PMC:6373180 / 18550-19685 JSONTXT

{"project":"2_test","denotations":[{"id":"30411222-28345944-29867948","span":{"begin":426,"end":430},"obj":"28345944"}],"text":"We used a pre-to-post induction difference score as our measure of drift (significant change in position was observed in all six conditions, p \u003c 0.001). We first used mixed model ANOVAs to demonstrate that both groups showed a difference in spatial drift effects between hands. We then used linear contrasts to determine the nature of these spatial drift effects for each group and hand separately (Dempsey-Jones and Kritikos 2017). Linear contrasts (which fall within the framework of the ANOVA) were used because they provide a powerful tool to look for a priori effect types, e.g., as here first-order linear effects, or for higher-order effects such as quadratic or cubic functions (Abdi and Williams 2010; Seltman 2013). Particularly, here we use linear contrasts to ask whether drift is maximal near the shoulder of origin, decreasing in a linear manner with distance from this position (rather than using a battery of post hoc t tests comparing drift at each hand position separately, which runs into significant issues of multiple comparisons). All statistical analyses were run on SPSS, version 22 (IBM Corp, Armonk, NY, USA)."}

{"project":"MyTest","denotations":[{"id":"30411222-28345944-29867948","span":{"begin":426,"end":430},"obj":"28345944"}],"namespaces":[{"prefix":"_base","uri":"https://www.uniprot.org/uniprot/testbase"},{"prefix":"UniProtKB","uri":"https://www.uniprot.org/uniprot/"},{"prefix":"uniprot","uri":"https://www.uniprot.org/uniprotkb/"}],"text":"We used a pre-to-post induction difference score as our measure of drift (significant change in position was observed in all six conditions, p \u003c 0.001). We first used mixed model ANOVAs to demonstrate that both groups showed a difference in spatial drift effects between hands. We then used linear contrasts to determine the nature of these spatial drift effects for each group and hand separately (Dempsey-Jones and Kritikos 2017). Linear contrasts (which fall within the framework of the ANOVA) were used because they provide a powerful tool to look for a priori effect types, e.g., as here first-order linear effects, or for higher-order effects such as quadratic or cubic functions (Abdi and Williams 2010; Seltman 2013). Particularly, here we use linear contrasts to ask whether drift is maximal near the shoulder of origin, decreasing in a linear manner with distance from this position (rather than using a battery of post hoc t tests comparing drift at each hand position separately, which runs into significant issues of multiple comparisons). All statistical analyses were run on SPSS, version 22 (IBM Corp, Armonk, NY, USA)."}