cov.lambda4: Compute Covariance Maximized Lambda4
In JackStat/Lambda4: Collection of Internal Consistency Reliability Coefficients.

Description Usage Arguments Value Author(s) Examples

This code estimates maximized lambda4, a split-half reliability estimate. The function splits the halves by specifying a two column list of paired inter-item covariances in descending order. It then calculates Guttman's lambda4 on every possible split-half while preserving the inter-item pairings. The function then returns a list of the Lambda4s and then takes the minimum, maximum, median, and mean of the list. This calculation is most appropiately applied to tests with multiple factors.

1
2
3

  cov.lambda4(x, method = "Hunt", missing = "complete",
    show.lambda4s = FALSE, show.splits = FALSE,
    standardize = FALSE)

`x`	Can be either a data matrix or a covariance matrix.
`method`	Can specify either "Hunt" or "Osburn".
`missing`	How to handle missing values.
`show.lambda4s`	If TRUE then the estimates for each split are included in the output.
`show.splits`	If TRUE then a binary matrix is exported that describes the ways the items were split.
`standardize`	When TRUE results are standardized by using the correlation matrix instead of the covariance matrix for computation.

`estimates`	The mean, median, max, and min of the split-half reliabilities.
`lambda4s`	A vector of maximized split-half reliabilities.
`method`	The method chosen. Either "Hunt" or "Osburn".
`Analysis.Details`	Returns the number of variables and the number of split-half reliabilities.
`Splits`	The binary indicators of the splits for the min, max, and median split-half reliability.
`show.splits`	Logical argument selected to show the splits.
`show.lambdas4s`	Logical argument selected to show the split-half reliabilities.