compute_factor_array: Factor arrays on the forced Q-sort distribution
In bayesqm: Bayesian Q Methodology: Probabilistic Factor Analysis
compute_factor_array R Documentation
Factor arrays on the forced Q-sort distribution
Description
Posterior-mean factor z-scores ranked onto the study's forced
distribution. The result is a tidy data frame with one row per
statement and per-factor integer grid scores. For the continuous
z-scores with credible intervals, use compute_zscores().
Usage
compute_factor_array(F_draws, Y)
Arguments
F_draws
Array of shape [T, J, K] of factor-score draws.
Y
The Q-sort matrix whose first column supplies the forced
distribution (as in the original study's grid).
Value
A data frame with columns statement and f1_grid, f2_grid, ..., fK_grid.
bayesqm documentation built on June 18, 2026, 1:07 a.m.
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| compute_factor_array | R Documentation |
Factor arrays on the forced Q-sort distribution
Description
Posterior-mean factor z-scores ranked onto the study's forced
distribution. The result is a tidy data frame with one row per
statement and per-factor integer grid scores. For the continuous
z-scores with credible intervals, use compute_zscores().
Usage
compute_factor_array(F_draws, Y)
Arguments
F_draws |
Array of shape |
Y |
The Q-sort matrix whose first column supplies the forced distribution (as in the original study's grid). |
Value
A data frame with columns statement and f1_grid, f2_grid, ..., fK_grid.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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