Measurement & Scaling Techniques

 

MEASUREMENT AND SCALING

• Measurement is the process of observing and recording the observations that are collected as part of research. 
• The recording of the Measurement and Scaling Techniques observations may be in terms of numbers or other symbols to characteristics of objects according to certain prescribed rules. 
• The respondent’s, characteristics are feelings, attitudes, opinions, etc.

👉 There are two reasons for assigning numbers to any characteristics:

1. First, the numbers facilitate further statistical analysis of the data obtained.
2. Second, numbers facilitate the communication of measurement rules and results. The most important aspect of measurement is the specification of rules for assigning numbers to characteristics. The rules for assigning numbers should be standardized and applied uniformly. This must not change over time or objects.

• When a researcher is interested in measuring the attitudes, feelings, or opinions of respondents he/she should be clear about the following: 

a) What is to be measured? 

• b) Who is to be measured? 
• c) The choices available in data collection techniques

• The level of measurement refers to the relationship among the values that are assigned to the attributes, feelings, or opinions of a variable. Typically, there are four levels of measurement scales or methods of assigning numbers: 
• (a) Nominal scale, 
• (b) Ordinal scale,
• (c) Interval scale, and 
• (d) Ratio scale

• (a) Nominal scale, 

Originating from the Latin word nomin, meaning name, it assigns classification or labels or names to observations so that they can be categorized. 

• It is the simplest type of measurement that identifies types rather than the amount of something. Labels can be symbols, words, or even numbers to classify observations.
• The nominal scale is often referred to as a categorical scale. 
• The assigned numbers have no arithmetic properties and act only as labels. 
• The only statistical operation that can be performed on nominal scales is a frequency count. We cannot determine an average except mode.

For example, jersey numbers in basketball are measures at the nominal level, as numbers do not necessarily have any significance. Other examples are zodiac signs, gender, ethnicity, political affiliation. 

• (b) Ordinal scale
• Also known as the rank order scale, it ranks the observations on a given quality and categorizes them. Originating from the Latin word ordin, meaning order, it allows observations to be ranked but the distance between these ranks is not equal.

• In this scale, the items are classified according to whether they have more or less of a characteristic.
• The main characteristic of the ordinal scale is that the categories have a logical or ordered relationship. 
• This type of scale permits the measurement of degrees of difference, (i.e. ‘more’ or ‘less’) but not the specific amount of differences (i.e. how much ‘more’ or ‘less’). 
• This scale is very common in marketing, satisfaction, and attitudinal research. 
• Using ordinal scale data, we can perform statistical analysis like Median and Mode, but not the Mean. 
• For example, a fast food home delivery shop may wish to ask its customers: How would you rate the service of our staff? (1) Excellent • (2) Very Good • (3) Good • (4) Poor • (5) Worst •

For example, grocery stores generally rank their hot sauce as, “mild”, “medium”, and “spicy”. We know which one is the hottest and which one is less hot, but we don’t know whether the increase in hotness from “mild” to “medium” is the same as it is from “medium” to “spicy.”

(c) Interval scale

It inherits all the characteristics of the ordinal scale and has a meaningful distance between adjacent scores. Originating from the Latin words inter meaning between and vallum meaning ramparts, it provides a meaningful interval between the scores.

• Interval Scale is a scale in which the numbers are used to rank attributes such that numerically equal distances on the scale represent equal distances in the characteristic being measured. 
• An interval scale contains all the information of an ordinal scale, but it also one allows to compare the difference/distance between attributes.
• However, in an interval scale, the zero point is arbitrary and is not true zero.

For example, if we can measure temperature as 0c on the thermometer, it doesnot means there is no temperature at all, but all of these lack a true zero.

• (d) Ratio scale

It inherits all the characteristics of an interval scale in addition to having a true zero. Originating from the Latin word ratio meaning calculations, it is the highest level of scales of measurement where the researchers can perform mathematical and statistical operations.

• This has the properties of an interval scale together with a fixed (absolute) zero point. The absolute zero point allows us to construct a meaningful ratio. 
• Ratio scales permit the researcher to compare both differences in scores and the relative magnitude of scores.
• Examples of ratio scales are the number of children, weight, height, response time, income, etc.
• Many social science and educational variables cannot be measured using this scale. It is impossible to have zero self-esteem, intelligence, compassion, spelling ability, etc.

S.No.	Scale	Basic Characteristics	Can categorize data?	Can order/rank data?	Can add or Subtract data?	True or Meaningful Zero?	Permissive Statistics
							Descriptive Statistics	Inferential Statistics
1.	Nominal	Numbers Identify and Classify Objects	Yes	No	No	No	Percentage, Frequency, Mode	Chi-square, Binomial Test
2.	Ordinal	Numbers indicate the relative positions of the object but not the magnitude difference between them	Yes	Yes	No	No	Percentile, Median	Rank Order Correlation,
3.	Interval	Indicates the Difference between them	Yes	Yes	Yes	No	Range, Mean, Standard Deviation	Product Moment Correlation, T-test, ANOVA
4.	Ratio	It has the properties of an interval scale together with a fixed (absolute) zero-point.	Yes	Yes	Yes	Yes	Geometric Mean, Harmonic Mean	Coefficient of Variation

Source: What are the scales of measurement? - Concepts Hacked

SCALING 

Scaling is the assignment of objects to numbers or semantics according to a rule. In scaling, the objects are text statements, usually statements of attitude, opinion, or feeling. 

