8. scaling methods (ch 9)

7/31/2019 8. Scaling Methods (Ch 9)

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Prepared by Mr. C Y Nimkar - Part 8 1

Scaling Methods


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Scaling Methods

Two types of scaling methods Comparative Scales

Compare one object with another

Non-comparative scales Evaluate each object independently


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Comparative Scales


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Comparative Scales

Paired Comparison Full Comparison


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Paired comparison

Respondent is shown a pair of objects He is asked to select one object that he

prefers


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Paired comparison Example 1

Que.: (SHOW CARD A) This card shows pair of brands. Please tellme which brand would you prefer from each pair

Brand 1 Brand 2 Preferred

LG Samsung

LG Akai

LG Sony

Samsung Sony

Samsung Akai

Akai Sony


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LG SAMSUNG AKAI SONY

LG 0

SAMSUNG 0

AKAI 0

SONY 0

TOTAL

Preferred Brand

Preference Matrix


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Paired comparison Example 2

Que.: (SHOW CARD A) This card shows pair of brands.Allocate a total score of 11 to brands shown in each pair

Brand1

Brand2

Score to brand 1 Score to brand 2

LG Samsung

LG Akai

LG Sony

Samsung Sony

Samsung Akai

Akai Sony


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Paired comparison

Small difference in preference is captured

Not suitable if number of pairs is large


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Full Comparison Ranking

Respondents are asked to rank objects


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Que.: (SHOW CARD A) This card shows four brands of TV. Pleaserank them such that the most liked brand to you will get rank 1,the second most liked will get rank 2 and so on.

Attribute Rank

Samsung

Akai

SonyLG

Full Comparison Ranking - Example


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Full Comparison - Constant sum scale

Respondents are asked to allocate points to eachobject out of a constant say 100.


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Constant sum scale - Example

Que.: (SHOW CARD A) This card shows four brands of TV. Pleaseallocate a total of 100 points to them according your liking.More the points, more liked the brand to you.

Attribute Points

Samsung

Akai

Sony

LG

TOTAL 100


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Comparative Scales

Used to obtain preferences of respondents Ranking method gives data in ordinal scale:

Gives order of preference

Constant Sum method gives data in interval scale: Additionally gives intensity of preference


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Non comparative Scales


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Itemised rating scale Example 1

Respondent is asked to select one category

Que.: (SHOW CARD A) This card shows a scale. Please indicate your likingabout Sony TV by using the scale

Extremely Quite Slightly Neutral Slightly Quite Extremely

disliked liked


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(SHOW CARD A) This card shows 5 statements.Which statement would describe your decisionto buy this product?

1. I would definitely buy it2. I would probably buy it3. I may or may not buy it4. I would probably not buy it5. I would definitely not buy it



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Airline food service is _____ to me.

Extremely important

Very importantSomewhat important

Not so important

Not very important

Not at all important



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Korean Airs food service is:

Excellent

Very goodGood

Fair

Poor

Very poor



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Itemised rating scale

5 points 7 points

Definitely Definitely

Probably Mostly

Might or might not ProbablyProbably not Might or might not

Definitely not Probably not

Mostly not

Definitely not


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2. Graphic itemised rating scale

Respondents are shown pictures

Used for children/illiterates.


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Attitude Measurement Scales


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Attitudes are constructs. For e.g.: Attitude towards shopping in Big Bazaar

Measurement of attitudes requires:

Finding dimensions of attitude(operationalisation)

Selecting scale to measure dimensions

For e.g.

Attitudes


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We need a scale to obtain data on

dimensions Then, attitude will be an index calculated

by using data on dimensions

Scales used to obtain data on dimensionsare called Attitude Measurement Scales


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Attitude Measurement Scales

Single item Multiple items


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Single-item format


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Single-item format

Respondent is asked to give his rating on overallattitude

Que.: (SHOW CARD A) Using the scale shown in this card,

how would you rate your opinion towards shopping in BigBazaar?

