User Guide

Chapter
37
Reliability
Analysis
Reliability analysis allows you to study the properties of measurement scales and the
items that m
ake them up. The Reliability Analysis procedure calculates a number of
commonly used measures of scale reliability and also provides information about the
relationships between individual items in the scale. Intraclass correlation coefficients
can be used
to compute interrater reliability estimates.
Example. Does my questionnaire measure customer satisfaction in a useful way?
Using reliability analysis, you can determine the extent to which the items in
your ques
tionnaire are related to each other, you can get an overall index of the
repeatability or internal consistency of the scale as a whole, and you can identify
problem items that should be excluded from the scale.
Statisti
cs.
Descriptives for each variable and for the scale, summary statistics across
items, inter-item correlations and covariances, reliability estimates, ANOVA table,
intraclass correlation coefficients, Hotelling’s T
2
, and Tukey’s test of additivity.
Models. T
he following models of reliability are available:
 Alpha (
Cronbach).
This is a model of internal consistency, based on the average
inter-item correlation.
 Split-half. This model splits the scale into two parts and examines the correlation
between the parts.
 Guttman. This model computes Guttman’s lower bounds for true reliability.
 Parallel. This model assumes that all items have equal variances and equal error
varianc
es across replications.
 Strict
parallel.
This model makes the assumptions of the parallel model and also
assumes equal means across items.
Data. Da
ta can be dichotomous, ordinal, or interval, but they should be coded
numerically.
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