2017RePEc: Research Papers in EconomicsRequires access

QPAIR: Stata module to perform Q-analysis on paired Q-sorts using different factor extraction and factor rotation techniques

Noori Akhtar‐Danesh

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Abstract

qpair performs by-person factor analysis on paired Q-sorts. The command performs factor analysis on pairs of Q-sorts (matched Q-sorts) using either principal factor, iterated principal factor, or principal-component factor extraction methods. qpair is also able to rotate factors using all factor rotation techniques available in Stata (orthogonal and oblique) including varimax, quartimax, equamax, obminin, and promax. qpair displays the eigenvalues of the correlation matrix, the factor loadings, and the uniqueness of the variables. It also provides number of Q-sorts loaded on each factor, distinguishing statements for each factor, and consensus statements. qpair is able to handle bipolar factors and identify distinguishing statements based on Cohen's effect size (d).

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What this paper is about

qpair performs by-person factor analysis on paired Q-sorts. The command performs factor analysis on pairs of Q-sorts (matched Q-sorts) using either principal factor, iterated principal factor, or principal-component factor extraction methods. qpair is also able to rotate factors using all factor rotation techniques available in Stata (orthogonal and oblique) including varimax, quartimax, equamax, obminin, and promax. qpair displays the eigenvalues of the correlation matrix, the factor loadings, and the uniqueness of the variables. It also provides number of Q-sorts loaded on each factor, distinguishing statements for each factor, and consensus statements. qpair is able to handle bipolar factors and identify distinguishing statements based on Cohen's effect size (d).

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Available abstract

qpair performs by-person factor analysis on paired Q-sorts. The command performs factor analysis on pairs of Q-sorts (matched Q-sorts) using either principal factor, iterated principal factor, or principal-component factor extraction methods. qpair is also able to rotate factors using all factor rotation techniques available in Stata (orthogonal and oblique) including varimax, quartimax, equamax, obminin, and promax. qpair displays the eigenvalues of the correlation matrix, the factor loadings, and the uniqueness of the variables. It also provides number of Q-sorts loaded on each factor, distinguishing statements for each factor, and consensus statements. qpair is able to handle bipolar factors and identify distinguishing statements based on Cohen's effect size (d).

Key concepts: Principal component analysis, Factor (programming language), Factor analysis, Iterated function, Mathematics, Uniqueness, Statistics, Rotation (mathematics)

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