lambda3: Compute Guttman's Lambda 3 Coefficient (Coefficent Alpha)

In Lambda4: Collection of Internal Consistency Reliability Coefficients.

Description

Often recognized as Cronbach's alpha, Guttman's Lambda 3 can be used to estimate reliability when the data can be split in parallel forms.

Usage

  lambda3(x, item.stats.max = 12, missing = "complete")

Arguments

x	Can be either a data matrix or a covariance matrix
item.stats.max	items statistics shown if the number of items are less than this value.
missing	how to handle missing values.

Value

lambda3	The unstandardized and standardized lambda3 estimate.
item.stats	If the input data was a covariance matrix then this is a table of reliability estimates if an item was dropped. If the input data is a data frame then the mean, standard deviation, and number of observations are also included.
items	The number of items.
item.stats.max	The maximum number of item to display the item.stats table (user specified).

Author(s)

Tyler Hunt [e-mail]

References

Cronbach L (1951). "Coefficient Alpha and the Internal Structure of Tests." Psychometrika, 16, 297-334. Guttman L (1945). "A Basis for Analyzing Test-Retest Reliability." Psychometrika, 10, 255-282.

Examples

lambda3(Rosenberg)

Example output

Coefficient Alpha (Guttman's Lambda 3 Coefficient) 

Unstandardized 
0.88

Standardized 
0.883

Item Statistics 
                 Mean    SD Obs If.Dropped
SEFailureR      3.336 0.734 837      0.852
SENoGoodR       2.860 0.901 837      0.850
SEAble          3.133 0.597 837      0.870
SEUselessR      2.654 0.848 837      0.857
SENoProudR      3.174 0.811 837      0.852
SEGoodQualities 3.302 0.629 837      0.859
SEWorth         3.337 0.627 837      0.860
SEPositive      3.149 0.671 837      0.852
SERespectR      2.362 0.822 837      0.873
SESatisfied     3.168 0.708 837      0.852

Lambda4 documentation built on May 2, 2019, 1:05 p.m.