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liboscats Reference Manual | ![]() |
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Top | Description | Object Hierarchy | Properties |
struct OscatsAlgMaxFisher; void oscats_alg_max_fisher_resize (OscatsAlgMaxFisher *alg_data
,guint num
);
"A-opt" gboolean : Read / Write / Construct Only "modelKey" gchar* : Read / Write "num" guint : Read / Write / Construct Only "thetaKey" gchar* : Read / Write
struct OscatsAlgMaxFisher;
Item selection algorithm ("select"). Picks the item with optimal Fisher information. Note: This algorithm may not work correctly if there are multiple items with exactly the same optimality metric.
Fisher Information is: I_j(theta) = -E_{X|theta}[ d^2/dtheta dtheta' log P_j(x|theta) ]
D-optimal Fisher Information minimizes the confidence ellipsoid around theta.hat by maximizing the determinant of the Fisher Information: arg max_j det[ I_j(theta.hat) + sum_k I_k(theta.hat) ], where I_k are the previously administered items. This is equivalent to the traditional Maximum Information Criterion in the unidimensional case.
A-optimal Fisher Information minimizes the trace of the covariance matrix for theta: arg min_j tr{ [ I_j(theta.hat) + sum_k I_k(theta.hat) ]^-1 } This is equivalent to the D-optimal condition in the unidimensional case, but the D-optimal calculation will be slightly faster.
Note for multidimensional tests: These algorithms will not work correctly unless the test information matrix for the items already administered is full rank. If not all of the items in the item bank load onto every dimension, a different item selection mechanism may be needed until the test information achieves full rank.
References:
void oscats_alg_max_fisher_resize (OscatsAlgMaxFisher *alg_data
,guint num
);
Set the size of the continuous portion of the test's latent space. This function only needs to be called if the test switches to a set of models from a different latent space (which is not usual).
|
the OscatsAlgMaxFisher data |
|
the number of continuous dimensions of the test's latent space |
"A-opt"
property"A-opt" gboolean : Read / Write / Construct Only
If true, use the A-optimality critierion. Otherwise, use the D-optimality criterion.
Default value: FALSE
"modelKey"
property"modelKey" gchar* : Read / Write
The key indicating which model to use for selection. A NULL
value or
empty string indicates the item's default model.
Default value: NULL
"num"
property"num" guint : Read / Write / Construct Only
Number of items from which to choose. If one, then the exact optimal item is selected. If greater than one, then a random item is chosen from among the "num" optimal items.
Allowed values: >= 1
Default value: 1