Extremely Quite Slightly Neither Slightly Quite ExtremelyUnfavourable Favourable


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Multiple-items format


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Multiple-items format

This format collects data on each dimension of attitude

Index is computed to represent respondentsattitude.


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1. Likert scale

Generate as many statements as possible aboutattitude towards research object by: Asking few respondents to write as many statements as

possible

Writing statements ourselves by referring to focus groupdiscussion


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For e.g., statements for attitude towardsshopping in Big Bazaar:

Shopping in Big Bazaar saves time Big Bazar stores fresh stock

Service at cash counter in Big Bazaar is good

Big Bazaar never stores duplicate products.


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Ask few respondents to tell us to what extentthey agree to each statement by using following

scale:- Strongly agree

Agree

Neutral (Neither agree nor disagree)

Disagree

Strongly disagree


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Convert responses into numbers where favourableopinion will be given higher score. For e.g.:

Statements StronglyAgreeAgree Neutral Disagree Strongly

Disagree

Shopping in Big Bazaar saves

time5 4 3 2 1

OR

StatementsStronglyAgree

Agree Neutral Disagree StronglyDisagree

Shopping in Big Bazaar savestime

2 1 0 -1 -2


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Final statements are selected by: Item Discrimination method

Factor analysis method


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Add score of each statement to get Total scoresof each respondent

Calculate 25 th and 75 th percentiles of Total scores

Statistics

Total_score

250

142.5000192.5000

ValidMissingN

2575

Percentiles

RespNo. Total_score

2 90

12 95

11 105

13 105

25 125

24 135

4 150

8 150

19 160

23 160

9 165 15 165

17 170

5 175

7 175

16 180

22 180

20 185

10 190

21 195

18 200

6 205

1 210

3 210

14 240

In this example 50 statements were generatedand shown to 25 respondents

Total scores of each respondent arranged inascending order are shown in the table

25 th and 75 th percentiles are as below:


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Respondents with total score < P 25 haveoverall unfavorable attitude. We will callthis as GROUP A

Respondents with total score > P 75 haveoverall favorable attitude. We will callthis as GROUP B

RespNo. Total_score

2 90

12 95

11 105

13 105

25 125

24 135

4 150

8 150

19 160

23 160

9 165 15 165

17 170

5 175

7 175

16 180

22 180

20 185

10 190

21 195

18 200

6 205

1 210

3 210

14 240

A

B

Statistics

Total_score25

0142.5000192.5000

Valid

Missing

N

2575

Percentiles


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Prepare following table:

StatementNo Average rating by Difference

Group A Group B (B) - (A)

1 2.05 4.75 2.70

2 2.55 2.60 0.05

3 1.25 4.25 3.00

4 1.35 3.10 1.75 5 2.05 2.07 0.02

Larger the positive difference(B) (A), better the statement is

This difference is called ItemDiscrimination Index of the

statement Use Independent two samples ttest/ Mann Whitney U test tocheck whether the difference

(B) (A) is large Select those statements for those

this difference is large


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2. Semantic differential scale

Opposite adjectives (poles) are shown to the respondents on

each dimension of attitude with seven options in between.Que.: We would like to know what you think about Big Bazaar. Please check the

category that represents your opinion:

Modern ___ : ___ : ___ : ___ : ___ : ___ : ___ Old fashionedUnfriendly staff ___ : ___ : ___ : ___ : ___ : ___ : ___ Friendly staff Expensive ___ : ___ : ___ : ___ : ___ : ___ : ___ EconomicalQuick service ___ : ___ : ___ : ___ : ___ : ___ : ___ Delay in serviceGood ambience ___ : ___ : ___ : ___ : ___ : ___ : ___ Poor ambience

Inconvenient ___ : ___ : ___ : ___ : ___ : ___ : ___ Convenientstore hours store hours


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2. Semantic differential scale

Poles should be randomly distributed to left-hand andright-hand anchored positions.

Scoring is from 1 to 7 or from -3 to +3.

