Transcript Document

Survey Design and
Measurement
Jeremy Kees, Ph.D.
Some practical issues….
• Qualtrics Research Platform
– Free you under VSB’s “site license”
– Extremely user friendly, but also very
robust
– www.qualtrics.com
Some practical issues….
• Amazon Mechanical Turk
– The most inexpensive way to collect
consumer data
– Extremely user friendly, but also very
robust
– www.mturk.com
Online Survey (created by you and
housed on Qualtrics’ server)
Create HIT (Human Intelligence Task) on
Mturk
•
Description of your study and a
(Qualtrics) link to it
Mturk workers (survey responders)
“work” on your HIT (i.e., they take your
survey)
Data is recorded by Qualtrics. Participants
who complete the survey are given a code to
input into Mturk. Those that enter a valid
code, get paid.
Everyone is happy   
The Mturk data I collected today….
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N=200
Cost = $100
Data collected in less than 1 hour
Demographics
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Mean age = 36
56% male
76% Caucasian
80% at least some college
• 41% are college grads
– Median income = $35-50k
– Highly engaged!
Stages
in the
Research
Process
Formulate Problem
Determine Research Design
Design Data Collection
Method and Forms
Design Sample and Collect Data
Analyze and Interpret the Data
Prepare the Research Report
Surveys / Questionnaires
• The most common measurement
instrument when quantitative data
is sought
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Descriptive research
Experiments
Modeling
Etc….
Developing Surveys
• Good, well-specified research
objectives lead to good surveys
• Research design dictates what
types of questions should be used
– Exploratory research = unstructured
script
– Confirmatory research = structured
survey
Desirable Characteristics
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Brief
Objective
Specific
Relevant
Survey Methods
• Usually should determine administration
method prior to developing items
– Can dictate what types of questions you
should ask
• Internet panels have become the most
efficient and versatile method to collect
data
– Phone is still a viable option
– Mall intercepts can still be useful
– Mail/fax makes little sense anymore
Mall Intercepts vs. E-Panels
household size
average age
employed
white
male
college
mall
tests
2.8
40.5
71%
86%
20%
40%
internet
tests
2.9
39.2
72%
88%
21%
43%
panel
members
3.0
37.2
69%
89%
15%
46%
Correlation between Responses:
purchase intent
frequency
liking
price / value
mall vs.
internet
.86
.94
.85
.90
internet
test/retest reliability
.94
.97
.91
.99
E-Panels vs. Phone
Time survey took to administer
Internet
12.5
Phone
19.4 minutes
Upon completion, would respondent
participate in future studies?
35% yes
26% yes
More experienced Internet Users
x
Used rating scale extreme “endpoints”
more frequently
Jeff Miller and Alan Hogg “Internet vs. Telephone Data Collection” Burke White Paper series 2 (4)
(www.burke.com). Also see Ashok Ranchhod and Fan Zhou “Comparing Respondents of E-Mail and Mail
Surveys,” Marketing Intelligence & Planning 19 (2001), 254.
x
Types of Questions
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Screening Variables
Independent Variables
Dependent Variables
Classification Variables
– Segmentation
– Moderators
• Attention Filters
Primary Data: Overview
• Types of Primary Data
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Demographic / Socioeconomic Characteristics
Psychological / Lifestyle Characteristics
Attitudes / Opinions
Awareness / Knowledge
Intentions
Motivation
Behavior
• What, how much, where, when, how, who
• Purchase behavior vs. use behavior
• E.g., --- basic hierarchy of effects models
• Example (CWL Study)
QUESTION WORDING - General
Guidelines
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Use simple words and questions
Avoid ambiguous words and questions
Avoid leading questions---be objective
Avoid implicit alternatives
Avoid generalizations and estimates --Be specific
• Avoid double-barreled questions
1. What is your income?
$10,000 or less………………….1
$10,000 to $25,000……………..2
$25,000 to $50,000……………..3
$50,000 to $75,000………..…….4
$75,000 to $100,000..……..…….5
$100,000 or more…………..……6
What is the problem and how would you
revise the question?
4. Is the speed and efficiency of the drive-in teller
services at your regular bank…..(READ
CATEGORIES)
Very Satisfactory………………………4
Somewhat satisfactory…………………3
Somewhat unsatisfactory………………2
Very unsatisfactory……………….……1
Question Wording
• It is good practice to use scales
whenever possible
– Likert or semantic differential
– Multi-item
Itemized Rating Scales
• The respondents are provided with a scale that
has a number or brief description associated
with each category.
• The categories are ordered in terms of scale
position, and the respondents are required to
select the specified category that best describes
the object being rated.
• The commonly used itemized rating scales are
the Likert and semantic differential
Types of Scales
• Nominal scales: those that use only
labels
• Ordinal scales: those with which the
researcher can rank-order the
respondents or responses
• Interval scales: those in which the
distance between each descriptor is
equal
• Ratio scales: ones in which a true zero
exists
Examples…
Nominal
Ordinal
Which of the soft drinks in the
following list do you like?
