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Spss software for windows v 22

Manufactured by IBM
Sourced in United States

SPSS software for Windows V.22 is a statistical analysis and data management software. It provides tools for data access, data management, and statistical analysis. The core function of SPSS is to enable users to analyze data and present the results in a variety of formats.

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5 protocols using spss software for windows v 22

1

Descriptive Statistics and Subgroup Comparisons

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Descriptive statistics were computed for all variables. The findings are reported with medians and quartiles to describe ordinal data (deviated from normal distribution, except age) and frequencies and percentages to describe group proportions. HY stage IV (n = 56) and stage V (n = 6) were merged due to reasons of distribution. Non-parametric tests (the Kruskal-Wallis test and/or Mann-Whitney U-test for ordinal variables) or the Chi-Square test for dichotomous or categorical variables were used for sub-group comparisons. Initially, the Kruskal-Wallis or the Chi-Square tests were used for comparisons of more than two sub-groups. If the p-value then was statistical significant, subsequent tests (Mann-Whitney tests or additional Chi-Square tests) were corrected for multiple comparisons, using the Bonferroni Correction.
All p-values reported are based on two-tailed comparisons where applicable; the alpha level of significance was set at 0.05; p-values were presented exactly except when below 0.001. All statistical analyses were computed by using SPSS v. 22 software for Windows (IBM Corporation, Armonk, NY, United States).
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2

Clinically Significant Pain Prevalence

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The total patient material is presented by numbers and fractions (%). Correlations were analyzed with Pearson correlation, testing the primary outcomes and average pain (NRS) last week before examination, against relevant variables. The patients were further categorized into two groups depending upon whether they have had clinically significant pain, i. e. average pain NRS score last week of more than three (21, 22, 46) . For further study of patients with clinical significant pain versus those without, Mann-Whitney tests were used for comparisons, and for dichotomous variables Chi-square tests were performed. A p-value of <0.05 was used as level of statistical significance.
All analyses were conducted using SPSS v.22 software for Windows (IBM Corporation, Amonk, NY, USA)
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3

Breech Presentation and Adverse Outcomes

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IBM SPSS software for Windows V.22 was used for data analyses. Differences in proportions between groups were analysed using the χ2 test and prevalence rates with 95% CIs were calculated according to Newcombe and Altman.27 In the estimates of the prevalence of NNM, stillbirths were excluded and in the estimates of the prevalence of CP, stillbirths and children with postneonatal CP were excluded. We used logistic regression to estimate ORs with 95% CIs for adverse outcome of children in breech position at birth, using cephalic presentation as the reference. Moreover, we explored the roles of potential confounders including maternal age, parity, gestational age, child sex and SGA status in multivariable logistic regression analyses based on a priori knowledge and directed acyclic graphs methodology.28 (link)
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4

Comparative Analysis of Intervention Outcomes

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SPSS software for Windows v.22 (IBM Corp., Chicago, IL, USA) was used for data analysis [35 ]. Qualitative variables were presented as frequency and percentage and quantitative variables were calculated as mean and standard deviation. Considering the normal distribution of change variables according to Shapiro-Wilk normality tests, parametric paired t-test was used to compare the changes in each variable within one group in different follow ups. Chi-square test was also used to compare qualitative variables between the two groups. In order to control for the effects of age when comparing the change variables between the two groups, ANCOVA test was run. A p value of less than 0.05 was considered as statistically significant in all analyses.
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5

Epidemiological and Clinical Characteristics Comparison

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The data were compiled into a Microsoft Excel® table (Microsoft Corporation, Santa Rosa, USA).
Statistical analyses were performed with SPSS® software for Windows v.22 (IBM, Chicago, USA).
Most of the variables collected were qualitative. Pre, per and post-operative epidemiological and clinical characteristics were compared with a chi-square test when enrolment permitted, or by Fisher’s exact test. The quantitative variables were compared by a Mann-Whitney U test. Multivariate analyses were performed by binary logistic regression. The criteria of inclusion of variables from the univariate analysis for the multivariate analysis was their statistical significance in the univariate analysis.
Some quantitative variables were treated in subcategories (albumin, BMI, age, hemoglobin) and analyzed as qualitative variables. A value of p <0.05 was considered significant.
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