Exact(2)
To test for differences between groups in the spatial distribution of submovements and of the velocity profile symmetry index we used a mixed factor general linear model with participants as random factor.
For experiment 3 examining the specificity of CP 94,253 effects during maintenance of cocaine self-administration, a mixed factor ANOVA was used with 5-HT1B receptor ligand type (i.e., SB 224289, CP 94,253, or SB 224289 + CP 94,253) as the between-subjects factor and dose (i.e., vehicle or drug) as the repeated measure.
Similar(58)
These data were analyzed by using a mixed-factor ANOVA with between-subject factor of Trait (attractiveness/trustworthiness/competence) and within-subject factors of Selection Type (self/other) and Context (Facebook/dating/professional).
Data analysis will include a 2 (condition)×2 (time) mixed factor analysis of variance (ANOVA) that follows intent-to-treat principles, as well as an examination of effect sizes.
> -wrap-foot> Varees are presented as mean ± SD p values less than 0.05 are in italics * ANOVA with mixed factor with a p value cut-off of 0.05 The mean frequency of drinking acts was also significantly lower with the paper record than with the online version of the 7-day food record (Table 1).
This study used a 3 × 3 × 2 mixed factor design to determine the effects of two forms of irrelevant speech and individual differences on performance of a real-world verbal task and mental workload.
The proposed data analysis will be a 2 (FlexToBa vs Healthy Aging condition)×2 (time) mixed factor analysis of variance (ANOVA) that follows intent-to-treat principles.
Hence, it can be inferred that PC1 is controlled by mixed factor (lithogenic and anthropogenic).
The sampling locations group in C1 are influenced by lithogenic factor, whereas C2 by mixed factor, respectively, for both seasons.
Performance accuracy and reaction time were analyzed for both training blocks and test blocks, using repeated measures mixed factor analyses of variance (ANOVA).
A mixed two-factor design was used in which the first factor, external representation (tangible model/image), was a between-groups factor, while the second, time (pretest/posttest), was a within-groups factor.
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