qbstep {qmethod} | R Documentation |
Q Methodology: Single step for the bootstrap
Description
Bootstraping of Q methodology using PCA.
Usage
qbstep(subdata, subtarget, indet,
nfactors, nqsorts, nstat,
qmts = qmts, qmts_log = qmts_log,
rotation = "unknown",
flagged = flagged, cor.method="pearson", ...)
Arguments
subdata |
resampled dataset of Q-sorts. |
subtarget |
target matrix, adapted to match the rows of the resampled dataset. |
indet |
method to solve the double indeterminacy issue when bootstrapping Principal Components Analysis (PCA). |
nfactors |
number of factors in the study. |
nqsorts |
number of Q-sorts in the study. |
nstat |
number of statements in the study. |
qmts |
data frame with two rows and at least one column. This is automatically created when this function is called from |
qmts_log |
data frame with two rows and at least one column. This is automatically created when this function is called from |
rotation |
rotation method, defaults to |
flagged |
matrix or data frame of |
cor.method |
character string indicating which correlation coefficient is to be computed, to be passed on to the function |
... |
other arguments to be passed on to |
Details
This function performs a single step within a bootstrap of Q methodology data. It takes one resample, performs the Q method analysis, checks for indeterminacy issues, and corrects them if necessary by calling the function qindtest
or qpcrustes
.
Value
step_res |
summary of the analysis. |
Note
This function is called within the function qmboots
. Not intended to be used separately.
Author(s)
Aiora Zabala
References
Zabala, Pascual (2016) Bootstrapping Q Methodology to Improve the Understanding of Human Perspectives. PLoS ONE 11(2): e0148087.
See Also
qmethod
and qmboots
in this package.