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Workshop on Q methodology

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Presentation on theme: "Workshop on Q methodology"— Presentation transcript:

1 Workshop on Q methodology
Midwestern Educational Research Association St. Louis, MO 8 – 9:20 AM October 25, 2007 Sue Ramlo Joe Jurczyk

2 About the presenters: Sue Ramlo, PhD Joe Jurczyk
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 C&I Dissertation – developing & evaluating a versatile on-line Q-sort tool Presentations of Q studies Previous Q workshop presenter

3 Workshop Outline Introduction to Q methodology Why groups of people?
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

4 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).

5 Sorting items onto a normal Gaussian distribution
Pre-sort into 3 piles Distribute (& re-distribute) to fit specific normal Gaussian distribution. Most UNlike my view (~14 statements here) MOST like my view Neutral view about this statement

6 Now you try it! Condition of instruction – Because you’ve 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)….” Most undesirable (~7 items) MOST desirable Neutral view about this statement Pre-sort into 3 piles Distribute (& re-distribute) to fit specific normal Gaussian distribution.

7 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

8 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).

9 What is meant by subjectivity?
What do you see? Bunny? Duck? Is one right & the other wrong or are they both just different views?

10 Any Q study starts with a concourse:
Can consist of words / statements, pictures, sounds, smells… Subjective Not “It’s 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}

11 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

12 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)

13 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.

14 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

15 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.

16 PQ Method to determine factors & assist in their interpretation
Free download (start at DOS based Designed for handling Q sort entry and analyses Choices Centroid versus Principal Components factor extraction Graphical hand rotation versus Varimax Start PQMethod

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

18 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

19 For more on Q methodology:
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.

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