In this lesson, students will learn the necessary statistical terms to understand two-way ANOVA, how to visualize their data, how to perform two-way ANOVA and interpret their results, and how to check for the ANOVA assumptions.
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This dataset contains the data used in the paper: "The Impact of Altitude Training on NCAA Division I Female Swimmers’ Performance" being submitted to the International Journal of Performance Analysis in Sport.
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Two way ANOVA hypothesis reject TRUE/FALSE among 11 datasets related to ten patterns respectively
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For quantitative real time PCR data, the effect of treatment (CTR versus LES), the effect of ErbB2 over-expression (BALB/c versus BALB-neuT) and the interaction between the two factors (treatment and ErbB2 over-expression) were analyzed by two-way ANOVA test. Analysis of all ErbBs showed highly significant main effects of treatment (CTR versus LES) while the effect of ErbB2 over-expression (BALB/c versus BALB-neuT) and the interaction between the two factors (treatment and ErbB2 over-expression) was not significant. Analysis of NRG1 showed highly significant main effects of treatment (CTR versus LES) for all NRG1 isoforms analyzed; the effect of ErbB2 over-expression (BALB/c versus BALB-neuT) and the interaction between the two factors (treatment and ErbB2 over-expression) were highly significant only for NRG1 alpha, beta, type I/II. (df = degrees of freedom, E = error, P = P-value).
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Two-way ANOVA comparing biofouled/virgin and surface water/effluent.
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Results of the effect of tide (spring and neap) and region (mixed, frontal, and stratified) on the size and abundance of phytoplankton chains. Asterisks indicate significant effects (*P
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Table A.1 to A.11 has shown the Two way ANOVA statistic and pvalue of 11 datasets for ten patterns.
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Two-way ANOVA analysis with Bonferroni's post hoc correction was used to analyze data in figures 1, 3 and 5. Results of the overall analysis are presented; post hoc analysis p values are given in the text and figures. Statistics were done with GraphPad Prism 5.0.
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All d.f. = 1.
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SNK tests:Algal species: C. elongata > (C. amentacea = D. dichotoma) (p 1000 µatm (p
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Swimming behaviors of four species of cnidarian hydromedusae (Aequorea victoria, Mitrocoma cellularia, Stomotoca atra, Aglantha digitale) exposed to two flow conditions in a laboratory turbulence generator - still water and turbulent (ε ~10-7 m2 s-3) were examined.
A two-way ANOVA was used to test for significant effects of species, flow level (still and turbulent) and their interaction on swimming behavior parameters, including depth in the tank, observed speed, acceleration, NGDR, and time spent swimming. Raw data that did not meet the assumption of normality were square root transformed. Proportion data (NGDR, and time spent swimming) that did not meet the assumption of normality were arcsine square root transformed, which is appropriate for proportion data (Zar, 1999).
Related Datasets:
HydroSwimParams_N
HydroSwimParams_IndStats
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Figure 1. Chemical structures of tacrine (a) and its derivatives created by introducing substituents on the aromatic core and/or altering the size of the cycloalkyl moiety attached to the aromatic region: 7-MEOTA (b), K1578 (7-chloro-1H,2H,3H-cyclopenta[b]quinolin-9-amine; c), K1592 (1-chloro-6H,7H,8H,9H,10H-cyclohepta[b]quinolin-11-amine; d), K1594 (6-methyl-1,2,3,4-tetrahydroacridin-9-amine; e), and K1599 (7-methoxy-1H,2H,3H-cyclopenta[b]quinolin-9-amine; f). Compounds in this study were used in the form of hydrochloride salts.
