Chapter Thirteen Measurement Winston Jackson and Norine Verberg Methods: Doing Social Research, 4e.

Chapter ThirteenChapter ThirteenMeasurementMeasurement

Winston Jackson and Norine Verberg

Methods: Doing Social Research, 4eMethods: Doing Social Research, 4e

2 © 2007 Pearson Education Canada

A. Theoretical, Conceptual, and Operational Levels

Measurement is the “process of linking abstract concepts to empirical referents”(Carmines & Zeller)

Hence, one moves from the general (theoretical level) to the specific (empirical level) i.e., For each concept, an indicator is identified e.g., What is the best way to measure, or indicate, a

person’s social prestige? The concepts we measure are called variables See Figure 13.1 (next slide)


Figure 13.1 Levels in Research Design

FPO Figure 13.1 Levels in Research Design from page 350


Figure 13.1

Shows movement from the general to the specific – from the theoretical level to the operational level referred to as operationalization

At the theoretical level, concepts (e.g., socioeconomic status, alienation, job satisfaction, conformity, age, gender, poverty, political efficacy) are conceptualized

At the operational level, the researcher must create measures (or indicators) for the concept Indicators should reflect the variable’s conceptual

definition


Assessing Indicators

We assess the link between the concepts and the indicators by evaluating the validity and reliability of the indicators

1. Validity the extent to which a measure reflects a

concept, reflecting neither more nor less than what is implied by the conceptual definition

2. Reliability the extent to which, on repeated measures,

an indicator yields similar readings


1. Validity (in Quantitative Research)

Illustration: concept - socioeconomic status Conceptual definition: a “hierarchical continuum

of respect and prestige” Operational definition: annual salary Assessment: Low validity (salary might not

capture prestige – widows, ministers, nuns – prestige and respect would be higher than income suggests

Measure should be congruent with conceptual definition


Types of validity

Face validity… on the face of it... Content validity…reflects the dimension(s)

implied by the concept Criterion validity: two types

Concurrent validity…correlation of one measure with another

Predictive validity...predict accurately Construct validity…distinguishes participants

who differ on the construct


Validity in experimental design

Internal validity- the extent to which you can demonstrate that the treatment produces changes in dependent variable

External validity - the extent to which one can extrapolate from study to the general pop’n

In qualitative research… “credibility” is the issue .. Degree to which the description “rings true” to

the subjects of the study, to other readers, or to other researchers


2. Reliability (2. Reliability (in Quantitative Methods)

Reliability refers to the extent to which, on repeated measures, an indicator yields similar readings.

Assessing internal reliability of items used to construct an index (an index combines several items into a single score) Split-half method: randomly split the items in

two, construct index, do results correlate highly?

Internal consistency: statistical procedure done in SPSS (described later in chapter)


B. Measurement ErrorB. Measurement Error

Researchers assume that the object being measured has two or more values (i.e., is not a constant) and that it has a “true value” true value – the underlying exact quantity of a

variable at any given time Researchers also assume that measurement

errors will always occur because instruments are imperfect Measurement error is any deviation from “true

value”


Measurement Error (Cont’d)

Measures are made up of the following components: MEASURE= true value +/- (SE+/-RE)

SE ~ Systematic error is non-random error that systematically over- or under-estimates a value (eg., systematically assigning the lowest value when a respondent does not answer)

RE ~ Random error is random fluctuations around the true value Not a problematic…should average out


1. Tips for Reducing 1. Tips for Reducing Random and Systematic ErrorRandom and Systematic Error1. Take average of several measures

2. Use several different indicators

3. Use random sampling procedures

4. Use sensitive measures

5. Avoid confusion in wording of questions or instructions

6. Error-check data carefully

7. Reduce subject/experimenter expectations


C. Levels of MeasurementC. Levels of Measurement

Introduced in Chapter 8; This chapter stresses the importance of level of measurement for measuring concepts Type of level of measurement influences

which statistical procedures one can use Three levels of measurement

1. Nominal

2. Ordinal

3. Ratio



D. The Effects of Reduced Levels D. The Effects of Reduced Levels of Measurementof Measurement

Best to achieve most precise, and highest, level of measurements possible

When lower levels are used, the results under-estimate the relative importance of a variable The greater the reduction in measurement

precision, the greater the drop in correlations between variable

Precisely measured variables will appear to be more important than poorly measured ones


E. Indexes, Scales, and Special Measurement Procedures Combining several indicators into one score

results in an index or scale While used interchangeably, an index refers

to the combination of two or more indicators; a scale refers to a more complex combination of indicators where the pattern of responses is taken into account

Indexes are routinely constructed to reflect complex variables Socioeconomic status, job satisfaction, group

dynamics, social attitudes toward an issue


1. Item Analysis1. Item Analysis

Items in an index should discriminate well Example of test item development

Test graded, students divided into upper and lower quartile

Examine performance on each question Select those questions that discriminate best


Discrimination of ItemsDiscrimination of Items

FPO Table 13.1 Discrimination Ability of 100 Items: Percentage Correct for Each Item, by Quartile, from page 350


2. Selecting Index Items2. Selecting Index Items

1. Review conceptual definition Does the concept have ranges or dimensions

2. Develop measures for each dimension Developed items for each dimension of the

concept

3. Pre-test index Complete the index yourself, then pre-test it

with target-group members

4. Pilot test index Use SPSS to assess internal consistency


3. The Rationale for Using Several Items in an Index


4. Likert-based Indexes


A. Tips for Constructing Likert-based Index The “and” alert: avoid multiple dimensions Strongly Agree on right hand side 9-points

Response set issue Avoid negatives like “not” simply use negative

wording. Vary strength of wording to produce variation

in response Exercise….items for a euthanasia index


A. Tips for Constructing a Likert-based Index


B. Evaluation of Likert-based Indexes


C. Using the Internal Consistency Approach to Selecting Index Items


5.5. Semantic Differential Procedures

A variety of anchors are used and people place themselves or others on a continuum: shy/outgoing; bookworm/social butterfly

Continued…


5. Box 13.3


6. Magnitude Estimation Procedures

subjects use numbers or line lengths to indicate perceptions. Very good for comparisons: yields ratio level measures. Comparing liking of teachers; seriousness of crimes; liking of one community compared to another one, etc.


Tips for Using Magnitude Estimation Procedures

1. Only use ME when a researcher is present to explain the method to respondents

2. Use ME when comparative judgments sought

3. Use a stimulus category somewhere near the middle of the range you intend to use as a standard (avoid a standard too high or low)

4. After the standard established,

Chapter Thirteen Measurement Winston Jackson and Norine Verberg Methods: Doing Social Research, 4e.

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