twoway: Two-way imputation

In vandenman/mokken: Conducts Mokken Scale Analysis

Description

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

Usage

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

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.

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).

Value

The result is X for which the missing values have been replaced by imputed values.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.

Author(s)

L. A. van der Ark [e-mail]

References

Bernaards, C. A. and 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.

Sijtsma, K. and Van der Ark, L. A. (2003). Investigation and treatment of missing item scores in test and questionnaire data. Multivariate Behavioral Research, 38, 505-528.

Van Ginkel, J. R., Van dec Ark, L. A., and Sijtsma, K. (2007). Multiple imputation of item scores in test and questionnaire data, and influence on psychometric results. Multivariate Behavioral Research, 42, 387-414.

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)

vandenman/mokken documentation built on April 12, 2020, 4:06 a.m.