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About handling files:

• Why won't my Study File load?
• The program can't find my file. Why is that?
• Can a Study File name be changed?
• How can I import from PQmethod or Excel?

 

About parameter requirements:

• Why are there limits on the number of sorts and items?
• Why does the program only allow "forced" pile distributions?

 
About handling sorts and items:

• Is "item" synonymous with "statement"?
• Do I have to type in the items?
• What is a Q sample?
• What does the act of sorting signify?
• What are sort labels?
• How does the drag-and-drop feature work?
• How does the Least-Most feature work?

 
About contacting PCQ Software:

• How can I submit a bug report?
• How do I find out about updates?

About extracting factors:

• Why do we factor?
• How many factors are enough?
• What is a correlation?
• What roles do correlations play in factor analysis?
• What does "reflection" mean?
• What is a centroid?
• Why does PCQ restrict the number of factors?
• What does "significance level mean"?

 
About rotating factors:

• Why is it called "judgmental rotation"?
• Why is it called Varimax?
• How can I save or print a graph?

 
About handling the final Log Report:

• Will the program use both Varimax and Judgmental rotations for the final Log Report?
• Why are there so many tables?
• What does the correlation table tell us?
• What is the Factor Summary

 

 


Q: Why won't my Study File load?

A: The implication in the question suggests two likely possibilities, both being rather technical. One possibility has to do with PCQ data formats and the other with word processing program file coding formats. (1) Editing and changing a Study File outside of PCQ can cause the first kind of  problem because PCQ is very sensitive to how the data lines are constructed. (2) Problems of the second kind can occur if the Study File was opened in a word processing program and then saved. PCQ can only read ASCII text files; it cannot read the special coding formats used by Microsoft Word or WordPerfect. Please refer to How a Study File is Organized and Editing a Study File in the Technical Notes section.

Q: I named my study file BLAY.STY but when I try to load it, the computer cannot find my file. Why is that?

A: The file you want is probably stored in another folder in your computer. Use the Windows File Find features to search for it. Then, for convenience, you may want to copy the file into the folder containing other Study Files. To change the default Study File folder, click on File and select Preferences.

Q: Where is the best place to keep study files?

A: While any folder will do, keeping Study Files together is useful considering the large disk drives commonly in use. The default Study File folder created by the program is C:\PCQ\Studies.

Q: Can a Study File name be changed?

A: Yes. To change the name, open the Study File in Notepad. Replace Line 1 with the new name. Then, use the Save As feature to save the file under the new name.

Q: What are sort labels?

A: Use a label to briefly description each sort. Labels will be useful reminders during Judgmental Rotation and will help in reading the Final Log Report.

Q: How does the drag-and-drop feature work?
Q: How does the Least-Most feature work?

A: Entering data is tedious and one is prone to make errors when simply typing in the numbers. Drag-and-Drop allows you to click on an item in a list and "drop" it into a particular pile in the form. The Least-Most feature is also simple. Click on an item; then click on Least to record it in the lowest available pile or Most to record it in the highest available pile.

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Q:  Is "item" synonymous with "statement"?

A:
Yes, the words refer to the phrases, symbols or objects that make up a Q sample. In Q technique, whatever can be sorted can be referred to as an "item", including phrases, statements, symbols, pictures and other objects as well. Q studies have been conducted using a wide variety of stimuli. For example, in one of Stephenson's early Q studies, people were asked to sort aromas. The Q sample was the contents of a set of small bottles, each containing a different substance. Zero was represented by a bottle filled with plain water.

Q: Do I have to type in the items for my study file?

A: No, if you mean that the program requires you to type in the statements. However, this feature is very helpful when examining the Log Report because they make it much easier to compare items across the factor arrays.

Q: I want to import data from a principal components study. How do I do this?

A: The program will import parameters, sorts and items data from PQmethod. Imported data, however, must be within PCQ for Windows minimums and maximums: 5 to 125 sorts; 5 to 200 items. Attempting to exceed these maximums will, as they say, produce unexpected results. For detailed instructions, please see Importing Data.

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Q: Why do we factor?

A: Sometimes a simple question suggests a complicated answer, but this would be beyond the scope of this FAQ. One good reason for factoring is that Q technique uses factor analysis to find communalities within the relationships between the sorts. In other words, factoring satisfies an important requisite of Q methodology in that it provides a means to integration in an indeterministic framework.

Q: How many factors are enough?

A: Mathematically inclined factor analysts have argued this question for decades. In Q technique, the answer is indeterminant; that is to say, that the desirable number of factors depends more on the theoretical requirements established by the researcher and less on the mathematical standards. For example, for some purposes, a researcher may have a strategy of rotating toward fewest factors that account for the most sorts. In other circumstances, however, it may be desirable to rotate toward more factors.

Q: What is a correlation?