(Check ALL that apply):
___Coke
___Dr. Pepper
___Mountain Dew
___Pepsi
___Seven Up
___Sprite
Rank the soft drinks according to how much you
like each (most preferred drink = 1, and least
preferred drink = 6):
___Coke
___Dr. Pepper
___Mountain Dew
___Pepsi
___Seven Up
___Sprite
Interval
Ratio
Please indicate how much you like each soft
drink by checking the appropriate position on the
scale:
dislike
like
a lot dislike like
a lot
Coke
____ ____ ____ ___
Dr. Pepper
____ ____ ____ ___
Mountain Dew
____ ____ ____ ___
Pepsi
____ ____ ____ ___
Seven Up
____ ____ ____ ___
Sprite
____ ____ ____ ___
Please divide 100 points among these soft drinks
To represent how much you like each:
___Coke
___Dr. Pepper
___Mountain Dew
___Pepsi
___Seven Up
___Sprite
100
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Itemized Rating Scales
• Likert Scales
– requires the respondents to indicate a degree of
agreement or disagreement with each of a series of
statements about the stimulus objects
Strongly
disagree
Disagree
Neither
agree nor
disagree
Agree
Strongly
agree
1.
Wal-Mart sells high quality merchandise. 1
2X
3
4
5
2.
Wal-Mart has poor in-store service.
1
2X
3
4
5
3.
I like to shop at Wal-Mart .
1
2
3X
4
5
4.
Wal-Mart has low prices .
1
2
3X
4
5
Itemized Rating Scales
• Semantic Differential Scales
– End points associated with bipolar labels that have
semantic meaning
SEARS IS:
Powerful
--:--:--:--:-X-:--:--: Weak
Unreliable --:--:--:--:--:-X-:--: Reliable
Modern
--:--:--:--:--:--:-X-: Oldfashioned
Decisions for Itemized Scales
• Number of scale items
• More is better, but there is a diminishing return
around 11 points (Nunnally 1978)
• 7-point scales are customary
• Enough to discriminate
• Allows for a scale midpoint
• Manageable
• Odd/even number of categories
• Forced vs. non-forced
Why Multi-Item Scales??
Construct
Abstract Concept
“Unobservable”
“Latent”
“Psychological”
**Single items are typically not sufficient
to assess unobservable constructs
Multi-Item Scales are More
“Reliable”
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True Score Test Theory
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All measures have
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“True” Score
“Error” (Random and Systematic)
Good measures minimize the
systematic error component of the
score
Types of Reliability
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Inter-Rater
Test-Retest
Internal Consistency (Cronbach’s Alpha)
Developing Sound Measures
Step 1:
Specify Domain
of the Construct
Step 2:
Generate Sample
of Items
Step 3:
Collect Data
Step 4:
Purify Measure
Step 5:
Assess Validity
Question Sequencing
• After you have developed your
measures, think about the order in
which they should be asked
QUESTION SEQUENCING General Guidelines
• Use (more) simple, interesting opening
questions
• Use the funnel approach, asking broad
questions first, and follow with more
specific questions
• Carefully design branching questions
– Skip/display logic
– Ask for classification information last
• Place more difficult or sensitive
questions near the end
QUESTION SEQUENCING General Guidelines
Question ordering #1
1 – EVALUATION OF FAT LEVEL OF A PRODUCT
2 – EVALUATION OF OVERALL PROD. NUTRITIOUSNESS
3 – EVALUATION OF OVERALL PRODUCT ATTITUDE
AND INTENTIONS TO PURCHASE
Question ordering #2
1 – EVALUATION OF OVERALL PRODUCT ATTITUDE
AND INTENTIONS TO PURCHASE
2 – EVALUATION OF LEVEL OF PROD. NUTRITIOUSNESS
3 – EVALUATION OF FAT LEVEL OF PRODUCT
FOP Labeling Study
• We were interested in consumer
evaluations of:
1. Facts Up Front
2. All On-Package Labeling
3. Front-of-Package Nutrition Info
Why was question sequencing
critical??
Tips for Maximizing Participation
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Offer an incentive ($$$)
Importance/relevance of the research
project and its purpose
Completing the questionnaire will take
only a short time
Answers are anonymous or
confidential
Reminder 2-3 days after the initial ask
Attention Filters
• Always include an attention filter
to ensure that you are getting
“quality” respondents
– Eliminate “click throughs”
Attention Filters (Case Study)
• Advertising Experiment
– Very stringent screening criteria
• Total # that started the study = 15,458
• Number that qualified = 870
– Incidence Rate (IR) = 5.6%
• Number that qualified and passed the
attention screener = 451
– 48% failed the attention filter!!!
• NOT GOOD, criticalmix!
“Easy” Attention Filter
“Difficult” Attention Filter
And finally, remember the
golden rule….
Do unto your respondents as you
would have them do unto you!!
Team Assignment #2
• Refine your research questions
– Need to be clear, concise, and “testable”
• Based on your research questions
1. Design 2 potential studies that could
address your research questions
1.
2.
Explain the benefits and weaknesses of each
approach
Pick the “best” design and explain your
decision
(Note: Don’t worry about measurement or sampling too
much---you’ll have your chance to do that later)
Team Assignment #3
** Don’t start on this assignment until
you’ve read Fowler (CH 6-7)
• Based on your research design
1. Write a paragraph about what your
measurement instrument is supposed to
accomplish
2. Make a list of what should be measured to
accomplish the goals of the study
3. Develop your measurement instrument
Team Assignment #3
• Deliverables include:
1. A very clean, polished version that you
could use to actually collect data
•
This means you will need to carefully think
through all of the issues we covered tonight
(e.g., set-up, ordering, length, multi-item
scales, etc.)
2. Intro paragraph and variable list (see
previous slide)
(Note: Don’t worry about defining your sample--you’ll
have your chance to do that next week)