---
url: "https://questionstar.com/principles-of-survey-research/chapter-2/"
title: "Chapter 2: Survey: Measurement and Scaling"
type: "lehrbuch-chapter"
chapter: 2
chapterTitle: "Survey: Measurement and Scaling"
---

# Chapter 2: Survey: Measurement and Scaling

*61 slides (18–78) · Principles of Survey Research.*

## Slides

- [Slide 18: Survey: Measurement and Scaling](slide-018.html.md) — 2.1 Introduction · 2.2 Comparative Scales · 2.3 Non-Comparative Scales · 2.4 Latent Constructs · 2.5 Reliability and Validity
- [Slide 19: Survey: Measurement and Scaling](slide-019.html.md) — 2.1 Introduction · 2.2 Comparative Scales · 2.3 Non-Comparative Scales · 2.4 Latent Constructs · 2.5 Reliability and Validity
- [Slide 20: Measurement](slide-020.html.md) — Measurement — assigning numbers or other symbols to characteristics of objects according to a specific, predefined rule.
- [Slide 21: Scaling](slide-021.html.md) — Scaling — involves a continuum on which the measured objects are placed.
- [Slide 22: Primary Scales of Measurement](slide-022.html.md) — Measurement and Scaling
- [Slide 23: Some Commonly Used Scales in Marketing](slide-023.html.md) — Levels of Measurement
- [Slide 24: Classification of Scaling Techniques](slide-024.html.md) — Overview
- [Slide 25: Comparison of Scaling Techniques](slide-025.html.md) — The measured value of an object results from the direct comparison with another object.
- [Slide 26: Survey: Measurement and Scaling](slide-026.html.md) — 2.1 Introduction · 2.2 Comparative Scales · 2.3 Non-Comparative Scales · 2.4 Latent Constructs · 2.5 Reliability and Validity
- [Slide 27: Classification of Scaling Techniques](slide-027.html.md) — Focus
- [Slide 28: Pros-and-Cons of Comparative Scales](slide-028.html.md) — Assessment
- [Slide 29: Comparative Scales: Paired Comparison](slide-029.html.md) — For each pair of two objects, respondents select the one that in their opinion best fulfills a given criterion.
- [Slide 30: Comparative Scales: Paired Comparison](slide-030.html.md) — Practical Example
- [Slide 31: Paired Comparison: Pros-and-Cons](slide-031.html.md) — Evaluation
- [Slide 32: Violations of transitivity in paired comparison](slide-032.html.md) — Same respondent, same pairing — and yet contradictory answers:
- [Slide 33: Violations of transitivity when aggregating preferences](slide-033.html.md) — Apple ≻ Tomato ≻ Orange ≻ Apple. Apple is simultaneously the most and the least preferred — the group preferences are inconsistent!
- [Slide 34: Comparative Scales: Rank Order Scaling](slide-034.html.md) — Respondents put several objects into an order — based on a particular criterion.
- [Slide 35: Rank Order Scales: Example](slide-035.html.md) — Practical Example
- [Slide 36: Rank Order Scales: Examples](slide-036.html.md) — Practical Example
- [Slide 37: Rank Order Scales: Example](slide-037.html.md) — Practical Example
- [Slide 38: Rank Order Scales: Pros-and-Cons](slide-038.html.md) — Evaluation
- [Slide 39: Comparative Scales: Constant Sum Scaling](slide-039.html.md) — Respondents distribute a fixed amount (e.g. points, euros, chips, %) entirely across a set of objects — according to a particular criterion.
- [Slide 40: Constant Sum Scaling: Example of Analysis](slide-040.html.md) — Average rating across three segments
- [Slide 41: Constant Sum Scaling: Example](slide-041.html.md) — Practical Application
- [Slide 42: Constant Sum Scaling: Examples](slide-042.html.md) — Practical Application
- [Slide 43: Constant Sum Scaling: Pros-and-Cons](slide-043.html.md) — Assessment
- [Slide 44: Comparative Scales: Q-Sort Scaling](slide-044.html.md) — A rank-order procedure in which objects are sorted into piles (with respect to a specific attribute). Used to quickly compare a large number of objects…
- [Slide 45: Survey: Measurement and Scaling](slide-045.html.md) — 2.1 Introduction · 2.2 Comparative Scales · 2.3 Non-Comparative Scales · 2.4 Latent Constructs · 2.5 Reliability and Validity
- [Slide 46: Classification of Scaling Techniques](slide-046.html.md) — Focus
- [Slide 47: Continuous Rating Scale](slide-047.html.md) — Respondents rate objects by marking a corresponding position on a line that runs from one extreme to the other of a given criterion.
- [Slide 48: Perception Analyzer](slide-048.html.md) — During the presentation of a stimulus — e.g. a TV commercial — each participant turns a dial. This creates a continuous rating in real time, second by…
- [Slide 49: Likert Scale](slide-049.html.md) — Respondents indicate the extent to which they agree with the listed statements — using a 5- or 7-point scale that ranges from one extreme to the other.