Figure_2_values. Test results. Morris water maze: scopolamine-induced model of cognitive deficit in the acquisition and reversal phases. The graphs show the effects of K1578 (a), K1592 (b), K1594 (c), and K1599 (d) on escape latency during the acquisition phase, where none of the compounds ameliorated the deficit of spatial learning. The remaining graphs display the effects of K1578 (e), K1592 (f), K1594 (g), and K1599 (h) in the reversal phase, where K1578 (1 mg/kg) and K1599 (at both doses), and marginally K1592 (1 mg/kg; see in the text), mitigated the scopolamine-induced deficit of reversal learning. VEH – vehicle, the numbers in brackets denote the dose applied (mg/kg). Data are presented as the mean + SEM, * vs. VEH, * p < 0.05, ** p < 0.01, *** p < 0.001. n = 6–9 animals per group. Statistical significance was determined using two-way repeated measures ANOVA (a–d) or ANOVA (e, f, h) followed by Dunnett’s multiple comparisons tests.
Figure-3_values. Test results. Morris water maze: MK-801-induced model of cognitive deficit in the acquisition phase. The graphs illustrate the effects of the compounds K1578 (a), K1592 (b), K1594 (c), and K1599 (d) on escape latency. Only K1599 (1 mg/kg) ameliorated the MK-801-induced deficit of spatial learning. VEH – vehicle, the numbers in brackets denote the dose (mg/kg). Data are presented as the mean + SEM, * vs. VEH, * p < 0.05, ** p < 0.01. n = 5–7 animals per group. Statistical significance was determined using two-way repeated measures ANOVA followed by Dunnett’s multiple comparisons tests.
Figure_4_values. Open field test. The results demonstrate the effects of K1578 (a), K1592 (b), K1594 (c), and K1599 (d) on the distance moved by intact and MK-801-treated animals. VEH – vehicle, the numbers in brackets denote the dose (mg/kg). Data are presented as the mean + SEM, * vs. VEH group of the corresponding phenotype, * p < 0.05, ** p < 0.01, **** p < 0.0001. n = 6–14 animals per group. A significant effect of both factors (treatment and phenotype) was determined using two-way ANOVA, followed by Dunnett’s multiple comparisons tests.
Figure-5_values. Acetylcholinesterase activity. The results document the effect of the compounds (1 mg/kg ip) on AChE activity in the hippocampus (a), prefrontal cortex (b), striatum (c), and whole brain sample (d). K1578 and K1599 decreased AChE activity in the striatum. VEH – vehicle. Data are presented as the median with minimum to maximum range, * vs. VEH, *** p < 0.001, **** p < 0.0001. VEH samples AChE enzyme activities reached the following absolute values (a) 15.19 ± 3.09 U/mg protein, (b) 9.810 ± 1.54 U/mg protein, (c) 26.05 ± 3.27 U/mg protein, and (d) 27.38 ± 3.36 U/mg protein. Significance was determined by ANOVA (graphs c, d), followed by Dunnett’s multiple comparisons tests.
Figure_6_values. Electrophysiology: Inhibition of GluN1/GluN2A receptors by K1599. Representative whole-cell patch-clamp recordings measured from HEK293 cells expressing the GluN1/GluN2A receptors held at a membrane voltage of −80 mV and +60 mV; 30 μM K1599 was applied as indicated. Results summarizing the relative inhibition induced by 30 µM K1599, measured at the indicated membrane potentials. n ≥ 5 cells per each condition.
Table_1. The rats were pseudo-randomly assigned to one of the 18 treatment groups listed in. Each group received two injections: one containing the study compound and another containing either MK-801 or scopolamine, as indicated by the group name. The vehicle group (VEH) received the DMSO vehicle (2.5 mL/kg) and saline. The “scopolamine” and “MK-801” groups received scopolamine or MK-801, respectively, along with the DMSO vehicle (2.5 mL/kg).
Table 2. Treatment groups and n in biochemical experiments - AChE activity assay.
