BRM Unit 4
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Transcript of BRM Unit 4
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MEASUREMENT OFVARIABLES: OPERATIONAL
DEFINITION AND SCALES
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THE RESEARCH DESIGNDETAILS OF STUDY MEASURMENT
Purpose of thestudy
ExplorationDescriptionHypothesis testing
Types ofInvestigation
Establishing:-Casual relationships-Correlations-Group differences,
Extent of researcherInterference
Minimum: Studying eventsas they normally occurModerate: Minimumamount of interferenceMaximum: High degreeof control and artificialsettings
Study setting
Contrived
Noncontrived
Measurementand measures
Operationaldefinition
items (measure)ScalingCategorizingCoding
Unit of analysis(Population to bestudied)
IndividualsDyadsGroupsOrganizationsMachinesetc.
Sampling design
Probability/nonprobability
SampleSize (n)
Time horizon
One-Shot(cross-sectional)
Multishot(longitudinal)
Data-Collectionmethod
ObservationInterview
Questionnaire
Physicalmeasurement
Unobtrusive
1. Feel fordata
2. Goodnessof data
3. Hypothesestesting
PRO
BLE
MST
ATEM
ENT
DATAANALYSIS
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OPERATIONAL DEFINITION
Reduction of abstract concepts to render themmeasurable in tangible way is called operationalizing theconcepts. It is done by looking at the behavioraldimensions, facts, or properties denoted by the concept.
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EXAMPLE OF DIMENTIONS AND ELEMENTS The concept of thirst is abstract: we cannot see thirst. However, we would
expect a thirsty person to drink plenty of fluid. If several people say they
are thirsty, then we may determine the thirst level of each of these
individuals by the measure of the quantity of fluid that they drink to
quench their thirst. We will thus be able to measure their level of thirst,
even though the concept of thirst itself is abstract and nebulous (unclear).
In the above example the thirst is the concept, the drinking of plenty offluid is the dimension, and the measuring of the quantity of fluid that
they drink to quench their thirst is the element.
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The nature of measurement
Measurement occurs when an established index verifies the height, weight,or other feature of a physical object.
To measure is to discover the extent, dimension, quantity, or capacity ofsomething, especially by comparison with a standard.
Measurement in research consists of assigning numbers to empirical events,objects or properties, or activities in compliance with a set of rules.
This definition implies that measurement is a three-part process
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The nature of measurement
Select observable empirical events. Developing a set of mapping rules Applying the mapping rule(s) to each observation of that event.
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Gender Attendees Styling Characteristics Attendees
Gender
AssignM if maleF if female
(M, F)
A B C D E Desirability of auto styling
Assign5 if very desirable4 if desirable3 if neither2 if undesirable1 if very undesirable
(1 through 5)
A B C D E
M F1 2 3 54
Sampleelements
EmpiricalObservations
Mapping Rules
Symbol
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Methods of scale
A scale is a tool or mechanism by which individuals are distinguished asto how they differ from one another on the variable of interest to ourstudy.
There are four basic methods of scales: nominal, ordinal, interval, andratio. The degree of sophistication to which the scales are fine-tunedincreases progressively as we move from nominal to the ratio scale.
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Nominal Scale
The lowest measurement level you can use, from a statistical point of view,is a nominal scale, as the name implies, is simple some placing of data intocategories, without any order or structure.
Example of a nominal scale SEX 1. Male 2. Female Area 2. Rural 2. Urban
Numbers assigned to represent the categories cannot meaningfully beadded, subtracted, or divided.
A mean or a median cannot be calculated for nominal data. A mode and a chi-square statistical test can be used.
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Ordinal Scale Ordinal scale include the characteristics of the nominal scale plus an
indication of order. Ordinal data require conformity to a logical postulate,which states: If a is greater than b and b is greater than c, then a is greaterthan c.
The use of an ordinal scale implies a statement of greater than or lesser than(an equality statement is also acceptable) without stating how much greateror less. Example of a ordinal scale: Brand Preference for purchasing a Television
Onida : Samsung : LG : Sony : Sharpe :
Median and mode, rank order correlation statistical test can be used
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INTERVAL SCALE An interval scale measure the distance between any two points on the
scale. This help us to compute the means and the standard deviations of the
responses on the variables.
In other words, the interval scale not only groups, it also measures themagnitude of the differences in the preferences among the individuals.
