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Spss statistical package version 22

Manufactured by IBM
Sourced in United States

SPSS Statistics is a software package used for statistical analysis. Version 22.0 provides data management and analysis capabilities, including the ability to perform a variety of statistical procedures. The software is designed to work with a wide range of data types and can be used for tasks such as data exploration, modeling, and reporting.

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99 protocols using spss statistical package version 22

1

Statistical Analysis of Experimental Results

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The statistical analysis was performed by the SPSS statistical package, version 22.0 (SPSS, Inc.). To compare the results among tested groups, we applied the unpaired samples t-test, one-way analysis of variance (ANOVA), and Dunnett's test. P < 0.05 was measured statistically significant.
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2

Statistical Analysis of Experimental Data

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All of the experiments were carried out in triplicate. The SPSS statistical package, version 22.0 (SPSS, Inc., Chicago, IL, USA), was applied for data analysis. Here, the alterations in the test and control groups were examined by a t-test. Furthermore, p < 0.05 was considered statistically significant.
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3

Statistical Analysis of Research Data

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All statistical analyses were performed using the SPSS® statistical package, version 22.0 (SPSS Inc., Chicago, IL, USA) for Windows®. Repeated measures analysis of variance was used to analyse data collected in the study. Details of the methods of data analysis are the same as in previous studies.22 (link),29 A P-value ≤ 0.05 was considered statistically significant.
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4

Multivariate Analysis of Cardiac Procedures

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Statistical analysis was performed with the SPSS statistical package version 22.0 (SPSS Inc., Chicago, IL, USA). Categorical data were expressed as frequency distributions and single percentages and were compared between groups using Fisher's exact test if the expected frequency was <5 or the chi-square test. Normally distributed continuous variables were expressed as the mean ± standard deviation and were compared between groups using an independent-samples t test; non-normally distributed continuous variables were expressed as median and interquartile range (IQR) and were compared between groups with the Wilcoxon rank sum test. Baseline characteristics (including demographics, concomitant diseases, preoperative cardiac status, and echocardiographic data) with p < 0.2 obtained through the univariate analysis were then entered into forward stepwise multivariate logistic regression analysis (the combined group or the alone group as independent variables and baseline variables as dependent variables) to test the independent association between grouping (concomitant mitral subvalvular procedures vs. myectomy alone) and baseline characteristics. A two-sided p-value less than 0.05 was considered statistically significant.
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5

Statistical Analysis of Heterogeneous Samples

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All statistical analyses were performed using the SPSS® statistical package, version 22.0 (SPSS Inc., Amrok, NY, USA) for Windows®. The Shapiro–Wilk test was used to evaluate the distribution of the variables. Categorical variables are presented as frequencies and percentages. Normally distributed continuous variables are expressed as mean ± SD, whereas skewed distributed continuous variables are expressed as median ± SE. In the analysis of statistical significance, an independent-sample Student’s t-test was implemented for normally distributed variables, and the Mann–Whitney U-test was performed for variables that were not normally distributed. The χ2-test, where appropriate, was used to compare the proportions in different groups. For the multivariate analysis, the variables that had P-values < 0.1 on univariate logistic regression analysis were further evaluated in multivariate logistic regression analysis to determine independent predictors of HS. A P-value < 0.05 was considered statistically significant unless otherwise stated.
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6

Gastric Cancer Prognosis Analysis

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Clinicopathological characteristics were compared using the χ2 test for categorical variables and the Mann–Whitney U test for continuous variables. For univariate analyses, the Kaplan–Meier estimator was used with the log-rank test. Recurrence-free interval (RFI) was measured from the date of surgery to the date of recurrence or death as a result of gastric cancer and was censored at the last follow-up or non-gastric-cancer-related death. Hazard ratios (HR) were estimated by univariate Cox proportional hazards regression models. In the multivariate analysis, a Cox proportional hazards regression model was fitted. All P values <0.05 were judged as statistically significant. Variables with P < 0.05 in univariate analysis were assessed in multivariate analysis. Statistical analyses were performed using the SPSS statistical package, version 22.0 (SPSS, Chicago, IL, USA).
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7

Statistical Analysis of Quantitative and Qualitative Data

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The statistical analyses were performed with SPSS® statistical package, version 22.0 (SPSS Inc., Chicago, IL, USA) for Windows®. Qualitative variables were expressed as numbers or percentages. Continuous variables were expressed as mean  ±  SD. Normal distribution was tested by using the Skewness-Kurtosis test. Mann–Whitney U test was used to evaluate the differences of continuous variables between two groups. Z-test was used to compare the frequency between groups. Kruskall–Wallis test was used for multiple comparisons. P value  <  0.05 was considered statistically significant.
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8

Analysis of Drug-Drug Interaction

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All statistical analyses were performed using the SPSS® statistical package, version 22.0 (SPSS Inc., Chicago, IL, USA) for Windows®. Bivariate analysis, Mann–Whitney U-test or log-rank test were used to examine the time-to-events due to a drug–drug interaction between S-1 and WF. Fisher’s exact probability test was used for categorical variables. A P-value < 0.05 was considered statistically significant.
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9

Cartilage Biomarkers in Osteoarthritis

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All statistical analyses were performed using the SPSS® statistical package,
version 22.0 (SPSS Inc., Chicago, IL, USA) for Windows®. Quantitative data are
expressed as mean ± SD. Serum CTX-II and ColX levels and MRI tibial plateau
cartilage volumes in the OA group were compared with those of the control group
using an independent sample t-test (2-detailed,
95% confidence interval). Using Shapiro–Wilk for normality testing, P > 0.1 was considered to indicate that the data
were normally distributed. A P ≤ 0.05was
considered statistically significant.
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10

Statistical Analysis of Experimental Results

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To analyze the results, we used the SPSS statistical package, version 22.0 (SPSS, Inc.). To compare the results among tested groups, we applied the unpaired samples t-test and one-way analysis of variance (ANOVA), and Dunnett's test. p < 0.05 was considered statistically significant.
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