qfcharact

Calculates the general factor characteristics: number of flagged Q-sorts, composite reliability, standard errors of factor scores, and comparisons between factors.

Analysis of Q methodology, used to identify distinct perspectives existing within a group.
This methodology is used across social, health and environmental sciences to understand diversity of attitudes, discourses, or decision-making styles (for more information, see <https://qmethod.org/>).
A single function runs the full analysis. Each step can be run separately using the corresponding functions: for automatic flagging of Q-sorts (manual flagging is optional), for statement scores, for distinguishing and consensus statements, and for general characteristics of the factors.
The package allows to choose either principal components or centroid factor extraction, manual or automatic flagging, a number of mathematical methods for rotation (or none), and a number of correlation coefficients for the initial correlation matrix, among many other options.
Additional functions are available to import and export data (from raw *.CSV, 'HTMLQ' and 'FlashQ' *.CSV, 'PQMethod' *.DAT and 'easy-htmlq' *.JSON files), to print and plot, to import raw data from individual *.CSV files, and to make printable cards.
The package also offers functions to print Q cards and to generate Q distributions for study administration.
See further details in the package documentation, and in the web pages below, which include a cookbook, guidelines for more advanced analysis (how to perform manual flagging or change the sign of factors), data management, and a graphical user interface (GUI) for online and offline use.

Aiora Zabala

qmethod

Analysis of Subjective Perspectives Using Q Methodology

Maximilian Held

Frans Hermans

qfcharact function

<dl> <dt>loa</dt>
<dd>matrix or data frame of as many rows as Q-sorts (<code>nqsorts</code>) and <code>nfactors</code> columns, with values of factor loadings for Q-sorts, calculated using, e.g., <code>principal(...)$loadings</code>.</dd> <dt>flagged</dt>
<dd>matrix or data frame of type logical, indicating which Q-sorts are flagged for each factor. Provided manually or automatically using <code>qflag</code>.</dd> <dt>zsc</dt>
<dd>a data frame with the z-scores for statements, calculated using <code>qzscores</code>.</dd> <dt>nfactors</dt>
<dd>number of factors extracted.</dd> <dt>av_rel_coef</dt>
<dd>average reliability coefficient (the individual variability of a respondent), set by default as 0.8.</dd></dl>

Arguments

Author

Q methodology: factor characteristics — qfcharact

<dl>

 <dt>loa</dt>
<dd>matrix or data frame of as many rows as Q-sorts (<code>nqsorts</code>) and <code>nfactors</code> columns, with values of factor loadings for Q-sorts, calculated using, e.g., <code>principal(...)$loadings</code>.</dd>

 <dt>flagged</dt>
<dd>matrix or data frame of type logical, indicating which Q-sorts are flagged for each factor. Provided manually or automatically using <code>qflag</code>.</dd>

 <dt>zsc</dt>
<dd>a data frame with the z-scores for statements, calculated using <code>qzscores</code>.</dd>

 <dt>nfactors</dt>
<dd>number of factors extracted.</dd>

 <dt>av_rel_coef</dt>
<dd>average reliability coefficient (the individual variability of a respondent), set by default as 0.8.</dd>

</dl>

qfcharact: Q methodology: factor characteristics

Description

Usage

Value

Arguments

Author

References