Question

(a) Discuss the primary scales of measurement. Develop an example of each.

(b) What is the appropriate way to assess the internal consistency of a multi-item scale with sets of items designed to measure different aspects of a multi-dimensional construct?

(c) Discuss construct validity and the types of construct validity.

4) (a) Discuss the primary scales of measurement Develop an example of each. (b) What is the appropriate way to assess the internal consistency of a multi- item scale with sets of items designed to measure different aspects of a multi- dimensional construct? (c) Discuss construct validity and the types of construct validity. (15 marks)

Answer 1

a.)  There are four major scales of measurement of variables: nominal, ordinal, interval and ratio.

Nominal: A nominal scale is a scale of measurement used to assign events or objects into discrete categories. This form of scale does not require the use of numeric values or categories ranked by class, but simply unique identifiers to label each distinct category. Often regarded as the most basic form of measurement, nominal scales are used to categorize and analyze data in many disciplines. Eamples: sex, religion etc.

Ordinal:The ordinal scale contains things that you can place in order. It measures a variable in terms of magnitude, or rank. Ordinal scales tell us relative order, but give us no information regarding differences between the categories. The ordinal scale has the property of both identity and magnitude.example- movie rating,military rank.

Interval: Interval scales are numeric scales in which we know both the order and the exact differences between the values. The classic example of an interval scale is Celsius temperature because the difference between each value is the same. For example, the difference between 60 and 50 degrees is a measurable 10 degrees, as is the difference between 80 and 70 degrees.

Ratio: It refers to the level of measurement in which the attributes composing are measured on specific numerical scores or value that have equal distance between attributes or points along the scale and are based on "true zero" point. Example- distance, speed , weight, temperature.

B)

Internal consistency is usually measured with Cronbach's alpha, a statistic calculated from the pairwise correlations between items. It value ranges between negative infinity and one. Coefficient alpha will be negative whenever there is greater within-subject variability than between-subject variability.

A common method for calculation of Internal consistency

Cronbach's alpha	Internal consistency
0.9 ≤ α	Excellent
0.8 ≤ α < 0.9	Good
0.7 ≤ α < 0.8	Acceptable
0.6 ≤ α < 0.7	Questionable
0.5 ≤ α < 0.6	Poor
α < 0.5	Unacceptable

Higher value of alpha are not necessarily desirable, as this indicates that the items may be redundant.The goal in designing a reliable instrument is for scores on similar items to be related (internally consistent), but for each to contribute some unique information as well. Note further that Cronbach's alpha is necessarily higher for tests measuring more narrow constructs, and lower when more generic, broad constructs are measured. This phenomenon, along with a number of other reasons, argue against using objective cut-off values for internal consistency measures. Alpha is also a function of the number of items, so shorter scales will often have lower reliability estimates yet still be preferable in many situations because they are lower burden.

C.) Construct validity is established experimentally to demonstrate that a survey distinguishes between people who do and do not have certain characteristics. For example, a survey researcher who claims constructive validity for a measure of satisfaction will have to demonstrate in a scientific manner that satisfied respondents behave differently from dissatisfied respondents.

There are 2 types of construct validity:

1.Convergent validity, a parameter often used in sociology, psychology, and other behavioral sciences, refers to the degree to which two measures of constructs that theoretically should be related, are in fact related. Convergent validity, along with discriminant validity, is a subtype of construct validity. Convergent validity can be established if two similar constructs correspond with one another, while discriminant validity applies to two dissimilar constructs that are easily differentiated.

2.Discriminant validity: is demonstrated by evidence that measures of constructs that theoretically should not be highly related to each other are, in fact, not found to be highly correlated to each other. Practically speaking, discriminant validity coefficients should be noticeably smaller in magnitude than convergent validity coefficients.