Results from the experiment were presented as the mean±SEM. All statistical analyses were conducted using SPSS 22.0 Statistics Software for Windows (SPSS, Inc., Chicago, Illinois, United States). Means among multiple groups were compared with 1-way analysis of variance followed by Student-Newman-Keuls post hoc tests for different pair-wise comparisons. The number of animals that experienced SE and survived were calculated as percentages (percentage SE and percentage survival, respectively), and compared using a chi-square test. P<0.05 was considered statistically significant.
Spss 22.0 statistics software for windows
Manufactured by IBM
Sourced in United States
SPSS 22.0 Statistics Software for Windows is a comprehensive software package designed for statistical analysis. It provides a wide range of statistical techniques, including descriptive statistics, advanced modeling, and data management tools, to help researchers, analysts, and decision-makers gain insights from their data.
Automatically generated - may contain errors
Lab products found in correlation
4 protocols using spss 22.0 statistics software for windows
1
Statistical Analysis of Seizure Incidence
2
Seizure Activity Assessment Protocol
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The experiment results are presented as the mean ±SEM. All statistical analyses were conducted using SPSS 22.0 Statistics Software for Windows. Means of the number and accumulated time of seizure activities between SSSE and SSSE+MB was compared using the unpaired t test. Means among multiple groups were compared by one-way ANOVA followed by least significant difference (LSD) post hoc tests for different pair-wise comparisons. A difference was considered statistically significant if P<0.05.
3
Comparative Analysis of Substance Use
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All calculations were conducted using IBM SPSS Statistics 22.0 for Windows software (SPSS Inc., Chicago, IL, USA). Numerical data was analyzed using the Shapiro–Wilk test for assessing the parametric qualities of data. The differences between numeric parameters were assessed using a series of one-way ANOVAs. The significances in ANOVA test were presented as F (dfbetween, dfwithin)= F value and p value. If p value is less than <0.05 and beside this, F value is greater than 1; the statistical significance can be demonstrated more clearly. In our study, we considered to use both F and p values for more clear interpretation of results. Differences between groups were evaluated with multiple pairwise comparison tests [Tukey honest significant difference (HSD)]. Tukey’s HSD was applied for post-hoc analysis of multiple comparisons of the SCB users, opioid users and healthy volunteers. All numerical data was expressed as mean±standard deviation. The difference in categorical variables was assessed using the χ2 test. Data was assessed by a confidence interval of 95%, and a 2-tailed p<0.05 was accepted as statistically significant.
4
Statistical Analysis of Clinical Data
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Data management and analysis were performed using IBM® SPSS® Statistics 22.0 for Windows® software (IBM Corporation, New Orchard Road Armonk, New York, United States). The normality of variables was tested using the Shapiro–Wilk method for normal distributions. Continuous variables (i.e.: age, eGFR, respiratory function parameters, laboratory parameters) were expressed as average ± standard deviation; categorical variables (e.g.: absolute values, gender, genetic mutations, transplant undergone) were expressed as percentage. Some variables such as eGRF, FEV1, and creatinine were recorded into categories based on their clinical significance. The hypothesis testing was performed using univariate analysis. Using the following tests: Chi squared test (χ2), t-Student, analysis of variance (ANOVA) and Bivariate Correlation (Pearson’s r) when each test was appropriate to use; values of p < 0.05 were considered statistically significant.
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