It is more powerful scale than the nominal and ordinal scale, and has forits measure of central tendency the arithmetic mean. Its measure of
dispersion are the range, the standard deviation, and the variance.
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EXAMPLE OF INTERVAL SCALE
Indicate the extent to which you agree with the following statements asthey related to your job, by circling the appropriate number against each,using the scale given below.
StronglyDisagree
1
Disagree
2
Neither AgreeNor Disagree
3
Agree
4
StronglyAgree
5The following opportunities offered by the job are very important to me:
a. Interacting with others. 1 2 3 4 5b. Using a number of different skills. 1 2 3 4 5
c. Completing a task from beginning to end. 1 2 3 4 5d. Serving others. 1 2 3 4 5
e. Working independently. 1 2 3 4 5
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RATIO SCALE The ratio scale overcomes the disadvantage of the arbitrary origin point of the
interval scale, in that it has an absolute zero point, which is a meaningful
measurement point. Thus the ratio scale not only measures the magnitude of the
differences between points on the scale but also tapes the propositions in the
differences. It is most powerful of the four scales because it has a unique zero
origin (not an arbitrary origin) and subsumes all the properties of the other three
scales.
The measurement of central tendency of the ratio scale could be either thearithmetic or the geometric mean and the measure of dispersion could be either
the standard deviation, or variance, or the coefficient of variation.
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EXAMPLE OF RATIO SCALE1. How many other organization did you work for before joining this system? ____2. Indicate the number of children you have in each of the following categories:
____below three years of age
____between three to six years
____over six years but under twelve years
____twelve years and over.
3. How many retail outlets do you operate? ____.
The responses to the questions could range from 0 to any reasonable figure.
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SCALE
Assigning numbers or symbols to elicit the attitudinal responses of subjectstoward object, event, or persons is called scale.
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TYPES OF SCALES
There are two main categories of attitudinal scales.
1.Rating scale: Rating scales have several response categories and are used toelicit responses or behavioral concept with regard to the object, events,
or person studied.
2.Ranking scale: Ranking scales make comparison between or amongobjects, events, or persons and elicit the preferred choices and ranking
among them.
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Rating Scale
Simple Attitude Scale Likert Scale Semantic Differential Scales Numerical/Multiple Rating List Scale STAPEL Scales Constant-Sum Scales Graphic Rating Scales
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Simple Attitude Scale
The simple category scale (also called a dichotomous scales) offers twomutually exclusive response choice.
This response strategy is particularly useful for demographic questions orwhere a dichotomous response is adequate.
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Examples of Simple Attitude Scale Do you plan to purchase a laptop in the next 3 Months
Yes No
What newspaper do you read most often for financial newsThe Economic times the financial express business standard Others
Check any of the sources you consulted when designing your new homeOnline Magazines Designer Architect others
The internet is superior to traditional libraries for comprehensive searchesStrongly Agree Agree Neutral Disagree Strongly Disagree
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Likert Scale
The Likert scale, developed by Rensis Liker (pronounced Lick-ert), is themost frequently used variation of the summated scale. Summated rating
Scale consist of statements that express either a favourable or an
unfavourable attitude towards the object of interest.
Typically, each scale item will have 5 categories, with scale values rangingfrom -2 to 2 with 0 as neutral response.
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Examples of Likert Scale
Strongly Agree Agree Neutral DisagreeStronglyDisagree
Quality of theFood
2 1 0 -1 -2
Cleanness ofthe Hostel
2 1 0 -1 -2
Amenitiesprovided by the
management5 4 3 2 1
Training timeintervals
1 2 3 4 5
Satisfactionwith thepresent
Appraisalsystem
5 4 3 2 1
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Semantic Differential Scales
This type of scale makes extensive use of words rather than numbers.Respondents describe their feelings about the products or brands on scales
with semantic labels. When bipolar adjective are used at the end points of
the scales, these are termed Semantic Differential Scales.
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Examples of Semantic Differential Scales
Extremely Quite Slightly Neither Slightly Quite Extremely
Good Bad
Important unimportant
High Low
Strong Week
Active Passive
Semantic Scales
Semantic DifferentialScales
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Numerical/Multiple Rating List Scale
The Numerical/Multiple Rating List Scale is commonly used variation of thelinear, numeric scale but there is an important distinction. With the linear,
numeric scale the respondents has to pick a number from the scale and then
write the number beside the item.
