irv: Calculates the intra-individual response variability (IRV)

In careless: Procedures for Computing Indices of Careless Responding

Calculates the intra-individual response variability (IRV)

Description

The IRV is the "standard deviation of responses across a set of consecutive item responses for an individual" (Dunn, Heggestad, Shanock, & Theilgard, 2018, p. 108). By default, the IRV is calculated across all columns of the input data. Additionally it can be applied to different subsets of the data. This can detect degraded response quality which occurs only in a certain section of the questionnaire (usually the end). Whereas Dunn et al. (2018) propose to mark persons with low IRV scores as outliers - reflecting straightlining responses, Marjanovic et al. (2015) propose to mark persons with high IRV scores - reflecting highly random responses (see References).

Usage

irv(x, na.rm = TRUE, split = FALSE, num.split = 3)

Arguments

x	a matrix of data (e.g. survey responses)
na.rm	logical indicating whether to calculate the IRV for a person with missing values.
split	logical indicating whether to additionally calculate the IRV on subsets of columns (of equal length).
num.split	the number of subsets the data is to be split in.

Author(s)

Francisco Wilhelm [e-mail]

References

Dunn, A. M., Heggestad, E. D., Shanock, L. R., & Theilgard, N. (2018). Intra-individual Response Variability as an Indicator of Insufficient Effort Responding: Comparison to Other Indicators and Relationships with Individual Differences. Journal of Business and Psychology, 33(1), 105-121. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s10869-016-9479-0")}

Marjanovic, Z., Holden, R., Struthers, W., Cribbie, R., & Greenglass, E. (2015). The inter-item standard deviation (ISD): An index that discriminates between conscientious and random responders. Personality and Individual Differences, 84, 79-83. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.paid.2014.08.021")}

Examples

# calculate the irv over all items
irv_total <- irv(careless_dataset)

#calculate the irv over all items + calculate the irv for each quarter of the questionnaire
irv_split <- irv(careless_dataset, split = TRUE, num.split = 4)
boxplot(irv_split$irv4) #produce a boxplot of the IRV for the fourth quarter

careless documentation built on Oct. 1, 2023, 9:06 a.m.