Applies the two standard algorithms to pre-flag Q-sorts automatically, for posterior calculation of the statement scores.

`qflag(loa, nstat)`

loa

nstat

number of statements in the study.

These are the two standard criteria for automatic flagging used in Q method analysis:

Q-sorts which factor loading is higher than the threshold for p-value < 0.05, and

Q-sorts which square loading is higher than the sum of square loadings of the same Q-sort in all other factors.

Returns a logical matrix with Q-sorts as rows, and factors as columns.

Brown, S. R., 1980 *Political subjectivity: Applications of Q methodology in political science*, New Haven, CT: Yale University Press.

Van Exel, J., de Graaf, G., Rietveld, P., 2011. "'I can do perfectly well without a car!'" *Transportation* 38, 383-407 (Page 388, footnote 8).

See further references on the methodology in `qmethod-package`

.

# NOT RUN { data(lipset) library(psych) loa <- as.data.frame(unclass(principal(lipset[[1]], nfactors = 3, rotate = "varimax")$loadings)) flagged <- qflag(loa = loa, nstat = nrow(lipset[[1]])) summary(flagged) # }

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