Search alternatives:
significantly predictive » significant predictive (Expand Search), significantly predicted (Expand Search), significantly positive (Expand Search)
predictive model » prediction model (Expand Search), prediction models (Expand Search)
main decrease » gain decreased (Expand Search), small decrease (Expand Search), point decrease (Expand Search)
mean decrease » a decrease (Expand Search)
significantly predictive » significant predictive (Expand Search), significantly predicted (Expand Search), significantly positive (Expand Search)
predictive model » prediction model (Expand Search), prediction models (Expand Search)
main decrease » gain decreased (Expand Search), small decrease (Expand Search), point decrease (Expand Search)
mean decrease » a decrease (Expand Search)
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Spatial information is significantly decreased in dCA1 and vCA1 in APP/PS1 mice.
Published 2024“…(B) In dCA1, spatial information was decreased in APP/PS1 mice relative to C57BL/6 controls (mean ± std: C57BL/6 = 0.132 ± 0.048, APP/PS1 = 0.128 ± 0.051, p < 0.005, two-sided Wilcoxon rank-sum test, n<sub>C57BL/6</sub> = 305 units from 5 recording sessions, n<sub>APP/PS1</sub> = 180 units from 4 recording sessions). …”
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The variables that significantly predicted litter clump weight in shelter cats.
Published 2025“…C) Fewer days in the study predicted greater urine output (p = .034). The black line represents the line of best fit based on the reduced model with marginal means. …”
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Mean values of participants’ heart rate.
Published 2023“…Additionally, a motivational decrease was observed for the high motivation group due to the interruption. …”
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Mean values of participants’ heart rate.
Published 2023“…Additionally, a motivational decrease was observed for the high motivation group due to the interruption. …”
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Cat Stress Score (CSS) was significantly predicted by intake type and days in the study.
Published 2025“…B) More days in the study predicted lower CSS (<i>p</i> < 0.001). The black line represents the line of best fit based on the reduced model with marginal means. …”
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Predicted banana distribution map (2016) using logistic regression model M2-12 fitted using 12 covariates and significant two-way combinations.
Published 2022“…<p>Predicted banana distribution map (2016) using logistic regression model M2-12 fitted using 12 covariates and significant two-way combinations.…”
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The main effects of PRGDP and Gi on SWB.
Published 2024“…Key findings include: (1) In temporal relationships, a 46.70% increase in GDP per capita implies a 0.38 increase in subjective well-being, while a 0.09 increase in the Gini coefficient means a 1.47 decrease in subjective well-being. (2) In spatial relationships, for every 46.70% increase in GDP per capita, subjective well-being rises by 0.51; however, this relationship is buffered by unfair distribution, and GDP per capita no longer significantly affects subjective well-being when the Gini index exceeds 0.609. …”
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