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Spss program 22

Manufactured by IBM
Sourced in United States

SPSS® program 22.0 is a comprehensive statistical software suite for data analysis, management, and presentation. It provides a wide range of analytical capabilities, including descriptive statistics, regression analysis, and advanced modeling techniques. The program is designed to handle large and complex data sets, making it a useful tool for researchers, analysts, and decision-makers across various industries.

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Lab products found in correlation

13 protocols using spss program 22

1

Analyzing AMH Levels with Statistics

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All statistical analyses were performed using SPSS program 22.0 (Chicago, Illinois, USA). Normality was tested using Kolmogorov-Smirnov test. The t test was performed for variables fitting to normal distribution, and the Mann-Whitney U test was used for variables not fitting to normal distribution. Spearman correlation test was used for the correlation of AMH levels with other variables. p values <0.05 were regarded as statistically significant.
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2

Physical Stability of Optimum ZNs Formulation

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For a period of three months, the optimum ZNs formulation was kept at 4–8 °C to test its physical stability. It was tested for visual, EE%, PS, PDI, and ZP alterations before and after storage. The gathered data were statistically examined utilizing the Student’s t-test in SPSS® program 22.0 [63 (link),64 (link)].
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3

Evaluating Optimum TNs' Physical Stability

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The optimum TNs were maintained at 4–8 °C for 45 days to examine its physical stability (Abd-Elsalam et al., 2018 (link)). Before and after storage, the optimum TNs were examined for changes in appearance, EE%, PS, PDI, and ZP. The obtained data were statistically inspected applying Student’s t-test via SPSS® program 22.0 (SPSS Inc., Chicago, IL).
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4

Statistical Analysis of Parametric and Nonparametric Data

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Mann–Whitney U test and Wilcoxon Signed Rank test were applied for nonparametric data. Student paired t test and student unpaired t test were utilized for parametric data via SPSS® program 22.0. At (p ≤ 0.05), the difference is significant.
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5

Biomarker Diagnostic Validation Protocol

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Windows SPSS program 22.0® was used to analyze the data. Non-normally distributed quantitative variables were documented as median and percentile 25–75. All data were analyzed with nonparametric tests: chi-square test for nonparametric qualitative variables and Mann–Whitney U test for quantitative variables. Biomarker cutoffs, area under the curve (AUC), sensitivity, specificity, positive and negative predicted values, and likelihood ratios were analyzed using MedCalc Program 11.3®. Differences in P-value <0.05 were considered statistically significant.
The study was carried out in accordance with the Declaration of Helsinki and was approved by the Sant Joan de Déu Ethical Assistance Committee. Before the study, written informed consent was obtained from parents.
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6

Extrusion Method for Evaluating Vesicle Elasticity

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The elasticity of both the optimum novasomes and traditional niosomal formulation was determined using the extrusion method.16 (link) The formulations were properly diluted (5 folds) before extrusion through a nylon filter of a 220 nm (Jinteng Experiment Equipment Co., Ltd, China)17 (link),18 (link) at a constant pressure of 2.5 bar (Haug Kompressoren AG; Büchi Labortechnik AG, Flawil, Switzerland). The outcomes were expressed as average value ± SD, n = 3. DI was calculated using the equation below:19 (link)
\documentclass[12pt]{minimal}
\usepackage{wasysym}
\usepackage[substack]{amsmath}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage[mathscr]{eucal}
\usepackage{mathrsfs}
\DeclareFontFamily{T1}{linotext}{}
\DeclareFontShape{T1}{linotext}{m}{n} {linotext }{}
\DeclareSymbolFont{linotext}{T1}{linotext}{m}{n}
\DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext}
\begin{document}
$${\rm{DI }} = {\rm{ J}}{\left. {\left({{\ }{{{\rm{rv}}} \over {{\rm{rp}}}}} \right.} \right)^2}$$
\end{document}
where J = weight of sample extruded in 10 min, rv = size of the vesicle after extrusion in nm, and rp = the barrier pore size in nm. Statistical analysis was computed by Student’s t-test utilizing SPSS® program 22.0 (USA). The difference at P ≤ 0.05 was considered significant.
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7

Stability Evaluation of Optimum SPs

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The optimum SPs formulation was stored for 90 days at 25°C and 4°C. Samples were taken from fresh SPs, after 45 days and after 90 days. The storage effect was evaluated by the comparison between the first and the after storage results in respect of EE%, VS, PDI and ZP.18 (link) Student’s t-test was used to analyze the results statistically using SPSS® program 22.0 (USA). A significant difference was considered at P ≤ 0.05.
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8

Analyzing Obstetric Outcomes with PROBE

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All analyses were performed using the SPSS program 22.0 (IBM Inc., Armonk, NY). Statistical significance was defined as two-sided P-values using a significance level of 5%. The t-test was used for quantitative variables with approximately normal distribution and Chi-Square tests were used when analysing the categorical variables. BMI, oxytocin stimulation, delivery method (partus normalis, vacuum extraction) and length of active labour >10h were considered as putative confounding factors and were thus included in the adjusted analysis through multiple logistic regression analyses comparing pre-PROBE to post-PROBE outcomes.
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9

Statistical Analysis of Categorical and Continuous Variables

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All statistical comparisons were made with the IBM SPSS program 22.0 (SPSS, Inc., Chicago, IL). Results are presented as frequencies and percentages. Differences between the groups in categorical variables were assessed using Pearson’s Chi-Squared test and in continuous variables with an independent samples’ t-test. P-value of 0.05 was set as the limit for statistical significance.
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10

Surgical Approach and suPAR Levels

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Sample size analysis: Assuming higher levels in open surgery compared to laparoscopic techniques and based on a prediction of an approximate 15% increase in suPAR (3.7 ng/ml to 4.2 ng/ml), 19 patients per group were calculated when the a was 0.5 with a power of 90% (G*Power 3.1). Considering a possible 5% drop-out, a minimum of 40 patients were planned to be enrolled in the study.
The SPSS 22 program was used in the analysis of the data collected within the scope of the research (SPSS, Chicago, IL, USA). Shapiro-Wilk test values were examined to determine the conformity of the data with a normal distribution. Parametric analyses were used for data with a normal distribution, and nonparametric analyses were used for data without a normal distribution. The independent samples t test and Mann-Whitney U test were used to compare quantitative (numerical) data between the groups, while χ2 analysis was used to compare qualitative (categorical) data between the groups. The Wilcoxon test was used to compare suPAR measurements of the groups before and after the operation. The Spearman test, which is a nonparametric test, was used to evaluate the correlation between CPR and suPAR within the group. P-values < 0.05 were considered statistically significant.
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