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Spss

Manufactured by IBM
Sourced in United States

SPSS is a software package used for statistical analysis. It provides tools for data management, analysis, and visualization. SPSS is designed to handle a variety of data types and offers a range of statistical techniques, including regression analysis, hypothesis testing, and multivariate techniques.

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8 protocols using spss

1

Quantifying Brain Vasculature and Iron Content

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Manually quantified counts from the microscope were plotted into patients’ individual scans with Adobe Photoshop
TM. In the next step these results were manually transposed from the individual scans to an average brain (
Supplementary Fig. 1). These average brain data were then quantified with ImageJ at a resolution of 10 000 pixels/image and imported into IBM SPSS
TM. The raw results were then corrected for the area that the regions of interest covered on each individual patient’s Klüver-Pas scan, to control for variation of section level within the mid-thalamus and interindividual variation. Venous density was determined in a 7 T MRI venous atlas of the normal human brain (
Fig. 1G) (
Grabner
et al., 2014
), based on venous-sensitive susceptibility weighted imaging. A corridor of ∼1 cm adjacent to border zones of the anterior-, medial-, posterior- cerebral and anterior choroidal arterial territory was considered as watershed area (
Fig. 1I) (
van der Zwan and Hillen, 1991 (link)
). Iron content in different brain regions was depicted by Turnbull staining (
Fig. 1H) (
Hametner
et al., 2013
). Structures in the fissura longitudinalis cerebri, in the sulcus lateralis and individual sulci were considered as areas with low CSF flow (
Fig. 1I).
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2

Statistical Analysis of Continuous Variables

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All continuous variables were presented as the mean standard ± error of the mean unless otherwise specified. The normality of the distribution was confirmed according to the Kolmogorov–Smirnov and Shapiro–Wilk tests, when indicated. Comparison between groups were performed using Student’s t-test, while the differences among ≥3 groups were analyzed by one-way analysis of variance for post hoc multiple comparisons. Statistical analyses were performed using SPSSTM (IBM Corp. (North Castle, NY, USA), Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY, USA: IBM Corp.). Statistical significance was set at p < 0.05.
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3

Non-parametric Statistical Analysis

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Statistical analysis was performed with IBM SPSS
TM. Due to uneven distribution of our data, non-parametric tests were applied. Descriptive statistics included median value and range. Differences between two groups were assessed with Wilcoxon Mann Whitney U-tests. In case of multiple testing (comparison of more than two groups), significant values were corrected with the Bonferroni procedure. Interdependence of variables was evaluated by the Spearman non-parametric correlation test. The reported
P-values are results of two-sided tests. A
P-value ≤ 0
.05 was considered statistically significant.
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4

Comparative Analysis of Implant Materials

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Non-parametric analysis and multiple comparisons were achieved using one-way analysis of variance (ANOVA) with a repetition test followed by post hoc tests using the statistical software SPSSTM (V21.0, IBM, Bloomington, IL, USA). A comparison was performed between the two tested implants (MC® vs NB™). For indirect contact, implant extract exposed cells were also compared to control group cells (cells without any treatment). Results were reported as mean standard deviation (±SD) and statistical significances were accepted at p < 0.05 and p < 0.01.
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5

Statistical Analysis of Quantitative Data

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Statistical analysis was performed utilizing SPSS TM (IBM Statistical Package of Social Science software, USA). Shapiro_Wilk test was utilized for normality analysis. Chi square with Fischer correction was utilized for qualitative data calculation, and ANOVA, t-Student and Kruskal Wallis for quantitative data analysis. Statistical difference was considered when p value was inferior to 0.05.
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6

Triplicate Experiments with ANOVA Analysis

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All experiments were conducted in triplicate. The data were analyzed by the analysis of variance (ANOVA) procedure using SPSSTM (IBM® Version 25, Armonk, NY, USA). Tukey’s post hoc test was used to determine the significant differences in mean values with significance considered at p < 0.05.
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7

Nurses' Communication Patterns in Medical Consultations

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Qualitative data were managed by atlas TI TM and analysed through content analysis [20] to extract themes. Numerical data were analysed using IBM SPSS TM with descriptive and inferential statistics.
Descriptive statistics provided an overview of nurses' cue-responding behaviours in relation to patients' informational and psychosocial needs.
A descriptive analysis of discursive spaces was also undertaken [20] , which considers the frequency of words used by participants during consultations [6] , indicating how participants shared the available discursive space. Analysing discursive spaces is one way of understanding patients' ability to make their voices heard by telling professionals about their everyday lives within medical consultations. We included cues elicited when topics were brought up by patients and also by nurses, to provide a comprehensive account of the whole communication process.
Inferential statistics included analysis of variances (ANOVA) to compare mean differences in nurses' level of cue-responding across clinics, mean differences in the number of cues and level of cueresponding between nurse consultations of different durations, and also correlational analyses of discursive spaces between nurses, patients, and family members (p<.05 was considered statistically significant).
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8

Obesity and autoCPAP pressure in OSA

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Statistical analysis was performed using SPSS TM (version 20, IBM Corporation Ltd, USA). Normality was assessed using Shapiro-Wilk's test. Data is expressed as mean (standard deviation or SD) where normally distributed, or median (interquartile range or IQR) where non-normally distributed. Categorical variables are expressed as number (%). Differences in the 95 th centile autoCPAP pressure in those with and without OSA (defined as an AHI ≥15) were compared. The correlation between measures of obesity (BMI, neck and waist circumference) and measures of sleep severity (AHI, ODI, AI, HI and apnoea: hypopnoea ratio) were each compared with the 95 th centile autoCPAP pressure. Mann-Witney U tests and Spearman's rank correlation were used as autoCPAP pressure and sleep parameters were not normally distributed.
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