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Examples of Numerical/Multiple Rating ListScale
Extremelysafe
ExtremelyUnsafe
SavingsAccount
1 2 3 4 5 6 7
Loansaving
account1 2 3 4 5 6 7
Certificateof deposit
1 2 3 4 5 6 7
Corporatecommon
stocks1 2 3 4 5 6 7
Preciousmetals
1 2 3 4 5 6 7
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STAPAL (BASIC) SCALE
This scale simultaneously measure both the direction and intensity of theattitude toward the item under study. The characteristic of interest to the
study is placed at the center and a numerical scale ranging, say from +3 to -3
or +5 to -5, on either side of the item. This gives the idea of how closer or
distant the individual response to the stimulus. Since this does not an
absolute zero point, this is an interval scale.
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Example of STAPAL (BASIC) SCALE
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FIXED OR CONSTANT SUM SCALE
The respondents are here asked to distribute a given number of pointsacross various items. This is an ordinal scale
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Example of Fixed or Constant Sum Scale
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GRAPHIC RATING SCALE
A graphical scale representation helps the respondents to indicate on thisscale their answers to a particular question by placing a mark at the
appropriate point in the line. This is an ordinal scale. The faces scale, which
shows faces ranging from smiling to sad is also a graphic scale, used to
obtain responses regarding peoples feelings.
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EXAMPLE GRAPHIC RATING SCALE
On a scale of 1 to 10 how would you rate your supervisor?
1 5 10
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Ranking Scale
In ranking scales, the participants directly compares two or more objectsand makes choices among the.
Ranking scales used in organization1. PAIRED COMPARISON.2. FORCED CHOICE.3. COMPARATIVE SCALE.
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PAIRED COMPARISON
It is used when, among a small number of objects, respondents are asked tochoose between two objects at a time.
As the number of objects to be compared increases, so does the number ofpaired comparisons. The paired choices for n objects will be n (n-1) / 2.
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Examples of Paired Comparison
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FORCED CHOICE
It enables respondents to rank objects relative to one another, among thealternatives provided. This is easier for the respondents, practically if the
number of choices to be ranked is limited in number.
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Example of Forced Ranking Scale
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COMPARATIVE SCALE
It provides a benchmark or a point of reference to assess attitudes towardthe current object, event, or situation under study.
EXAMPLE OF COMPARATIVE SCALE
In a volatile (evaporation) financial environment, compared to stocks,how wise or useful is it to invest in Treasury bonds? Circle theappropriate response.More Useful About the
SameLess Useful
1 2 3 4 5
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GOODNESS OF DATA It is important to make sure that the instrument that we develop to measure
a particular concept is indeed accurately measuring the variable, and that in
fact, we are actually measuring the concept perceptual and attitudinal
measure. This ensures that in operationally defining perceptual and
attitudinal variables, we have not overlooked some important
dimensions and elements or included some irrelevant ones.
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Item analysis
Item analysis is carried out to see if the items in the instrument belong thereor not. Each item is examined for its ability to discriminate between thosesubjects whose total scores are high, and those with low scores.
Thereafter, test for the reliability of the instrument are carried out and thevalidity of the measure is established.
Reliability is a test of how consistently a measuring instrument measureswhatever concept it is measuring.
Validity is a test of how well an instrument that is developed measures theparticular concept it is intended to measure. In other words, validity isconcerned with whether we measure the right concept, and reliability withstability and consistency of measurement.
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TESTING GOODNESS OF MEASURES
Goodnessof data
Reliability(accuracy
InMeasure-
ment)
Validity(we are
MeasuringThe right
Thing)
Stability
Consistency
Test-retest reliability
Interitem consistency reliability
Parallel-form reliability
Split-half reliability
Logical validity(content)
Criterion-relatedvalidity
Congruent validity(construct)
Face validity ConvergentPredictive Concurrent Discriminant
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Types of validity tests
1. Content validity.2. Criterion-related validity.3. Construct validity
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CONTENT VALIDITY It ensures that the measure includes an adequate and representative set
of items that tap the concept. The more the scale items represent thedomain (circle of affection) or universe of the concept being measured, thegreater the content validity.
