,
  mandatory.response,
  item.colnames,
  ID.colname
)

Arguments

data	dataframe to be analyzed.
cutoff	numeric cutoff value for Time per Item, 'default' value set to 1 second.
condition	character string of condition that is desired for comparison of data to TPI cutoff value, i.e <, >=, etc. 'Default' logic set to "<=".
ttc.colnames	vector of column names of "Start Time" and "End Time" to calculate time to complete, also can be "Completion Time" if already calculated.
number.items	integer, number of items per assessment.
mandatory.response	logical value based on whether response to items in each assessment were mandatory to complete.
item.colnames	vector of column names of all items/questions to be used to calculate time per item.
ID.colname	character string of column name for ID of assessment.

Details

This function creates the dataframe that includes the ID and index of assessments that met the cutoff criterion for Time Per Item per assessment. If an assessment has a Time Per Item less than or equal to the cutoff value, it will be flagged and placed in the dataframe.

Value

The item "ttc.colnames" must be the names of columns, corresponding to Start Time and End Time, ordered ttc.colnames = c("StartTime", "EndTime") start time first, followed by end time. If the data includes assessment duration, then list the column name that corresponds with assessment completion: ttc.colnames = "SurveyDuration"

The item "mandatory.response" should be TRUE if participants were required to complete all items per assessment. This item should be FALSE if not all items were required to be completed per assessment.

If there is variability in the items that are asked, mark the item "mandatory.response" as FALSE and ensure that "item.colnames" includes all items.

References

Jaso, B.A., Kraus, N.I., Heller, A.S. (2020) Identification of careless responding in ecological momentary assessment: from post-hoc analyses to real-time data monitoring.

See Also

SD_cutoff for a similar function, using Standard Deviation rather than Time per Item.

Perc_Mode_cutoff for a similar function, using Percent of Items at Mode rather than Time per Item.

See the following functions for more information on Careless Response Identification in EMA: flagging_df, flagging_plots, longstringr, Combined_cutoff, and Combined_cutoff_percent

manateelab/EMAeval-R-Package documentation built on Oct. 13, 2021, 6:48 a.m.