# PsyB01 Chapter 5&6.doc

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University of Toronto Scarborough

Psychology

PSYB01H3

Connie Boudens

Fall

Description

Chapter 5 Measurement Concepts
Reliability of measures
- Reliability refers to the consistency or stability of a measure of
behaviour
- A reliable measure does not fluctuate from one reading to the
next; if the measure does fluctuate, there is error in the
measurement device
- Any measure that you can make can be thought of as comprising
two components:
o True score, which is the real score on the variable
o Measurement error
- An unreliable measure of intelligence contains considerable
measurement error and so does not provide an accurate
indication of an individuals true intelligence
- A reliable measure of intelligence one that contains little
measurement error will yield an identical (or nearly identical)
intelligence score each time the same individual is measured
- The measurement error in an unreliable test is revealed in the
greater variability of its results of the unreliable test
- It is important to use a reliable measure since researchers only
measure each person only once
- Trying to study the behaviour using unreliable measures is a
waste of time because the results will be unstable and unable to
be replicated
- Reliability is most likely to be achieved when researchers use
careful measurement procedures
- In many areas, reliability can be increased by making multiple
measures; this is most commonly seen when assessing
personality traits and cognitive abilities (e.g. a survey with more
items [questions] is more reliable)
- We can assess the stability of measures using correlation
coefficients, which is a number that tells us how strongly two
variables are related to each other - Pearson product-moment correlation coefficient (symbolized as r)
can range from 0.00 to +1.00 and 0.00 to -0.00
o A correlation of 0.00 tells us that the two variables are not
related at all; the closer a correlation is to either +1.00 or
-1.00, the stronger the relationship
o The positive and negative signs provide information about
the direction of the relationship
When the correlation coefficient is positive, there is a
positive linear relationship high scores on one
variable are associated with high scores on the
second variable
A negative linear relationship is when high scores on
one variable are associated with low scores on the
second variable
- To assess the reliability of a measure, we will need to obtain at
least two scores on the measure from many individuals; if the
measure is reliable, the two scores should be very similar (e.g. a
Pearson correlation coefficient that relates the two scores should
be a high positive correlation)
Test-Retest Reliability
- Test-retest reliability is assessed by measuring the same
individuals at two points in time; having two scores for each
person would allow the researcher to calculate the correlation
coefficient and determine the relationship between the first test
score and the retest score
- If many people have very similar scores, we conclude that the
measure reflects true scores rather than measurement error
- For most measures, the reliability coefficient should probably be
at least .80
- Given that test-retest reliability involves administering the same
test twice, the correlation might be artificially high because the
individuals remember how they responded the first time
o To solve this problem, alternate forms reliability is used,
which involves administering two different forms of the
same tests to the same individuals at two points in time Internal Consistency Reliability
- Internal consistency reliability is the assessment of reliability
using responses at only one point in time; because all items
(questions) measure the same variable, they should yield similar
or consistent results
- Split-half reliability is the correlation of an individuals total score
on one half of the test with the total score on the other half
o One drawback with this method is that it does not take into
account each individual items role in a measures
reliability
- Cronbachs alpha is based on the individual items; here the
researcher calculates the correlation of each item with every
other item
o The value of alpha is based on the average of all the
interitem correlation coefficients and the number of items
in the measure; more items indicate higher reliability
- Item-total correlations is the examination of the correlation of
each item score with the total score based on all items
- Item-total correlations and Cronbachs alpha are very informative
because they provide information about each individual item;
items that do not correlate with the other items can be
eliminated from the measure to increase reliability
Interrater Reliability
- Interrater reliability is the extent to which raters agree in their
observations; high interrater reliability is obtained when most of
the observations result in the same judgment
Reliability and Accuracy of Measures
- Reliability tells us about measurement error but it does not tell us
about whether we have a good measure of the variable of
interest
Construct Validity of Measures
- If something is valid, it is true in the sense that it is supported
by available evidence

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