Hi Dear Ralph Cattermole,

Clearly, Q methodology has long been used by researchers to estimate participants' subjective viewpoints about a certain variable. After defining the categories and subcategories underpinning the variable, a number of statements are written for each and the participants are asked for a Q-sort using a symmetrical Q-grid.  Finally, a factor analysis is run to find common ranking of the statements by the participants. You can use PQ Method 2.11 software for the factor analysis. For more information, I refer you to an article named, " Q Methodology: An Overview" by Coogan and Herrington (2011).

Good Luck.

R. Biria

Hi Reza Biria,

I currently am engaged in conducting a qmethod inquiry and am at the results and interpretation stage. the qmethod has much literature to support it, however it is seemingly difficult from a beginners point of view when looking at what the analysis programs spit out and what to display in the results section, i am currently reading Doing Q Methodological Research by Watts and Stenner 2012. which is a great resource, but again uses complex language that it expects the reader to know.

Ultimately i was just after someone to discuss my results and thoughts with. Also the forum described in the paper you spoke of above is sadly no longer available.

Many thanks,

Ralph

Have you constructed prototype sorts for each of the resultant viewpoints?  That can make interpretation much easier.  At the end of the PQMethod output there should be a list of all statements, ranked in order of 'importance' for each point of view (according to size of Z-score for each statement I think).  You can use these to physically recreate a completed sort for each factor (i.e. greater score=greater 'agreement' with the statement within each factor).

In the past I have grouped similar statements into loose themes and applied a  colour code to each theme.  Then, when you recreate the prototype factor, you can quickly see how statements within each theme are spread across the array.  Finally, in the PQMethod output there are statistics indicating the statements on which there was greatest agreement and disagreement across factors.  You can use these to assist your interpretation also.  This information should enable you to construct a narrative  summarising each point of view.

I have been using PCQ software, which is adequate for identifying significant sorters and correlations of beliefs, viewpoints, etc. The downside to this software is I cannot find a way to extract Z scores. If anyone knows how to extract Z scores from PCQ softwre, I am all ears.