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Statistical package for social sciences program

Manufactured by IBM
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The Statistical Package for the Social Sciences (SPSS) is a software program designed for statistical analysis. It provides a comprehensive suite of tools for data management, data analysis, and reporting. SPSS is widely used in the social sciences, including fields such as psychology, sociology, and market research, to analyze and interpret data.

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22 protocols using statistical package for social sciences program

1

Quantitative Analysis of Qualitative Data

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Qualitative data obtained from the participating laboratories and from stability testing included two dependent variables, such as positive/negative, sensitive/resistant, correct/incorrect. Post capturing, qualitative data were coded and converted into a quantitative form, for example 1 for positive and 2 for negative, and analysed using Cohen’s kappa (k) statistical method. The Statistical Package for Social Sciences program (IBM, Bengaluru, India) was used to measure Cohen’s kappa. The inter-rater reliability agreement and the p-value cut-off points were calculated as: k > 0.75 and p ≤ 0.05, indicating statistical significance. The kappa score and p-value were evaluated between the researcher and the participating laboratories as well as for stability testing results.
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2

Statistical Analysis of Categorical Data

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Results were analyzed using the IBM Statistical Package for Social Sciences program (SPSS) version 21. The relationships between categorical variables were analyzed using the Chi-square test for small cell sizes (n < 5). A p value of less than 0.05 was considered significant. For continuous variables, data were expressed as median ± SD. Categorical variables were expressed as frequencies and percentages.
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3

Vascular Access and Bloodstream Infections

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Data were entered and analyzed using version 21 of the Statistical Package for Social Sciences program (IBM Corp., Armonk, NY, USA). For continuous variables, data were expressed as means ± SD or as median and interquartile ranges for variables which were not normally distributed. Categorical variables were expressed as frequencies and percentages. Comparisons between groups according to vascular access type were performed via an independent sample t-test for continuous variables that were normally distributed and Mann–Whitney test for continuous variables that were not normally distributed. For categorical variables, Chi-square test was performed to determine the relationship between the type of vascular access and history of BSI and Fisher’s exact test was performed for the rest. Level of significance was a P value ≤ 0.05.
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4

Statistical Analysis of Microbial Composition

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Statistical analysis was performed using IBM's Statistical Package for Social Sciences program (SPSS, version 22.0, Chicago, IL, USA). Differences were considered statistically significant when p < 0.05.
In order to determine equality of variance and normal distribution, the Levene and Kolmogorov-Smirnov tests, respectively, were carried out. One-way ANOVA and Bonferroni's post hoc test were performed on the results with equality of variance and normal distribution. The nonparametric Mann–Whitney U test was performed on the data that did not have equality of variance and/or normal distribution.
Bivariate Pearson correlation was used to determine whether an association exists between intestinal IgA concentration and either relative abundance, absolute abundance, or the number of detected bacterial species.
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5

Comparing Tomography Findings in Patients

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Statistical analyses were carried out using Statistical Package for Social Sciences program version 23.0 Inc. Chicago, IL, USA. All variables were categorical and descriptive statistics for categorical variables were given as numbers (n) and percentages. Statistical analysis was performed to compare typical and atypical tomography findings in ambulatory and inpatient patients. Categorical variables were compared using Pearson’s Chi-squared test or Fisher’s exact test. Significance level was considered p<0.05.
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6

Statistical Analysis of Social Data

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Statistical analysis was performed using the Statistical Package for Social Sciences program (SPSS Inc., Chicago, IL, USA, version 20 for Windows). Descriptive data were analyzed using frequency and percentage and crosstabulation, and the Chi-square test was used to identify differences between groups, with a significance level of 5% (p < 0.05).
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7

Retrospective Cohort Analysis of Patient Data

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All calculations were based on the available data and missing data were excluded from the calculations. Categorical data are presented as frequency and percentages. Continuous variables are presented as the mean ± standard deviation (SD). The data were analyzed using the Statistical Package for Social Sciences program (SPSS Inc., Chicago, IL, United States), version 23.
As no hypothesis was tested in the study, we did not perform formal sample size calculation and included patients who met the eligibility criteria during the stipulated time.
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8

Analyzing HRQoL in Haemophilia Patients

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Descriptive data analysis was performed to analyze the demographic/clinical variables and HRQoL in haemophilia patients. Of the data collected, continuous data were presented as basic statistics (number of observations, averages, and standard deviations) and categorical variables were presented as frequency and percentage (%). HRQoL was compared according to the demographic and clinical variables. The Student’s t-test and Mann–Whitney U test were used to examine differences according to the normality of distribution for the variable. For multiple comparisons, the Bonferroni correction was utilized. To assess whether the generic and disease-specific instruments agree, the Pearson’s correlation coefficients were calculated. Multiple linear regression analyses were performed to determine the clinical factors associated with HRQoL using backward elimination. All final significance levels reported were two-tailed, and statistical significance was estimated at p ≤0.05. The Statistical Package for Social Sciences program (version 20.0) was used for statistical analysis.
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9

H. pylori Infection Analysis Using SPSS

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Statistical Package for Social Sciences program (SPSS Inc., Chicago, IL, USA) version 16 was used for data entry and for analysis of the patients demographic characteristics; clinical diagnosis and findings of H. pylori infection were analyzed by simple descriptive statistics. Chi-square test was used to compare every two variables. A p value lower than 0.05 was statistically significant.
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10

Statistical Analysis in Social Sciences

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The Statistical Package for Social Sciences program (SPSS Inc., Chicago, IL, USA) was used for statistical analyses. To compare two means of unpaired data, the t-test was used. To compare 3 means of unpaired data, the data were compared using one-way analysis of variance (ANOVA) and the post hoc Tukey test (for a homogenous subset), or Dunnett’s T3 multiple-comparison test (for a non-homogenous subset). For data that were not normally distributed, nonparametric analyses (Kruskal-Wallis test) were used. A p value < 0.05 was considered statistically significant. All of the data are expressed as the means ± standard deviations (SD), except the median (range) for Tmax.
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