This dataset examines the complexity of network structures in professional and collegiate women’s soccer teams using directed network analysis based on tri-axial acceleration data. The study involved one professional team and one university-level team, with data collected from matches during their respective seasons. Directed network analysis identified dyads and triads, representing cooperative interactions among players, while movement entropy quantified the influence of individual movements within the team. Network diversity, defined as the variability in activation probabilities of dyads and triads, was calculated to evaluate the tactical dynamics and cooperative behaviors of the teams. Data were collected using GNSS devices equipped with tri-axial accelerometers, ensuring precise measurement of movement intensity. The findings provide insights into the structural and functional differences in team coordination between professional and collegiate levels. The dataset is anonymized an..., Participants Prior to participant recruitment, we calculated the minimum required number of matches using G*Power 3.1.9.4 (Heinrich Heine Universität Düsseldorf, Germany). This study employs a two-way analysis of variance (ANOVA) to primarily examine the interaction effects between the period of the match (the first half and second half of the match) and three team groups (professional teams during the first half of the season, professional teams during the second half of the season, and collegiate teams). Thus, the calculation for the F-test with ANOVA was conducted a priori, given an effect size of 0.40, an α error probability of 0.05, a power of 0.80, and a numerator df of 2 with six groups. The effect size (0.40) for this analysis was set based on findings from a previous study that examined changes in team coordination states during matches and reported a large effect size (η² = 0.240 to 0.263) for differences influenced by the level of the opposing team. The total required sample ..., , # Accelerometer-based network analysis in female soccer: performance levels and injuries
https://doi.org/10.5061/dryad.sf7m0cgh6
This dataset investigates the complexity of network structures in professional and collegiate women’s soccer teams, focusing on cooperative interactions and tactical dynamics. Data were collected during matches using GNSS devices equipped with tri-axial accelerometers, providing precise measurements of player movements and interactions.
The dataset includes:
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A major influence was observed for the maximum velocities of flexion and extension. The degree of freedom was 2 in all cases. * indicates statistical significance at p
This record contains raw data related to article "Robotic surgery, video-assisted thoracic surgery, and open surgery for early stage lung cancer comparison of costs and outcomes at a single institute"
Background:
Robotic surgery is increasingly used to resect lung cancer. However costs are high. We compared costs and outcomes for robotic surgery, video-assisted thoracic surgery (VATS), and open surgery, to treat non-small cell lung cancer (NSCLC).
Methods:
We retrospectively assessed 103 consecutive patients given lobectomy or segmentectomy for clinical stage I or II NSCLC. Three surgeons could choose VATS or open, the fourth could choose between all three techniques. Between-group differences were assessed by Fisher's exact, two-way analysis of variance (ANOVA), and Wilcoxon-Mann-Whitney test. P values <0.05 were considered significant.
Results:
Twenty-three patients were treated by robot, 41 by VATS, and 39 by open surgery. Age, physical status, pulmonary function, comorbidities, stage, and perioperative complications did not differ between the groups. Pathological tumor size was greater in the open than VATS and robotic groups (P=0.025). Duration of surgery was 150, 191 and 116 minutes, by robotic, VATS and open approaches, respectively (P<0.001). Significantly more lymph node stations were removed (P<0.001), and median length of stay was shorter (4, 5 and 6 days, respectively; P<0.001) in the robotic than VATS and open groups. Estimated costs were 82%, 68% and 69%, respectively, of the regional health service reimbursement for robotic, VATS and open approaches.
Discussion:
Robotic surgery for early lung cancer was associated with shorter stay and more extensive lymph node dissection than VATS and open surgery. Duration of surgery was shorter for robotic than VATS. Although the cost of robotic thoracic surgery is high, the hospital makes a profit.
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All d.f. = 1.
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Two-way ANOVA results for performance (percent of targets reached by each participant in a session) and reaction time (RT).
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Two-way ANOVA statistics for total dendritic measures at 13 weeks.
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Repeated measures two-way ANOVA statistics for dendritic measures as a function of distance from the soma at 13 weeks.
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Significant levels:*p
In this lesson, students will learn the necessary statistical terms to understand two-way ANOVA, how to visualize their data, how to perform two-way ANOVA and interpret their results, and how to check for the ANOVA assumptions.