Question 1

The standard error of measurement is a function of which two factors?

Accepted Answer

The standard error of measurement is a function of the reliability of the test and the variability of test scores. Reliability measures the consistency of scores, so a test with high reliability will have a lower standard error of measurement. Variability measures the spread or range of scores, so a test with greater variability will have a higher standard error of measurement. Therefore, option C is the correct answer. Option A is incorrect because it only considers reliability and not variability. Option B is incorrect because it suggests that the standard error of measurement is a function of only variability and range of test scores, which is not entirely true. Option D is incorrect because sample size is not one of the factors that directly affects the standard error of measurement.

Question 2

Changes over time in the attribute being measured are considered sources of measurement error in

Accepted Answer

Test-retest reliability estimates compare the results of the same test given to the same participants at different points in time. Changes in the attribute being measured during this interval can lead to measurement error, making test-retest reliability vulnerable to this source of error. Split-half, alternate forms, and internal consistency reliability estimates do not involve measurement over time, so changes in the attribute being measured over time are not sources of error for these types of reliability estimates.

Question 3

Reliability of a test is affected by

Accepted Answer

All of the factors listed can affect the reliability of a test. The characteristics of the people taking the test, such as their age or cognitive ability, can impact their performance and ultimately affect the consistency and dependability of the test results. The method used to estimate reliability, such as test-retest, split-half, or inter-rater reliability, can also influence the degree to which a test is reliable. Finally, the intended use of the test scores, such as making important decisions about people's lives or assessing small differences in performance, can impact the level of reliability needed for the test to be considered valid and useful. Therefore, all of these factors should be taken into account when evaluating the reliability of a test.

Question 4

_________ scores are typically more reliable than ________ scores.

Accepted Answer

Composite scores are typically more reliable than difference scores because they average out individual test score variability, reducing the impact of measurement error.

Question 5

If individual differences are _______, reliability will be _______.

Accepted Answer

When individual differences are small, it is harder to distinguish between individuals, leading to lower reliability in measurements or assessments.

Question 6

True Score Theory of Reliability was developed by

Accepted Answer

True Score Theory, also known as Classical Test Theory, was developed by Charles Spearman. This theory posits that each test score reflects a true score component plus an error component.

Question 7

Reliability of a test can be increased by

Accepted Answer

Increasing the number of test items has been shown to increase reliability, while decreasing the number of items or decreasing inter-item correlations can actually decrease reliability. Therefore, the best choice is to increase the number of test items (option C).

Question 8

A test in which items are trivially easy, but which is administered under strict time limits, is called a(n)

Accepted Answer

A speed test is a type of test in which the items are deliberately made easy, but the time limit is set up in such a way that only the most able individuals can complete all of the items. This type of test is used to measure processing speed and mental agility.

Question 9

The ________ the correlation between X and Y, the ________ the reliability of their difference scores.

Accepted Answer

If the correlation between X and Y is high, it means that the two variables are strongly related and change together. Therefore, the difference scores between them will be less reliable because any measurement error or variability in one variable will also affect the other variable, causing more variability in the difference scores. On the other hand, if the correlation between X and Y is low, it means that the two variables are weakly related and change independently of each other. Thus, the difference scores will be more reliable because any variability in one variable will have less impact on the other variable, resulting in less variability in the difference scores.

Question 10

A pure speed test should have an odd-even split-half reliability of about

Accepted Answer

A pure speed test, where all items are of similar difficulty and the main factor is how quickly a person can respond, should have a high split-half reliability. This is because both halves of the test measure the same ability (speed) in a similar manner, leading to a correlation close to 1.00.

Question 11

Variability expected on the basis of measurement error is best represented by

Accepted Answer

The standard error of measurement is the most appropriate choice for representing variability expected on the basis of measurement error. This value represents the amount of error that can be expected in a person's score due to test administration and scoring inconsistencies. A higher standard error of measurement indicates greater variability due to measurement error.

Question 12

If a test has a reliability coefficient of 0.00 and a standard error of 0.00, the test is

Accepted Answer

A reliability coefficient of 0.00 indicates the test is unreliable, meaning it does not consistently measure what it is supposed to measure. However, a standard error of 0.00 suggests that the scores are perfectly consistent or accurate, with no variability in repeated measurements under the same conditions.

Question 13

In general, _______ could be expected to be higher than _______, because more factors contribute to measurement error in the latter.

Accepted Answer

Internal consistency estimates are typically higher than alternate form correlations because internal consistency focuses on the consistency of performance across items within a single test form, which is generally more stable and less prone to error than comparing performance across different forms of a test, where more factors can introduce variability.

Question 14

If a person's true score is 110 on a test with a standard error of measurement of 3.7 and a mean of 100, we would expect 95% of the person's test scores to fall within

Accepted Answer

We can use the formula: true score ± (1.96 x standard error of measurement)
110 ± (1.96 x 3.7) = 102.75 to 117.25
Thus, we would expect 95% of the person's test scores to fall within the range of 102.75 to 117.25.

Question 15

If the standard error of a test increases, the range in which you could be confident that true scores will fall would

Accepted Answer

The standard error represents the degree of uncertainty in an estimation or measurement. A larger standard error indicates that there is more variability in the data and less precision in the estimate, which means that we would need a wider range to be confident that true scores will fall within it. Therefore, if the standard error increases, the range in which we could be confident that true scores will fall would also increase.

Question 16

A method of estimating the true correlation between X and Y given the correlation between two unreliable measures of X and Y is by using the

Accepted Answer

The method referred to in the question is known as the correction for attenuation, which involves adjusting the correlation coefficient obtained from two unreliable measures to estimate the true correlation between X and Y. The formula for this correction involves dividing the observed correlation by the square root of the product of the reliability coefficients of the two measures. Therefore, the best choice would be C, as the other options (shrinkage coefficient, reliability coefficient, and corrected reliability index) are not directly related to this method of estimating the true correlation.

Question 17

Which reliability coefficient reflects the more reliable test?

Accepted Answer

A reliability coefficient of 0.90 reflects a high level of reliability, indicating that the test is consistent in its measurement over time or across different people. Coefficients of 0.30 and -0.85 indicate low levels of reliability and suggest that the test may produce highly inconsistent results. A coefficient of 2.58 does not represent a reliability coefficient, but rather a z-score that has no bearing on the reliability of a test.

Question 18

The most useful method of assessing the reliability of highly speeded tests is the

Accepted Answer

The answer of The most useful method of assessing the...

Question 19

Because of measurement error, the variability of test scores is _________ the variability of true scores.

Accepted Answer

The variability of test scores is larger than the variability of true scores because measurement error adds additional variability to the observed scores.

Question 20

A test can be _________, yet not __________.

Accepted Answer

Reliability refers to the consistency or stability of test scores over time or across different examiners, while validity refers to the extent to which a test measures what it is supposed to measure. Thus, a test can be reliable (consistent) but not valid (it may be measuring something other than what it is supposed to be measuring). However, a test cannot be valid without also being reliable, as it must be consistent in order to accurately measure the intended construct. Option A correctly reflects this relationship between reliability and validity.

Quiz 7: Using and Interpreting Information About Test Reliability