3 S l l


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3. Stapel scale Only one pole of a component of attitude is shown. For

example, Expensive store.

Scale has 10 response categories with no neutral orindifference category. 5 categories have + sign and 5 have negative sign. For e.g.:

Big Bazaar Store is:

+ 5+ 4+ 3+ 2+ 1

Expensive store

- 1- 2- 3- 4- 5


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Reliability of measures


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Reliability means consistency It is measured by:

Test-retest method

Internal consistency method Inter-item method Split-half method

T t R t t M th d


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Test-Retest Method

Same question is asked second time to same

respondents Correlation between scores obtained at two

different times expresses reliability

For e.g., following question was asked two timeswith a gap of one week to same respondents

Que: (SHOW CARD A) This card shows features that onewould like to have in cooking oil. Please rank them as peryour preference. The most preferred feature to you willget rank 1, the second- most will get rank 2 and so on.


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Features RankFat content

Purity

Taste

Flavour

Stickiness

CARD A


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Rank to Fat Content

Reliability coefficient of ranking scalefor measuring preference to FatContent is 0.667 (Spearmans rho)

Calculate reliability coefficients forother features

Overall reliability is the average of coefficients

RespNo.

1stTime

2ndTime

1 2 2 2 3 2

3 3 3

4 2 1

5 1 1

6 2 2

7 4 3

8 3 3

9 2 2

10 1 1

11 2 2

12 2 2

13 2 1

14 1 2

15 2 1

16 2 2

17 1 2

18 3 3

19 2 2

20 3 2

Correlations

1.000 .667**. .001

20 20

.667** 1.000

.001 .20 20

Correlation CoefficientSig. (2-tailed)N

Correlation CoefficientSig. (2-tailed)N

1st Time

2nd Time

Spearman's rho1s t Time 2n d Time

Correlation is s ignificant a t the 0.01 level (2-tailed).**.


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l C i h d S li h lf


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Used for psychometric tests or skill measurement tests

Questions (items) are divided into two groups: Odd even items First half and second half Randomly

Total scores are computed for both groups Correlation between two groups is the reliability

coefficient For e.g. in a numerical ability test:

There are 50 multiple choice items

Items are divided by odd even method Test is administered to 20 respondents

Total scores are as follows:

Internal Consistency Method Split-half


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Correlations

1 .710**.000

20 20.710** 1.000

20 20

Pearson CorrelationSig. ( 2-tailed)NPearson CorrelationSig. ( 2-tailed)N

Even items

Odd items

Even items Odd items

Correlation is significant at the 0.01 level (2-tailed).**.

RespNo.

Total scoreon

Even items

Total scoreon

Odd items

1 20 18

2 15 18

3 20 22

4 22 20

5 22 18

6 16 17

7 18 15

8 18 20

9 16 20

10 20 22

11 21 18

12 17 19

13 25 24

14 22 20

15 19 18

16 18 16

17 14 15

18 15 18

19 12 10

20 22 20

Reliability of the scale is 0.710(Pearsons correlation)


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Validity of measures


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Validity is the appropriateness of dimensions to describe a construct likeattitude

Validity answers question: Are we

measuring what we think we aremeasuring?


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Three types of validity: Content Validity

Criterion-related validity (Predictive Validity) Construct Validity


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It is the representativeness or samplingadequacy of the construct

Each dimension must be relevant to theconstruct

It is decided by the judgment

Content Validity

Subject knowledge(Construct)

Question inquestion paper

Content Validity


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It is related to predicting an outcome It answers the question: How far the

measure predicts well?

For e.g.: Candidate selection tests predicts his suitability

Aptitude test predicts his future achievement

Que: Will you buy this product? predictsbuying behaviour when product is launched

Criterion-related Validity (Predictive Validity)

C V lidi


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It answers the question: What is it that thescale is measuring?

For e.g.: Is the test measuring logical ability or

reasoning ability?

Construct Validity

8. scaling methods (ch 9)

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