twoway function

Two-way imputation

Returns a single or multiple completed data sets using two-way imputation with normally distributed errors.

twoway(X, nCompletedDataSets = 1, minX = defaultMinX, maxX = defaultMaxX, seed = FALSE)

Details

For single imputation (nCompletedDataSets == 1, default) the function returns an object of the same class as X, for multiple imputation (nCompletedDataSets > 1) the function returns a list. References for two-way imputation include Bernaards and Sijtsma (2000), Sijtsma and Van der Ark (2003), and Van Ginkel, Van der Ark, and Sijtsma (2007).

Arguments

• X: matrix or data frame of integer data containing the score of now(X) respondents to nicol(X) items. Typically X contains missing values.
• nCompletedDataSets: Number of completed data sets.
• minX: Minimum item score. By default, the minimum item score is the lowest score found in the data.
• maxX: Maximum item score. By default, the maximum item score is the highest score found in the data.
• seed: Seed for random sampling. If seed = FALSE (default), no seed is given, otherwise seed must be a numeric value. Replications having the same seed result in exactly the same outcome value.

Returns

The result is X for which the missing values have been replaced by imputed values. For multiple imputations, the result is a list of matrices/data frames. For single imputations, the result is a matrix/data frame.

References

Bernaards, C. A., & Sijtsma, K. (2000). Influence of simple imputation and EM methods on factor analysis when item nonresponse in questionnaire data is nonignorable Multivariate Behavioral Research, 35, 321-364. tools:::Rd_expr_doi("10.1207/S15327906MBR3503_03")

Sijtsma, K., & Van der Ark, L. A. (2003). Investigation and treatment of missing item scores in test and questionnaire data. Multivariate Behavioral Research, 38, 505-528. tools:::Rd_expr_doi("10.1207/s15327906mbr3804_4")

Van Ginkel, J. R., Van dec Ark, L. A., & Sijtsma, K. (2007). Multiple imputation of item scores in test and questionnaire data, and influence on psychometric results. Multivariate aBehavioral Research, 42, 387-414. tools:::Rd_expr_doi("10.1080/00273170701360803")

Author(s)

L. A. van der Ark L.A.vanderArk@uva.nl

See Also

DS14, recode

Examples

data(DS14)

  # Handle missing data and recode negatively worded items
  X <- DS14[, 3 : 16]
  X <- twoway(X)
  X <- recode(X, c(1, 3))
  head(X)