check.norms: Standard errors for norm statistics

In vandenman/mokken: Conducts Mokken Scale Analysis

Description

The function presents standard errors for the mean, standard deviation, standard scores, stanine boundaries, and percentiles based on a vector of test scores (Oosterhuis, Van der Ark, and Sijtsma, in press).

Usage

check.norms(y, nice.output = TRUE)

Arguments

y	numerical vector. Typically a numerical vector of length N, representing the test scores of N respondents. Missing values are not allowed
nice.output	Logical: If TRUE, norm statistics and standard errors are combined in an a single object of class noquote

Value

list of five components:

(1) mean: Sample mean and its standard error (noquote).

(2) sd: Sample standard deviation and its standard error (noquote).

(3) z: For each unique testscore, the test score, its frequency, the corresponding estimated standard score and its standard error (noquote).

(4) sta9: The estimates of the 8 boundaries of the stanines and their standard error (noquote).

(5) z: For each unique testscore, the test score, its frequency, the corresponding estimated percentile rank and its standard error (noquote).

Author(s)

L. A. van der Ark [e-mail] and H. E. M. Oosterhuis

References

Oosterhuis, H. E. M., Van der Ark, L. A., and Sijtsma, K. (in press). Standard errors and confidence intervals of norm statistics for educational and psychological tests. Psychometrika. doi:10.1007/s11336-016-9535-8

See Also

DS14, recode, twoway

Examples

  data(DS14)

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

  # Negative affectivity
  Na <- X[, c(1, 3, 6, 8, 10, 11, 14)] 

  # Social inhibition
  Si <- X[, c(2, 4, 5, 7, 9, 12, 13)] 

  # Norms
  check.norms(rowSums(Na))
  check.norms(rowSums(Si))

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