PQMethod is a statistical program tailored to the requirements of Q studies. Specifically, it allows to easily enter data (Q-Sorts) the way they are collected, i.e. as 'piles' of statement numbers. It computes intercorrelations among Q-Sorts, which are then factor-analysed with either the Centroid or Principal Component method. Resulting factors can be rotated either analytically (Varimax), or judgmentally with the help of two-dimensional plots. Finally, after selecting the relevant factors and 'flagging' the entries that shall define the factors, the analysis step produces an extensive report with a variety of tables on factor loadings, statement factor scores, discriminating statements for each of the factors as well as consensus statements across factors, etc.
Dr Grover check this out if it helps you?http://schmolck.userweb.mwn.de/qmethod/pqmanual.htm
PQMethod is a statistical program tailored to the requirements of Q studies. Specifically, it allows to easily enter data (Q-Sorts) the way they are collected, i.e. as 'piles' of statement numbers. It computes intercorrelations among Q-Sorts, which are then factor-analysed with either the Centroid or Principal Component method. Resulting factors can be rotated either analytically (Varimax), or judgmentally with the help of two-dimensional plots. Finally, after selecting the relevant factors and 'flagging' the entries that shall define the factors, the analysis step produces an extensive report with a variety of tables on factor loadings, statement factor scores, discriminating statements for each of the factors as well as consensus statements across factors, etc.
Dr Grover check this out if it helps you?http://schmolck.userweb.mwn.de/qmethod/pqmanual.htm
Further to Béatrice Ewalds-Kvist's reply, there is another dedicated Q Methodology software package- PCQ - which provides a similar range of features as PQMethod. Unlike PQMethod, PCQ is a commercial package and has to be purchased. For further information see http://www.pcqsoft.com
Both of these packages provide user-friendly procedures for the input, analysis and interpretation of Q Methodology data.