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Data were analyzed using the following tests: Mann–Whitney (for non-parametric data), T-tests 1-way or 2-way ANOVA with Bonferroni correction for parametric data.
10 days later cognition and behavior were tested using the following tests: Light Dark Latency, Elevated Plus Maze, Novel Object Recognition, and Barnes Maze.
Statistical analysis was performed using the following tests: the chi-square test to verify association between variables; the Student t test to compare means; Wilcoxon, Mann–Whitney and Levene's nonparametric tests to compare scores; and the kappa coefficient to assess interrater agreement.
Physical capacity was measured using the following tests: unsupported upper limb exercise test (UULEX), endurance testing, and the 6-min walk test (6MWT).
The concentration of the aforementioned markers of bone turnover in serum was measured using colorimetric immunoenzymatic method (ELISA), using the following tests: Rat-MID Osteocalcin EIA (Immunodiagnostic Systems), Osteomark NTx Serum ELISA (Osteomark), and MicroVue Serum PYD EIA Kit (Quidel).
The items were evaluated using the following tests: 30-second chair stand (repetitions), arm curl (repetitions), chair sit-and-reach (centimeters), back scratch (centimeters), 8-ft up-and-go (seconds), and 6-minute walk (meters), always in this order.
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In this algorithm, the components which have jumps are first detected using the following test (24).
We obtained the residuals from the above regression and performed an ADF test on the residuals to estimate whether they are I(1) using the following test regression for each country: varDelta {e}_{i,t}={rho}_{it}{e}_{i,t-1}+{displaystyle sum_{j=1}{psi}}}{psi}_{i,j}varDelta {e}_{i,t-1}+{v}_{i,t}.
Finally, the overall models were compared using the following test command in Stata: test [Model1 = Model2].
We used the following tests: 1. Grip strength.
We also used the following tests for the continuous variables: one way ANOVA, Kruskal-Wallis test, t-test, or Wilcoxon test.
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