The SPSS 22.0 for Windows statistical software (SPSS Inc., Chicago, IL, USA) was used to perform the statistical analysis. The patients were divided into two groups according to ADS score. Continuous variables were expressed as the means ± standard deviation. The categorical variables were expressed as a percentage. One-way ANOVA was used to evaluate differences between normally distributed numerical variables, and non-normally distributed numerical variables were analyzed using the Mann–Whitney U-test. The Chi-squared test was used to compare the categorical variables. Kaplan–Meier analysis was utilized to analyze the cumulative incidence of long-term prognosis. The log-rank test was used to compare between groups. A multivariate Cox model was used to adjust the potential confounders. P < 0.05 was considered statistically significant.
Spss 22.0 for windows statistical software
Manufactured by IBM
Sourced in United States
SPSS 22.0 for Windows is a statistical software package that provides advanced analytical capabilities. It offers tools for data management, analysis, and reporting. The software is designed to help users explore data, model relationships, and generate insights from their information.
Automatically generated - may contain errors
Lab products found in correlation
11 protocols using spss 22.0 for windows statistical software
1
Evaluating Long-term Prognosis in ADS Patients
2
Analysis of Continuous and Categorical Variables
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All analyses were performed using SPSS 22.0 for Windows statistical software (SPSS Inc). Continuous variables are expressed as mean ± standard deviation or median (25th to 75th percentiles), while categorical variables are presented as frequencies (percentages). Between‐group differences with respect to normally distributed continuous variables were evaluated using one‐way ANOVA; those with respect to non‐normally distributed variables were assessed using the Mann–Whitney U test or Kruskal–Wallis variance analysis as appropriate. The chi‐squared (χ2) test was employed for the comparison of categorical variables. To construct the model for multivariate regression analyses, univariate models for each of the predictor variables were run, and variables that showed a significant association in univariate analysis were included in the multivariate logistic analysis p < .05 were considered indicative of statistical significance.
3
Prognostic Factors for Clinical Outcomes
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All analyses were performed using SPSS 22.0 for Windows statistical software (SPSS Inc., Chicago, IL, USA).The normality of the distribution of continuous variables was evaluated by the Kolmogorov-Smirnov test. Continuous variables were expressed as Mean ± standard deviation. Parametric patient characteristics were compared using one-way ANOVA, whereas non-parametric characteristics were compared using the Kruskal–Wallis test. Categorical variables were summarised as percentages and compared using the Chi-square (x2) test. Stepwise regression was used to deal with the collinear problem. Multivariate Cox proportional hazard model were used for determination of independent parameters for MACE and ACM. To construct the Cox model, univariate models for each of the all predictor variables were run, with those variables that were significant (P < 0.05) in univariate Cox models were then simultaneously entered into a multivariable Cox model. The Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. The cumulative survival curve for MACE and ACM was constructed using the Kaplan-Meier method and compared using the log-rank test. P < 0.05 was considered significant. Receiver operating characteristic (ROC) curve was performed to discuss the diagnostic value of risk factors for the prediction of poor prognisis.
4
Predictive Value of MELD in Outcomes
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All analyses were performed using the SPSS 22.0 for Windows statistical software (SPSS Inc, Chicago, Illinois, United States). Continuous data were presented as the mean and standard deviation (SD) or median (interquartile range, IQR) according to the results of the normal test. Categorical data were expressed as the frequencies and percentages (%). The differences between normally distributed numeric variables were analyzed by ANOVA, while nonnormally distributed variables were analyzed by the Mann–Whitney U test. The chi-square test was employed for the comparison of categorical variables. Kaplan–Meier analysis was used for cumulative incidence rates of long-term outcomes, and the log-rank test was used to compare between groups. Multivariable Cox regression analysis was performed to assess the predictive value of the MELD for outcomes during and up to a 10-year follow-up. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. p value < 0.05 was considered significant.
