Sentence examples for positioning of items from inspiring English sources

From the second we enter the door we are being manipulated, from the layout of the store to the positioning of items on shelves.

Based on a five-player game, the positioning of items is within a space enclosed by a pyramid.

Fifteen participants returned for this activity, confirming the appropriate number of clusters, the positioning of items within clusters, and refining the cluster labels.

The position of items in the bedroom means Pistorius' version cannot be true.

Similarly, the positions of items cannot be controlled in computerized adaptive tests in which item positions typically differ significantly from one examinee to another (Davey and Lee 2011; Kolen and Brennan 2014; Meyers et al. 2009).

Comparing mean person measures and the positions of items on Wright maps (Fig. 7) revealed four items related to situational factors that comprised the majority of the statistical significance calculated between the pre- and post-development BARSTL surveys.

The focus of the remainder of this section is on patterns of students' responses to the PISA tests over successive cycles with respect to the position of items in a booklet.

Memories developed for sequential spatial positions of items may, therefore, be embedded in a large-scale relational spatial memory (a mental map).

We next examined how performance on inference pairs varied as a function of the distance between the position of items on the hierarchy (i.e., symbolic distance; e.g., equal to 2 for a B vs. D trial; see Fig. 2D).

Fig. 1 The structural equation model for examining item position effects (Note (eta) = Latent trait; (lambda_{1}) to (lambda_{k}) = factor loadings; (tau_{1}) to (tau_{k}) = item thresholds; (p_{1}) = positions of item 1 on the test; (beta_{1}) = linear item position effect for item 1; (omega_{1}) = interaction term between latent trait and positions of item 1).

The SEM formulation of M4 is given as: y_{i}^ = lambda_{i} eta + beta_{i} *{text{item position}}_{i} + varepsilon_{i}, (7 where ({text{item position}}_{i}) is the position of item i across all examinees, and (beta_{i}) is the regression coefficient that represents the impact of one unit change in the position of item i on the difficulty of item i.