A: Aside from mathematical definitions, which can be found in any introductory statistics textbook, it is useful to think of a correlation as a very precise expression of a relationship between two sorts. For example, a correlation indicates similarity between two sorts; a low correlation indicates the sorts have little in common. A perfect correlation of 1.0 is a rare occurrence indeed.

Q: What roles do correlations play in factor analysis?

A:  Correlations articulate the relationships between all the sorts in mathematical terms. The collection of all of them are presented as a table of correlations. This table provides the basic mathematical relationships from which factors are extracted.

Q: What does "reflection" mean?

A: In centroid factor analysis, the columns of correlations are summed. From time to time a column sum is a negative value, meaning that some of the correlations between the sorts are negative to the degree that they yield a negative sum. Since the concepts of negative and positive in factor analysis are arbitrary, when a negative column sum is encountered during factor extraction the program multiplies each correlation in that column (and the coordinate row) by -1. Consider the tables below, with correlations for five sorts. As it happens, before reflection all column sums are negative, so when they are summed the Table Sum is also negative.

 

=============================
Before reflection
=============================
Sort   1    2    3    4     5
-----------------------------
1      0  -40   60  -61  -16
2    -40    0  -64   14  -12
3     60  -64    0  -16    5
4    -61   14  -16    0   22
5    -16  -12    5   22    0
-----------------------------
Col  -57 -102  -15  -41   -1
sums                     -216 = Table sum
-----------------------------
Note: Leading decimals have been omitted.

 

=============================
After reflection of Col. 2
=============================
Sort  1    2    3    4     5
-----------------------------
1     0   40   60  -61   -16
2    40    0    64   14   12
3    60   64    0   -16    5
4   -61   14  -16    0    22
5   -16   12    5   22     0
-----------------------------
Col   23  130  113  -41   23
sums                      248 = Table sum
-----------------------------

Disregarding signs, column 2 has the largest absolute sum and is the best candidate for reflection. To change the signs, multiply each correlation in column 2 and row 2 by the quantity -1. This way all the negative correlations in column 2 and row 2 are made positive and all the positive correlations are made negative. The table on the right shows the impact of this operation:

There are two results. Reflection produces a positive sum for the column, but it also produces a change in signs across the row and therefore changes the sums of all the other columns. Then all the columns are summed again, which produces a change in the Table sum from -216 to +248. Notice that column 4 is still negative, and it should be reflected next. The objective of reflection is to produce the largest positive sum for the entire table, with the fewest number of negative correlations. In the literature, this goal is called a "positive manifold." Achieving it is important because the Table sum determines how much variance can be accounted for when a factor is extracted.

Q: What is a centroid?

A: A centroid can be thought of as a kind of grand average of the relationships between all the sorts, as they are represented by their correlation coefficients. In other words, Centroid Analysis is a way of defining centers of gravity embedded in a correlation matrix. In physics, a center of gravity turns out to be where the weight tends to fall on average. For us this concept can be represented as a vector that spans the longest dimension of the data space. The factor loadings, then, are values expressing each sort’s relationship with the centroid. Each loading represents a sort’s contribution to the length of the centroid, and thus can be expressed as the correlation of that sort with the centroid.

Q: Why does PCQ restrict the number of factors?

A
: As a practical matter, the results of a Q study can be thought of as dimensions of communicability embedded in the concourse from which the Q sample is a representation. This implies that, while a communication situation will have several dimensions, more than nine of them is unlikely. PCQ was designed with this concept in mind. A researcher seeking more dimensions is advised to use principal component factor analysis, which can be found in many commercially available statistical software programs. Since principal component factor analysis produces factors that account for 100 percent of the correlation table variance, often there are as many factors as there are variables.

 

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Q: Why is it called "Judgmental Rotation"?

A: Very often the researcher has specific theoretical goals in mind in conducting a communication experiment using a Q study: reasons for selecting a particular Q sample, for selecting the people to provide the Q sorts. In PCQ for Windows, rotations can be performed that take the theory into account. For example, suppose that a group of nurses, including the chief of nursing, have provided sorts. Rotating to maximize the chief of nursing's sort may reveal relationships hither to unrecognized. Since it is the researcher who decides to rotate in this way, it is called "Judgmental Rotation."

Q: Why is it called Varimax?

A: This approach to factor rotation is strictly mathematical. Through an iterative process, variance is distributed across the factor structure in such a way that each sort has highest degree of association with only one factor, all sorts and all factors being taken into consideration.

 

Q: How can I save or print a graph?

A:
A number of freeware programs will capture graphical images. Once a screen has been captured, the image can either be saved as a file or printed. Please note: Start the screen capture program before beginning a Judgmental Rotation.

 

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Q: How do I modify what will be saved in the Log Report file?

A: At the PCQ File Menu, select Preferences. Click the tables you want to have saved in the Log Report.

 

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Q: How can I submit a bug report?

A: We welcome your help in uncovering bugs. Please click here to send your message.

Q: How do I find out about updates?

