Workshop on Q methodology

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Workshop on Q methodology

• Midwestern Educational Research Association
• St. Louis, MO
• 8 920 AM
• October 25, 2007
• Sue Ramlo
• Joe Jurczyk

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About the presenters

• Sue Ramlo, PhD
• Physicist w/ PhD in Curricular Instructional
  Studies
• Presentations of Q studies
• Published Q studies
• Editorial board of both Q journals (English)
• Operant Subjectivity
• Human Subjectivity
• Previous Q workshop developer

• Joe Jurczyk
• Systems Engineer w/ MBA ABD in CI
• Dissertation developing evaluating a
  versatile on-line Q-sort tool
• Presentations of Q studies
• Previous Q workshop presenter

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Workshop Outline

• Introduction to Q methodology
• Sorting items onto a normal Gaussian distribution
• Concourse of items the Q sample
• Analyzing the sorts using PQ Method factors
  interpretation
• Why groups of people?
• Examples of Q studies

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Introduction to Q methodology - Overview

• Investigate the views, or perspectives, of a
  person or a group of people.
• Process involves
• Creating a concourse of items (text, sounds,
  pictures).
• Sorting a sample of the items into a normal
  Gaussian distribution.
• Sorts are factor analysized to group people with
  similar sorts (Note R FA groups items).

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Sorting items onto a normal Gaussian distribution

• Pre-sort into 3 piles
• Distribute ( re-distribute) to fit specific
  normal Gaussian distribution.

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Now you try it!

• Condition of instruction Because youve been
  working so hard, your boss is going to give you a
  bonus in the form of a one year vehicle lease
  he wants your input. In the envelope you have
  received, there are pictures of a variety of
  different vehicles. Rate these items on a scale
  of most desired (4) to most undesired
  (-4).

• Pre-sort into 3 piles
• Distribute ( re-distribute) to fit specific
  normal Gaussian distribution.

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Introduction to Q methodology historical
background

• Developed in 1935 by William Stephenson
• Physicist-psychologist
• Student of Spearman
• A Study of Behavior, 1955
• Q for Quantum
• Most typically used in fields of psychology,
  marketing, advertising, political science
• Mixes quantitative qualitative aspects of
  research

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Why not another method to determine views?

• Alternatives for determining perspectives are not
  as powerful as Q (McKeown, 2001).
• Likert scale evaluations and rank ordering lead
  to the loss of meaning (McKeown, 2001) e.g.
  aggregate results
• Because Q measures personal opinion regarding a
  concourse of items related to a topic, validity
  is not a consideration (Brown, 1999).

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What is meant by subjectivity?

• What do you see? Bunny? Duck?
• Is one right the other wrong or are they both
  just different views?

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Any Q study starts with a concourse

• Can consist of words / statements, pictures,
  sounds, smells
• Subjective
• Not Its raining
• But can be the rain makes me feel sad or- I
  love to walk in the rain.
• Items are interpreted by participant removes
  the view of the researcher the issue of
  validity / reliability.
• Select the Q sample from the concourse
• Try to balance the Q sample
• Sample needs to be sufficiently large sample
  size here is the number of items, not the number
  of people in the study

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Concourse of items 3 possibilities

• Naturalistic statements - taken from
  participants oral or written communications.
• Interviews
• Focus Groups
• Ready made statements - from sources other
  than those of the participants communications.
• Likert survey items
• Based on knowledge of researcher w/o interviews
• Hybrid - combine both naturalistic and ready
  made items.
• One is not inherently superior to the other
  (McKeown Thomas, 1988).
• Researcher selects the type best suited to the
  project at hand

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Q sample select items from the concourse to use
in the study.

• Example Selection from a Q sample of 44 (chosen
  from a concourse of 74)

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Condition of instruction

• Participants sort based upon a condition of
  instruction (or multiple conditions).
• E.g. Sort the following statements as they relate
  to your views about learning in this class.
• The statements are matters of subjective opinion
  and may mean different things to different
  people.
• Meaning is determined by sorter, not researcher
• Reason why validity is not a consideration
• e.g. I worked hard in this class.

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Analyzing Q sorts

• SPSS SAS not really designed for Q sorts you
  mess with weightings, etc.
• Need software designed for Q methodology
• PCQ
• PQMethod
• QUANAL

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Factor Analysis

• Higher order correlation
• Used to determine patterns in a data set
• R-factor analysis groups items (people are rows,
  items are in columns). Factors represent similar
  items. Objective.
• Q-factor analysis groups people (people are in
  columns, items are in rows). The factors
  represent people with similar topologies.
  Objective
• Q methodology is not Q FA but does group people
  based upon their VIEWS on a subject. Factors
  represent similar views about a topic.
  Subjective.

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PQ Method to determine factors assist in their
interpretation

• PQMethod
• Free download (start at www.qmethod.org)
• DOS based
• Designed for handling Q sort entry and analyses
• Choices
• Centroid versus Principal Components factor
  extraction
• Graphical hand rotation versus Varimax
• Start PQMethod

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PQMethod Analyses

• Creates print out with
• Factor loadings
• Factor correlations
• Distinguishing statements
• Consensus statements, etc
• Example - knowledge Tech Physics sorts Ramlo
  2006.lis.

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Results

• Different factors represent the various views
  within the P-set
• More democratic, not simply majority wins
• Allows further investigation (linear regression,
  etc) especially if groups not known a priori
• Consensus allows researcher to see where there is
  agreement
• Organizational change theory

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For more on Q methodology

• www.qmethod.org
• I4S International Society for the Scientific
  Study of Subjectivity Next conference in
  Hamilton, ON Sept/Oct. 2008
• Brown, S. R. (1980). Political subjectivity
  Applications of Q methodology in political
  science. New Haven Yale University Press.
• McKeown, B., Thomas, D. (1988). Q methodology.
  Newbury Park, Calif. Sage Publications.
• Stephenson, W. (1955). The study of behavior
  Q-technique and its methodology. Chicago
  University of Chicago Press.