Statistical analysis was performed by one-way ANOVA followed by Tukey post-hoc analysis using SPSS computer package (SPSS version 16).
Spss computer package
Manufactured by IBM
Sourced in United States
SPSS is a computer software package used for statistical analysis. It provides a range of statistical and data management capabilities, including data entry, data manipulation, and statistical modeling. SPSS is widely used in various industries and academic fields for data analysis and research purposes.
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Lab products found in correlation
7 protocols using spss computer package
1
One-way ANOVA with Tukey Post-hoc Analysis
2
Predictors of Emergency Visits in Asthma
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The SPSS computer package (version 16.0) was used to compute differences in demographic and clinical variables. Continuous variables were compared using the non-parametric Mann–Whitney U –test and categorical variables using the Chi square test.
All associated clinical variables were included in the Cox proportional hazard model to determine the independent predictors for the first emergency visit. The respective estimated hazard ratios (HR) with confidence intervals (CI) of 95% are reported. Differences were considered statistically significant when the p value was less than 0.05.
Cumulative emergency visit free time (Figure1 ) among asthma patients was stratified according to their smoking status and adjusted for age, gender, duration of disease, FEV1 of predicted, chronic sinusitis, and the number of co-morbidities.
All associated clinical variables were included in the Cox proportional hazard model to determine the independent predictors for the first emergency visit. The respective estimated hazard ratios (HR) with confidence intervals (CI) of 95% are reported. Differences were considered statistically significant when the p value was less than 0.05.
Cumulative emergency visit free time (Figure
3
Lung Function Analyses in Adults
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Continuous variables were presented as means ± standard deviation and analyzed among the four groups by one-way analysis of variance (ANOVA) test and post hoc analyses with the Tukey’s b method, and analysis of covariance (ANCOVA) test was performed to adjust for age and sex. Categorical variables were presented as frequencies and percentages, and analyzed using Pearson’s chi-squared test for discrete variables. Multinomial logistic regression analyses with the quartiles of FEV1 or FVC (% pred) as the dependent variable were performed after adjusting for confounding factors such as age, sex, smoking, skeletal muscle mass and body fat mass included in the model. All tests were two sided and p values < 0.05 were considered to be statistically significant. All analyses were performed with the SPSS computer package (version 18.0; SPSS Inc., Chicago, IL, USA).
4
Statistical Analysis of Experimental Data
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One-way ANOVA was performed using SPSS computer package (SPSS Inc., USA) for all sets of data. Significant differences between means were determined through LSD test. Differences were considered statistically significant when P < 0.05. All data were presented as mean ± SD.
5
Statistical Analysis of Social Sciences Data
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Data were analyzed using SPSS computer package program version 22.0 (the Statistical Package for the Social Sciences, SPSS Inc., Chicago, USA). The descriptive statistics were presented as numbers and percentages for categorical variables and as mean±Standard deviation and median (minimum-maximum values) for continuous variables. The compliance of continuous variables with normal distribution was evaluated using visual (histogram and probability graphs) and analytical (Kolmogorov–Smirnov and Shapiro–Wilk tests) methods. The continuous variables were determined not to have normal distribution. Mann–Whitney U-test was used for the pairwise comparison of non-normally distributed data. The Chi-square test was used to determine whether the subject groups were different in terms of categorical variables. In this study, p<0.05 was accepted as statistically significant.
6
Survival Analysis of Patient Outcomes
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Survival analysis was performed using Kaplan–Meier plots and the difference in survival rates compared using the log-rank test. Variables between groups were compared using the chi-square test. The SPSS computer package (version 15.0, SPSS Inc., Chicago, IL, USA) was used in all analyses. Results were considered statistically significant at P < 0.05, and a multivariate analysis by Cox regression model was performed in which P values by log-rank test were <0.1 in the univariate analysis.
7
Statistical Analysis of Experimental Data
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All the data in this study were analyzed by Microsoft Excel 2007, and, moreover, the one-way ANOVA was performed by adopting SPSS computer package (SPSS Inc., USA). Every data acquired in the experiments is the mean of three biological replications at least. Significant differences between means were determined through LSD test. Differences were considered statistically significant when P < 0.05. All data were presented as mean ± SD. In addition, the figures were all created with SigmaPlot 10.0 (Systat Software, Inc., Germany).
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