L4 Reliability

Question 1

How many Cronbach’s alpha assumptions?

Answer 1

4

Question 2

Cronbach’s alpha assumption 1

Answer 2

-items are essentially tau-equivalent (each item is an equally strong indicator of the true score scores, but they may differ by a constant. Items can have different means)

Question 3

Cronbach’s Alpha Assumption 2

Answer 3

Each item’s error term is uncorrelated with every other item’s error term.

Question 4

Cronbach’s Alpha Assumption 3

Answer 4

-The error scores are uncorrelated with the true scores. (Assumption associated with all forms of reliability).

Question 5

Cronbach’s alpha assumption 4

Answer 5

-the items used to generate a composite score measure only 1 attribute or construct.

Question 6

Standard coefficient alpha

Answer 6

You apply it to scores that have been converted from a raw score to a standardised score. E.g to z-scores.

Question 7

Types of reliability assumption models

Answer 7

Parallel
Tau-Equivalent
Essentially Tau-Equivalent
Congeneric

Question 8

Parallel

Answer 8

• Equal true score variance
• Equal means
• Equal variance.

Question 9

Tau-Equivalent

Answer 9

• Equal true score variance
• equal means
• unequal error variances

Question 10

Essentially Tau-Equivalent

Answer 10

• Equal true score variance
• Unequal means
• Unequal error variances

Question 11

Congeneric

Answer 11

• Unequal true score variance (but all greater than zero)
• Unequal means
• Unequal error variances

Question 12

Factors affecting reliability

Answer 12

• Added items to a test must be parallel to other items to increase cronbach’s alpha.
• but they really need only be essentially tau-equivalent items and possibly even congeneric in some cases.
• main thing to consider is “will adding this item reduce the mean inter-item correlation”

Question 13

Sample Homogeneity

Answer 13

-Homogenous samples will yield lower reliability estimates than a heterogeneous sample.

Question 14

Standard error of measurement (SEM)

Answer 14

Amount of error “around” a point estimate (observed score) in standard deviation form.

Question 15

Confidence interval

Answer 15

• A confidence interval can be estimated around a point-estimate (observed score)
• A confidence interval reflects a range of values that is often interpreted as a range in which the true score is likely to fall.

Question 16

Standard error of estimate

Answer 16

Typically, people calculate the 95% confidence interval around a point estimate (observed score).

Question 17

2 types of correlations

Answer 17

Observed score correlation and true score correlation

Question 18

Observed Score Correlation

Answer 18

• the correlation you get based on the data you have
• will be compromised to the degree to which there is measurement error in your data.
• In practice this means that the maximum correlation between two sets of scores is less than 1.0

Question 19

True Score Correlation

Answer 19

• a hypothetical correlation you can estimate if you know the reliabilities associated with the scores.
• Not compromised by measurement error.