5
Predictive Value of Dynamic Fluid Responsiveness
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All analyses were performed using the SPSS 22.0 for Windows statistical software (SPSS Inc, Chicago, Illinois, United States). Continuous data are presented as the mean ± standard deviation. Categorical data are presented as frequencies and percentages. Patients were divided into 2 groups according to the DFR level (< 0.52, and ≥ 0.52). The differences between normally distributed numeric variables were analyzed by a t-test, while non-normally distributed variables were analyzed by the Mann–Whitney U-test or Kruskal–Wallis variance analysis as appropriate. Chi-square test was employed for the comparison of categorical variables. Kaplan–Meier analysis was used for cumulative incidence rates of long-term outcomes and the log-rank test was used to compare between groups. Multivariable analysis was carried out to assess the predictive value of the DFR for outcomes during and after a 7-year follow-up. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. P-value of < 0.05 was considered significant.
6
Behavioral Analysis Using Observer XT-9.0
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Frequencies of the behaviours (rate/minute) calculated by the Observer XT-9.0 system [20 ] were used for statistical analysis. Repeated Analysis of Variances (ANOVAs) were conducted using SPSS 22.0 for Windows statistical software (SPSS, Inc., Chicago, IL), and a p < .05 was accepted as significant throughout. When Mauchley’s tests indicated a violation of the assumption of sphericity, degrees of freedom were corrected using Greenhouse-Geisser sphericity estimates. Post-hoc comparisons have been carried out using Bonferroni correction.
7
Prognostic Factors in Long-term Outcomes
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All analyses were performed using SPSS 22.0 for Windows statistical software (SPSS Inc., Chicago, IL, USA). For the subsequent analyses, we divided patients into three groups according to WAR value. Continuous variables are expressed as the means ± standard deviation or medians (25 to 75%), and categorical variables are expressed as a percentage. One-way ANOVA was used to evaluate differences between normally distributed numerical variables, and nonnormally distributed numerical variables were analyzed using the Mann-Whitney U test. The chi-squared test was used to compare categorical variables, and the cumulative incidence of long-term prognosis was analyzed by using Kaplan-Meier analysis. The log-rank test was used to compare groups. To establish the COX model, a univariate model analysis was performed for all predictors, and a significant (P < 0.05) variable in the univariate analysis was included in the multivariate Cox model. P < 0.05 was considered statistically significant.
8
Prognostic Value of dNLR in Patients
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The SPSS 22.0 for windows statistical software (SPSS Inc., Chicago, IL, USA) was used to analyze the data. The continuous data were presented as mean ± standard deviation (mean ± SD). The t-test was utilized to analyze the differences between normally distributed numeric variables, while the Mann–Whitney U-test was used to analyze the difference between non-normally distributed variables. The categorical data were presented as frequencies and percentages. Chi-square (χ2) test was employed for the comparison of categorical variables. The patients were divided into three groups according to the dNLR tertiles: the first tertile (dNLR < 1.36; n = 1,139), second tertile (1.36 ≥ dNLR < 1.96; n = 1,166), and third tertile dNLR ≥ 1.96; n = 1,157). We utilized the Kaplan–Meier analysis to analyze the cumulative incidence of long-term outcomes among three groups. The log-rank test was used to compare the difference between each group. To adjust the confounders, we used the multivariable Cox regression analysis to evaluate the predictive value of dNLR and to calculate the hazard ratios (HRs) and its 95% confidence intervals (CIs). Two-side p < 0.05 was considered significant.
9
Comparative Analysis of K-line Groups
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Statistical analyses were performed using the SPSS statistical software 22.0 for Windows (SPSS, Chicago, IL). All parametric data are presented as mean ± standard deviation. A P value < 0.05 was considered statistically significant. Student’s t test for continuous variables, or the chi-squared test for dichotomous variables, was used to determine the significance of differences in perioperative parameters between patients in the K-line (+) and K-line (-) groups.
10
Antibacterial Activity of E. faecalis
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Statistical analyses were performed by using SPSS statistical software 22.0 for Windows. Descriptive analysis was used with media and standard deviation to quantitative variables The effect of antibacterial activity against E. faecalis and the halo inhibition diameter was quantified using the Student’s t test. Significance was set at p < 0.05.
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!