generateSingleFactorItems | R Documentation |
Imagine that there are people that play in tournaments of more than one board game. For example, the computer player AlphaZero (Silver et al. 2018) has trained to play chess, shogi, and Go. We can take the tournament match outcome data and find rankings among the players for each of these games. We may also suspect that there is a latent board game skill that accounts for some proportion of the variance in the per-board game rankings.
generateSingleFactorItems(df, prop, th = 0.5, name, ..., scale = 1, alpha = 1)
df |
a data frame with pairs of vertices given in columns |
prop |
the number of items or a vector of signed proportions of variance |
th |
a vector of thresholds |
name |
a vector of item names |
... |
Not used. Forces remaining arguments to be specified by name. |
scale |
a vector of scaling constants |
alpha |
a vector of item discriminations |
The given data.frame df
with additional columns for each item.
See cmp_probs for details.
The function generateFactorItems was renamed to
generateSingleFactorItems
(version 1.1.0) to make space for a more
flexible factor model with an arbitrary number of factors and
arbitrary factor-to-item loading pattern. If you don't need this
flexibility, you can call the old function generateSingleFactorItems.
Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., ... & Lillicrap, T. (2018). A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science, 362(6419), 1140-1144.
Other item generators:
generateCovItems()
,
generateFactorItems()
,
generateItem()
df <- twoLevelGraph(letters[1:10], 100)
df <- generateSingleFactorItems(df, 3)
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