qmethod (version 1.5.5)

## Description

Calculates factor characteristics, z-scores, and factor scores, provided a matrix of loadings and a matrix of (manually or automatically) flagged Q-sorts.

## Usage

```qzscores(dataset, nfactors, loa, flagged, forced = TRUE,
distribution = NULL)```

## Arguments

dataset

a matrix or a data frame containing raw data, with statements as rows, Q-sorts as columns, and the column scores in the distribution in each cell.

nfactors

number of factors to extract.

loa

matrix or data frame of `nqsorts` rows and `nfactors` columns, with values of factor loadings for Q-sorts, calculated using, e.g., `principal(...)\$loadings`.

flagged

matrix or data frame of `nqsorts` rows and `nfactors` columns, with `TRUE` values for the Q-sorts that are flagged. Automatic flagging can be aplied using `qflag`. Manual flagging can be done by providing a logical matrix with `nqsorts` rows and `nfactors` columns to the argument `flagged`.

forced

logical; Is the distribution of items forced? Set to `TRUE` if all respondents ranked the items following strictly the distribution scores, and the values of the distribution are calculated automatically. Set to `FALSE` if respondents were able to rank the items without following the distribution, and the values of the distribution have to be provided as an array in the argument `distribution`.

distribution

logical; when `forced = FALSE`, the distribution has to be provided as a vector of numbers, such as `c(-2, -1, -1, 0, 1, 1, 2, 2)`.

## Value

Returns a list of class `QmethodRes`, with seven objects:

brief

a list with the basic values of the analysis: date (`"date"`), number of statements (`"nstat"`), number of Q-sorts (`"nqsort"`), whether the distribution was 'forced' (`"distro"`), number of factors extracted (`"nfactors"`), type or rotation (`"rotation"`), method for correlation in the PCA (`"cor.method"`), and a summary of this information for display purposes (`"info"`).

dataset

original data.

loa

flagged

logical dataframe of flagged Q-sorts.

zsc

statements z-scores.

zsc_n

statements rounded scores, rounded to the values in the first row of the original dataset.

f_char

factor characteristics obtained from `qfcharact`.

## Details

In order to implement manual flagging, use a manually created data frame for `flagged`. See an example of code to perform manual flagging or to manipulate the loadings in https://github.com/aiorazabala/qmethod/wiki/Advanced-analysis.

The loadings from `principal(...)\$loadings` can be explored to decide upon flagging. The `loa` data frame should have Q-sorts as rows, and factors as columns, where `TRUE` are the flagged Q-sorts.

## References

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

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

## Examples

Run this code
```# NOT RUN {
data(lipset)
library(psych)
loa <- as.data.frame(unclass(principal(lipset[[1]],