Don't worry, be active: how to facilitate the detection of errors in immersive virtual environments.

This was confirmed by the results of the glmm analysis ( rc = 0.52, 95% CI [0.48, 0.55]) revealing an unexpected trend towards significance of the interaction between type of design error and viewing condition ( F 1, 751 = 3.90, p = 0.048, η p 2 = 0.005, 95% CI [0.000, 0.017]).

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This difference produced a marginally significant glmm estimated active vs. multi-passive error detection advantage of about (0.22 ± 0.23, z = 1.61, one-tailed p = 0.053, d = 0.34).

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4C , PE1, z = −1.45, one-tailed p = 0.073, d = 0.37; and PE3, z = −1.39, one-tailed p = 0.083, d = 0.39), all of which showed a trend towards significance concerning the active vs. passive error detection advantage.

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