The various types of scaling techniques used in research can be classified into two categories: 

(a) Comparative scales, and 

(b) Non-comparative scales

1. Comparative scale: It involves the direct comparison of objects. Comparative scale data must be interpreted in corresponding terms and have either ordinal or rank-order properties.          For example, the researcher can ask the respondents whether they prefer brand A or brand B of a detergent.

• The comparative scales can further be divided into the following four types of scaling techniques: 
• (a) Paired Comparison Scale, 
• (b) Rank Order Scale, 
• (c) Constant Sum Scale, and 
• (d) Q-sort S

(a) Paired Comparison Scale: This is a comparative scaling technique in which a respondent is presented with two objects at a time and asked to select one object (rate between two objects at a time) according to some criterion. The data obtained are ordinal in nature.

(b) Rank Order Scale: This is another type of comparative scaling technique in which respondents are presented with several items simultaneously and asked to rank them in the order of priority. This is an ordinal scale that describes the favored and unfavoured objects but does not reveal the distance between the objects. Like paired comparison, the rank order scale is also comparative in nature. The resultant data in rank order is ordinal data. This method is more realistic in obtaining the responses and it yields better results when direct comparisons are required between the given objects. The major disadvantage of this technique is that only ordinal data can be generated.

•  (c) Constant Sum Scale: In this scale, the respondents are asked to allocate a constant sum of units such as points, rupees, or chips among a set of stimulus objects with respect to some criterion. 
• The advantage of this technique is saving time. 

• 👉However, there are two main disadvantages. 
• The respondents may allocate more or fewer points than those specified. 
• The second problem is rounding off error if too few attributes are used and the use of a large number of attributes may be too taxing on the respondent and cause confusion and fatigue.

(d) Q-Sort Scale: This is a comparative scale that uses a rank order procedure to sort objects based on similarity with respect to some criterion. 

• The important characteristic of this methodology is that it is more important to make comparisons among different responses of a respondent than the responses between different respondents. 
• Therefore, it is a comparative method of scaling rather than an absolute rating scale.
• In this method, the respondent is given statements in a large number for describing the characteristics of a product or a large number of brands of a product.

2. Non-comparative scales

In non-comparative scaling, respondents need only evaluate a single object. Their evaluation is independent of the other object that the researcher is studying. Respondents using a non-comparative scale employ whatever rating standard seems appropriate to them. 

The non-comparative scaling techniques can be further divided into: 

(a) Continuous Rating Scale, and 

(b) Itemised Rating Scale

• (a) Continuous Rating Scale

It is very simple and highly useful. In a continuous rating scale, the respondents rate the objects by placing a mark at the appropriate position on a continuous line that runs from one extreme of the criterion variable to the other. Examples of continuous rating scales are given below:

• Whichever of the above continuous scales is used, the results are normally analyzed as interval-scaled.

b) Itemised Rating Scales 

An itemized rating scale is a scale having numbers or brief descriptions associated with each category. The categories are ordered in terms of scale position and the respondents are required to select one of the limited number of categories that best describes the product, brand, company, or product attribute being rated. 

Itemized rating scales are widely used in marketing research. 

Itemized rating scale further divided into three types  namely 

1. Likert scale

2. Semantic Differential Scale, and

3. Stapel Scale

1. Likert, is extremely popular for measuring attitudes, because, the method is simple to administer. With the Likert scale, the respondents indicate their own attitudes by checking how strongly they agree or disagree with carefully worded statements that range from very positive to very negative towards the attitudinal object. 

• Respondents generally choose from five alternatives (say strongly agree, agree, neither agree nor disagree, disagree, strongly disagree). 
• A Likert scale may include a number of items or statements. 
• The disadvantage of the Likert Scale is that it takes longer time to complete than other itemized rating scales because respondents have to read each statement. 
• Despite the above disadvantages, this scale has several advantages. It is easy to construct, administer, and use.

Semantic Differential Scale: 

This is a seven-point rating scale with endpoints associated with bipolar labels (such as good and bad, complex and simple) that have semantic meaning. 

• It can be used to find whether a respondent has a positive or negative attitude towards an object. 
• It has been widely used in comparing brands, products, and company images.
• It has also been used to develop advertising and promotion strategies and in a new product development study
• In the semantic Differential scale, the phrases used to describe the object form a basis for attitude formation in the form of positive and negative phrases. 
• The negative phrase is sometimes put on the left side of the scale and sometimes on the right side. 
• This is done to prevent a respondent with a positive attitude from simply checking the left side and a respondent with a negative attitude from checking on the right side without reading the description of the words.

 Staple Scale: The Stapel scale was originally developed to measure the direction and intensity of an attitude simultaneously. Modern versions of the Stapel scale place a single adjective as a substitute for the Semantic differential when it is difficult to create pairs of bipolar adjectives. 

• The modified Stapel scale places a single adjective in the center of an even number of numerical values (say, +3, +2, +1, 0, –1, –2, –3). 
• This scale measures how close to or how distant from the adjective a given stimulus is perceived to be.