All data were analyzed using the SPSS software package, version 19.0 (SPSS, Chicago, IL, USA) and graphed by GraphPad Prism 5 (La Jolla, CA, USA). The results were presented as mean ± standard error based on three independent experiments. Statistical analysis was performed using correlation analysis and t test. P value < 0.05 was defined as statistically significant.
Spss software package version 19
Manufactured by IBM
Sourced in United States
SPSS software package version 19.0 is a data analysis tool that enables users to import, analyze, and present data. The software provides a wide range of statistical techniques, including regression analysis, factor analysis, and cluster analysis, to help users gain insights from their data. SPSS is widely used in various industries, including academia, market research, and healthcare.
Automatically generated - may contain errors
30 protocols using spss software package version 19
1
Statistical Analysis of Experimental Data
2
Survival Analysis of Novel Compounds
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Data are expressed as mean ± standard deviation for normally distributed variables or median and interquartile range for highly skewed variables. Statistical analyses were performed using the SPSS software package, version 19.0 (SPSS, Inc., Chicago, IL, USA).
In survival experiments, the survival rate after the 12 h observation period was conducted by the Kaplan-Meier or Kruskal-Wallis H test. Analysis of variance was used for comparison of normally distributed data. Multiple comparisons were subjected to Kruskal-Wallis H test and Bonferroni correction test. The Chi-square test was used to evaluate the equality of frequencies for discrete variables. P<0.05 was considered to indicate a statistically significant difference.
In survival experiments, the survival rate after the 12 h observation period was conducted by the Kaplan-Meier or Kruskal-Wallis H test. Analysis of variance was used for comparison of normally distributed data. Multiple comparisons were subjected to Kruskal-Wallis H test and Bonferroni correction test. The Chi-square test was used to evaluate the equality of frequencies for discrete variables. P<0.05 was considered to indicate a statistically significant difference.
3
Avian Viral Infections: Statistical Analysis
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Descriptive statistics were used to represent the variability of the positive samples as previously described [7 ], including single and multiple viral infections, type of birds (broilers and pullet/layers), age of birds (days for broilers and weeks for pullet/layers hen), and clinical signs (respiratory signs, digestive signs, stunting, and no clinical signs reported). Next, statistical analyses were performed using the SPSS software package version 19.0 (SPSS Inc., Chicago, IL, USA). Categorical variables were reported as absolute, along with the corresponding relative frequencies. Chi-squared or Fisher’s exact test was used for comparisons. The two-sided significance level alpha was set as 0.05.
4
Statistical Analysis of Experimental Data
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Parametric summary statistics were presented as means with standard deviation. Non-parametric statistics were presented as medians with interquartile ranges. Categorical data were analysed with Chi-square tests. Independent t was used to test the means using the SPSS software package version 19.0 (SPSS Inc., Chicago, Il, USA).
5
Statistical Analysis of Wip1 Expression
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SPSS software package version 19.0 was used for all statistical analyses. The chi-square test was used to evaluate the association of Wip1 expression with different clinical characteristics. Survival analysis was performed using the Kaplan–Meier method. For in vitro data, statistical analyses were performed using unpaired Student’s t tests with GraphPad Prism V8.0 software (La Jolla, CA, USA), and a p-value < 0.05 was considered statistically significant. All data analysed were from three separate experiments. The significance of the data is represented as *p < 0.05, **p < 0.01, and ***p < 0.001.
6
Adrenaline Effects on Physiological Parameters
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All analyses were performed using the SPSS software package version 19.0 (SPSS, Inc., Chicago, IL). Data are presented as the mean ± standard deviation where applicable. Paired sample t test was used for comparisons of the parameters after the administration of adrenaline at 3 time points respectively with those before administration within each subject. The test was 2-tailed and statistical significance was defined as P < .05.
7
Statistical Analysis Using SPSS
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Statistical analysis was performed with the SPSS software package version 19.0 (SPSS Inc., Chicago, IL, USA).
8
Vitamin D Status and Vertebral Fractures
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Statistical analysis was performed using the SPSS software package version 19.0 (SPSS, Chicago, IL), and the results are presented as mean ±SD (for continuous variables) or frequencies (for categorical variables). The baseline differences between males and females were compared using the χ2 test or t test, and were further adjusted for potential confounding factors using an analysis of covariance (ANCOVA) or logistic regression analysis method. The association of vitamin D status with thoracolumbar VFx in females and males, fracture numbers, fracture grades, fracture locations, and spinal deformities were analyzed by using logistic regression analysis method, and they were also further adjusted for potential confounding factors. Each vitamin D measure was standardized, and the association of quartiles of serum vitamin D with VFx was analyzed by binary logistic regression analysis in different models. Finally, a receiver operating characteristic (ROC) curve was generated and the Youden index (Sensitivity+Specificity−1) was calculated for a range of cut-off scores. The cut-off value that corresponded to the highest Youden index was the optimal cut-off value for serum vitamin D that was related with VFx. P<0.05 was considered statistically significant.
9
Evaluation of Cellular Responses
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Data are expressed by the means ± standard error. The data were evaluated using the SPSS software package, Version 19.0 (Chicago, IL). Statistical significance was performed using one-way analysis of variance (ANOVA) followed by Turkey post hoc test. p values <0.05 were considered significant.
10
Prognostic Factors in Adrenal Metastases
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Univariate and multivariate analyses (stepwise forward procedure) were performed using Cox proportional hazard analysis to identify risk factors affecting overall survival (OS) and recurrence-free survival (RFS). OS was defined as the period from ADx to the date of death from any cause. RFS was defined as the period from ADx to the date of disease progression or death, whichever occurred first. If neither event had occurred at the time of the last record, the patient was censored at that time. The factors included in the model were age, sex, ECOG PS, operative method (open or laparoscopic), intent to treat (palliation or cure), interval of primary diagnosis to adrenalectomy (synchronous vs. metachronous), site of metastasis, site of primary tumor, previous metastasectomy, C-reactive protein, serum albumin, and GPS. Among the factors, those with p < 0.25 were selected (on univariate analysis for RFS and OS) and included in the multivariate regression analysis using Cox proportional hazards regression model, which was performed to achieve adjusted hazard ratio (HR) to determine prognostic factors for recurrence free and overall survival. A two-tailed p < 0.05 was considered significant for all analyses. The SPSS software package, version 19.0 (SPSS Inc., Chicago, IL, USA) was used for statistical analysis.
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