Face validity considered by some as a basic and a very minimum index of contentvalidity. Face validity indicates that the items that are intended to measure a concept,so on the face of it look like they measure the concept.
the simplest and least scientific definition of validity it is demonstrated when a measure superficially appears to measure what it claims
to measure
Based on subjective judgment and difficult to quantify e.g. intelligence and reasoning questions on the IQ test Problem - participants can use the face validity to change their answers
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CRITERION-RELATED VALIDITY
It is established when the measure differentiates individuals on a criterion itis expected to predict. This can be done by establishing concurrent ( withconsensus) validity or predictive validity
CONCURRENT VALIDITY: It is established when the scale discriminates individualswho are known to the different; that is they should score differently on the instrument
e.g. new IQ test correlates with an older IQ test PREDICTIVE VALIDITY: It indicates the ability of the measuring instrument to
differentiate among individuals with reference to a future criterion.
e.g. high scores on need for achievement test predict competitive behavior in children(ring toss game)
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CONSTRUCT VALIDITY
It testified to how well the results obtained from the use of the measure fitthe theories around which the test is designed. This is assessed throughconvergent and discriminant validity.
CONVERGENT VALIDITY: It is established when the scores obtained with twodifferent instrument measuring the same concept are highly correlated
e.g. an experimenter observing aggressive behavior in children correlated withteachers ratings of their behavior
DISCRIMINANT VALIDITY: It is established when, based on the theory, two variablesare predicted to be correlated, and the scores obtained by measuring them are indeedempirically found to be so.
e.g. aggressive behavior and general activity level in children
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Convergent validity, divergent validity and constructvalidity
By demonstrating strong convergent validity for two different constructs and then showingdivergent validity between the two constructs, you obtain strong construct validity of the twoconstructs
Aggressivebehavior
Teachers ratings Experimentersobservation
Active behavior
Teachers ratings Experimentersobservation
High convergentvalidity
Related scoresHigh Divergent Vali
dityUnrelated
scores
High convergentvalidity
Related scores
High Divergent Vali
dityUnrelated
scores
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TYPES OF VALIDITYValidity Description Method
Content Validity Does the measure adequately measure the concept?JudgmentalPanel evaluation with content validity ratio
Face Validity Do experts validate that the instrument measureswhat its name suggests it measures?
Criterion-related Validity Does the measure differentiate in a manner thathelps to predict a criterion variable. Correlation
Concurrent Validity Does the measure differentiate in a manner thathelps to predict a criterion variable currently? Correlation
Predictive Validity Does the measure differentiate individuals in asmanner as to help predict a future criterion? Correlation
Construct Validity Does the instrument tap the concept as theorized?JudgmentalCorrelation of proposed test with established oneConvergent discriminant techniquesFactor analysisMultitrait multimethods analysis
Convergent Validity Do two instruments measuring the concept correlatehighly?
Discriminant ValidityDoes the measure have a low correlation with avariable that is supposed to be unrelated to thisvariable?
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RELIBILITY
The reliability of a measure indicate the extent to which it is without bias(error free) and hence ensures consistent measurement across time and
across the various items in the instrument. In other words, the reliability of a
measures is an indication of the stability and consistency with which the
instrument measures the concept and helps to assess the goodness of a
measure.
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TEST-RETEST RELIABILITY The reliability coefficient obtained with a repetition of the same measure
on a second occasion is called test-retest reliability. That is, when a
questionnaire containing some items that are supposed to measure a
concept is administered to a set of respondents now, and again to the same
respondents, say several weeks to 6 months later, the correlation between
the scores obtained at the two different times from one and the same set of
respondents is called the test-retest reliability.
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PARALLEL-FORM RELIABILITY
When responses on two comparable sets of measure tapping the sameconstruct are highly correlated, we have parallel-form reliability. Both
forms have similar items and the same response format, the only
changes being the wordings and the order or sequence of the questions.
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INTERNAL CONSISTENCY OF MEASUREThe internal consistency of measures is indicative of the homogeneity of the
items in the measure that tap the construct. In other words, the items
should hang together as a set and be capable of independently
measuring the same concept so that the respondents attach the same
overall meaning to each of the items.
Consistency can be examined through :
1.Inter-item Consistency Reliability.2.Split- Half Reliability.
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INTER-ITEM CONSISTENCY RELIABILITY
This is a test of the consistency of respondents answer to all the items in ameasure. To the degree that items are independent measures of the same
concept, they will be correlated with one another.
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SPLIT-HALF RELIABILITY
Split-half reliability reflects the correlations between two halves of aninstrument. The estimates would vary depending on how the items in the
measure are split into two halves.
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