A: If you have purchased PCQ for Windows or have registered for notifications, you will be notified by email of updates.

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Q: Why are there limits on the number of sorts and items?

A: If you are curious about the computational power of contemporary personal computers, many more sorts and items are possible. (In a test, PCQ for Windows has factored 600 sorts, each with 100 items.)  However, from a theoretical standpoint, very few Q Studies contain more than 100 items and 100 sorts. In considering sorts, it is important to remember that Q Methodology experiments with communication possibilities in the Q sample. The people who perform the sorts are, in a defensible way, the measuring devices. Thus, 50 sorters produce 50 independent measurements of the Q sample. As a practical matter, 200 items is equivalent to four decks of Bridge cards, and a Q sample with more than 40 items or so will reduce the willingness of people to sort them.

 

Q: Why does the program only allow "forced" pile distributions?

A:
Another way to think about pile distributions would be "symmetrical". A preference for symmetry is understandable because a Q sample has been constructed for experimental purposes with an understanding that a sorter is likely to have strong preferences -- both positively and negatively -- for few statements. Also, since the sorts are normalized in correlation, forced and unforced distributions yield very similar factor structures.

 

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Q: What is a Q sample?

A: A Q sample is a representative subset of a range of communication on any topic. It may be comprised of statements, phrases, pictures or other symbols that are representative of the much larger flow of communication -- referred to as a concourse -- associated with a topic.

Q: What does the act of sorting signify?

A: Generally speaking, sorting is a model of human communication in action. When sorting, a person is literally "in conversation" with her/himself regarding the statements in the Q sample. When completed the statements have been put into positions (or rank ordered) assigned by the sorter. Significantly, the positions of the statements are relative one to the others in a way that can only be provided by the sorter. Using Q technique the rank orders of every sort can be formally analyzed.

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Q: PCQ for Windows says the significance level is .36 for my study. I want to set it higher. How do I do that?

A: You can change the significance level in more than one place, the most convenient being during the Rotation process. You may set the level either or higher or lower than the number calculated by the program. The value you set will be used until you change it, both during rotation and when generating the Final Report. PCQ for Windows will not allow the level to be set higher than .90 or less than .10.

Q: What does "significance level mean"?

A:
  Another way to think of this question would be to ask, "By what criteria is a sort associated with a factor?" In Q technique, it is the significance level that provides an answer. It is usually set equal to or greater than the value of two standard deviations away from the mean. The choice of two standard deviations is not entirely arbitrary because this translates into the conventionally accepted probability statistic p < 0.01, which means 99 percent of the area under a normal curve. The significance level, then, answers the question, "Given a certain number of items, at what magnitude would 99 out of 100 loadings be excluded from the factor?" The significance level is, therefore, a statistic directly related to the number of items in the Q sample; i.e., as the number of items increases, the theoretical significance level decreases, and, conversely, the smaller the number of items, the higher the theoretical significance level. In non-technical terms, the effect of raising or lowering the significance level raises or lowers the difficulty of gaining association with a factor. Setting the level lower means easier membership; setting it higher means more restricted membership. For example, a typical Q sample might contain 48 items. The program calculates the theoretical significance level as being ± .31, meaning a sort must have a factor loading of at least .31 to become associated with a factor.

 

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Q: Will the program use both Varimax and judgmental rotations for the Final Log Report?

A:
The program is flexible regarding rotation. You may choose to perform both Varimax and Graphical (Judgmental) rotations. Tip: Choose Varimax first to get a mathematical solution. Then, if you wish you may select the Graphical method and choose to start with either the Unrotated or the Varimax factor loadings. For example, you may use Varimax factor loadings and later choose to begin with the Unrotated loadings. Please remember, though, that the Final Log Report will be based upon the last rotations you performed.

 

Q: Why are there so many tables?

A:
If you are thinking about the size of the Final Log Report file, you can choose which tables you want to exclude. Choose the File Menu and click on Preferences. Many of the tables are generated to help you analyze the factor arrays. For example, take a look at a table of Descending Array of Differences between any two factors to see which items have been order differently.

 

Q: What does the Correlation Table tell us?

A:
Since the correlations of the sorts are the raw data for factor analysis, one can examine the correlation table to identify the relationships between any of the sorts.

 

Q: I don't understand the Q study summary of factors in the Log File.

A: This summary contains much information. First, each factor is described in a listing of the sorts contributing to the factor. Contributing sorts are defined as those having an absolute value greater than the significance level. Factors with no sorts are listed next. Any sorts with significant loadings on more than one factor are designated as "confounded." Any sorts with no significant loadings are listed next. A factor with both positive and negative sorts is designated as "bipolar." The last line states how many of the sorts have been accounted for in how many factors.

 

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Please send comments on this web page to woods.stricklin@pcqsales.com

Copyright © 2000, 2001, 2002, 2003, 2004 Michael Stricklin & Ricardo Almeida (All Rights Reserved)

Last update on 09 March 2010.