- [Slide 50: Likert Scale: Examples](slide-050.html.md) — Likert Scale · in online surveys
- [Slide 51: Some Commonly Used Scales in Marketing](slide-051.html.md) — Scale points from 1 (lowest level) to 5 (highest level).
- [Slide 52: Semantic Differential](slide-052.html.md) — A bipolar rating scale whose extremes are described by opposing adjectives. It allows the measurement of multidimensional attitudes and their profile…
- [Slide 53: Semantic Differential: Profile](slide-053.html.md) — Measures self-assessment as well as attitudes toward people or products. Each point corresponds to the mean or median of the respective scale…
- [Slide 54: Semantic Differential Scale: Example](slide-054.html.md) — Semantic profiles of the shampoo brands “Herbal Magic” and “Elseve” compared to the ideal shampoo from the consumers' point of view.
- [Slide 55: Stapel Scale](slide-055.html.md) — A unipolar rating scale with 10 categories from −5 to +5, without a neutral point (0).
- [Slide 56: Basic Non-Comparative Scales](slide-056.html.md) — Overview
- [Slide 57: Constructing Itemized Rating Scales](slide-057.html.md) — Five Design Questions
- [Slide 58: Number of Scale Categories](slide-058.html.md) — More categories capture finer differences — but most respondents can only handle a few categories.
- [Slide 59: Balanced or Unbalanced Scales](slide-059.html.md) — Design Question 2
- [Slide 60: Even or Odd Number of Scale Categories](slide-060.html.md) — The middle option attracts many undecided respondents — and those who are reluctant to reveal their opinion.
- [Slide 61: Forced or Non-Forced Response?](slide-061.html.md) — Do respondents not want to answer — or do they simply have no opinion?
- [Slide 62: Labeling the Scale Points](slide-062.html.md) — Should every scale point be labeled — or are a few selected points enough?
- [Slide 63: How Much to Label? — Four Variants](slide-063.html.md) — The same question: "How likely are you to buy Product A again?"
- [Slide 64: Peaked vs. Flat Response Distribution](slide-064.html.md) — How extreme the endpoints are worded shapes the form of the response distribution.
- [Slide 65: Survey: Measurement and Scaling](slide-065.html.md) — 2.1 Introduction · 2.2 Comparative Scales · 2.3 Non-Comparative Scales · 2.4 Latent Constructs · 2.5 Reliability and Validity
- [Slide 66: Latent Constructs and Multi-Item Scales](slide-066.html.md) — A phenomenon (e.g. customer satisfaction) that is not directly observable or measurable.
- [Slide 67: Latent Constructs: Hierarchy of Measurement](slide-067.html.md) — Construct → Dimensions → Factors → Items → Scale
- [Slide 68: Multi-Item Scales: Advantages](slide-068.html.md) — Advantages & Examples
- [Slide 69: Multi-Item Scales: Make or Steal](slide-069.html.md) — Where do you find ready-made scales?
- [Slide 70: Secure Customer Index](slide-070.html.md) — The Secure Customer Index combines three loyalty indicators into one metric. Only someone who chooses the top level (5) on Secure Customer counts as a…
- [Slide 71: Extended Secure Customer Index by Burke Inc.](slide-071.html.md) — Burke extends the Secure Customer Index by two additional loyalty dimensions (five in total) and links the loyalty index measured in Period 1 with the…
- [Slide 72: Survey: Measurement and Scaling](slide-072.html.md) — 2.1 Introduction · 2.2 Comparative Scales · 2.3 Non-Comparative Scales · 2.4 Latent Constructs · 2.5 Reliability and Validity
- [Slide 73: The True-Score Model](slide-073.html.md) — The result of a measurement is not the true value of a characteristic, but only an observation of it.
- [Slide 74: Reliability and Validity](slide-074.html.md) — Indicates how reliably a measurement instrument measures — i.e. how consistent the results are across repeated measurements.
- [Slide 75: Relationship between Reliability and Validity](slide-075.html.md) — Relationship
- [Slide 76: Why both matter](slide-076.html.md) — The purpose of a scale is to enable us to represent respondents with the highest accuracy and reliability. We cannot have one without the other and still…
- [Slide 77: Net Promoter Score® — a predictor of company growth?](slide-077.html.md) — „How likely is it that you would recommend company/brand/product X to a friend, relative or colleague?"
- [Slide 78: Net Promoter Score®: Warning](slide-078.html.md) — Although the “recommendation question” is by far the best single question for predicting consumer behavior across a range of industries — it is not the…

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*Part of [Principles of Survey Research](../index.md) · Dr. Paul Marx*