The largest database of trusted experimental protocols

Spss 22.0 statistical analysis software

Manufactured by IBM
Sourced in United States

SPSS 22.0 is a statistical analysis software developed by IBM. It is designed to assist users in analyzing and interpreting data. The software provides a comprehensive set of tools for data management, analysis, and visualization. SPSS 22.0 is capable of handling a wide range of data types and can be used for various statistical techniques, such as regression analysis, hypothesis testing, and multivariate analysis.

Automatically generated - may contain errors

19 protocols using spss 22.0 statistical analysis software

1

Evaluating PD-L1 Expression and Survival

Check if the same lab product or an alternative is used in the 5 most similar protocols
SPSS 22.0 statistical analysis software (IBM, Armonk, NY, USA) was used to perform the analyses. Data obtained from three independent experiments were presented as the means ± standard deviation. The two-tailed Student’s t-test was performed for two-sample comparisons and one-way analysis of variance (ANOVA) was applied for the comparisons of multiple groups. The chi-squared or Fisher exact test was used to evaluate the association between PD-L1 and clinicopathological parameters. The Kaplan-Meier analysis and Log rank test were used to assess the differences of overall survival between groups with different levels of PD-L1 expression. The influence of each variable on survival was examined by the Cox-multivariate regression analysis. P<0.05 was considered to indicate a statistically significant difference.
+ Open protocol
+ Expand
2

Evaluating Construct Stiffness and Load

Check if the same lab product or an alternative is used in the 5 most similar protocols
SPSS 22.0 statistical analysis software (IBM, NY, USA) was used to perform statistical analysis of the obtained data. Statistical significance of the effect of different plates on constructs’ stiffness and load values was determined via a linear mixed model approach by taking intra- and inter-subject variability into account. In the analysis, the fixed effect was the plate type while the specimens and trials were the random effects. The dependent variables were K and F5 for elastic tests and F15a, F15b and F30 for plastic tests. Differences between each pair were tested using Fisher’s least significant difference (LSD) multiple comparison based on the least-squared means. The statistical significance was set at p < 0.05.
+ Open protocol
+ Expand
3

Statistical Analysis of Experimental Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
SPSS22.0 statistical analysis software (IBM, Armonk, NY, USA) was used to analyze the experimental data. All the assays were repeated three times, and data were presented as the mean ± standard deviation (SD). The discrepancy between two groups was compared with Student’s t‐test, and one‐way ANOVA and Dunnett posttest were used to compare the multiple groups. The relationship between gene expression and clinical features was assessed using chi‐square test. Kaplan–Meier analysis was used to plot the survival curve, and the difference between groups was measured using log‐rank test. P < 0.05 was considered statistically significant.
+ Open protocol
+ Expand
4

Comparative Analysis of Crop Cultivars

Check if the same lab product or an alternative is used in the 5 most similar protocols
Data were processed using Excel 2013 software (Microsoft Corp., Redmond, WA, USA) and figures were prepared with Origin 2021 (OriginLab, Hampton, MA, USA). The data were expressed as average values. SPSS 22.0 statistical analysis software (IBM Corp., Armonk, NY, USA) was used to perform the least significant difference test to compare cultivars at α = 0.05. Path analysis was performed using Amos 25 (IBM Corp., Armonk, NY, USA) structural equation modeling software. The experimental design diagram was drawn with Figdraw (https://www.figdraw.com/).
+ Open protocol
+ Expand
5

Survival and Brain Metastasis Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols
SPSS 22.0 statistical analysis software (IBM Corp., Armonk, NY, USA) was used to analyze all data in the present study. A χ2 test was performed to compare the patients' clinical characteristics. Measurement data and enumeration data are presented as median number and percentage (%), respectively. All statistics were calculated at least three times by two independent authors in a double-blind situation. OS and the time of BM were calculated from the date of surgery to the date of BM diagnosis or to the last day of follow-up. The Kaplan-Meier method and log-rank test were used to evaluate patient survival and the cumulative risk of developing BM. Multivariate analyses for OS and BM were performed using Cox regression, and a backward-forward stepwise method was selected. Tests were two-sided, and P<0.05 was considered to indicate a statistically significant difference.
+ Open protocol
+ Expand
6

Emotional Intelligence and Trauma Symptoms

Check if the same lab product or an alternative is used in the 5 most similar protocols
SPSS 22.0 statistical analysis software (IBM Corp, 2013) was used for data analysis. Independent samples t-tests and one-way analysis of variance (ANOVA) were used to compare STSS scores according to participants’ demographic characteristics. Pearson correlation analysis was used to assess relationships between anxiety, depression and emotional intelligence, and multiple linear regression analysis was undertaken to assess relationships between STS and factors that might influence it. P < 0.05 was considered statistically significant.
+ Open protocol
+ Expand
7

Comparison of OSEM Reconstruction Methods

Check if the same lab product or an alternative is used in the 5 most similar protocols
SPSS 22.0 statistical analysis software (IBM, Armonk, NY, USA) was used for statistical analysis, and Graphpad8.0 was used for graphing. The data were presented as mean ± SD. The SUV of OSEM_3 was served as the reference for the comparison between different reconstruction groups. Shapiro-Wilk test were used to test the normal distribution of data. Paired samples were compared using the Wilcoxon signed-rank test and paired t-test. The inter-evaluator agreement was measured by Cohen's κ. A p < 0.05 was considered significant.
+ Open protocol
+ Expand
8

Statistical Analysis of Animal Study

Check if the same lab product or an alternative is used in the 5 most similar protocols
Statistical analysis was carried out using the χ 2 with correction for continuity (Yates), Fisher's exact test was used for a small number of observations (less than 5). Statistical data processing was performed using IBM SPSS 22.0 statistical analysis software (IBM Corp., Armonk, N.Y.). The differences were considered statistically significant at p ≤ 0.05.
The use of animals in this study was approved by the Bioethics Commission of the Medical University of Karaganda (Approval No. 53, dated 03/15/2021), and the study complied with the requirements of national legislation (Ahn et al., 2021; (link)Beck et al., 2014; (link)Campbell et al., 1987; (link)Canizares et al., 2017; (link)Erdim et al., 2009; (link)Gause et al., 2014; (link)Good Laboratory Practice Standard, 2015; Kirkham et al., 2012 (link); Order of the Mi-nister…, 2020; Ozsoy et al., 2006) (link) and recommendations of the European Convention for the protection of vertebrate animals used for experiments or other scientific purposes (European Convention…, 1986).
+ Open protocol
+ Expand
9

Evaluating In-Hospital Mortality Risk

Check if the same lab product or an alternative is used in the 5 most similar protocols
Data are shown as frequencies and percentages for categorical variables and as mean ± standard deviation, or medians with 1st and 3rd quartiles. The Kruskal-Wallis test was used for data with skewed distributions. Analysis of variance for multiple groups was used to compare normally distributed continuous variables. Multiple Chi-square test was used to compare categorical data. If significant differences were found between multiple groups, post-hoc pairwise analysis utilizing the Student's T-test or the Mann-Whitney U test was used to determine which categories displayed significance. In all cases, missing data were not defaulted to negative and denominators reflect cases for which information was reported and available.
Risk adjustment was performed to determine the association of presenting SBP with in-hospital mortality using multivariable logistic regression model using a backward stepwise method, introducing variables with p<0.15 on univariate analysis. Odd ratios and 95% confidence intervals were provided to demonstrate the strength of association. All p-values were two-sided with values <0.05 considered statistically significant. Analyses were performed using SPSS 22.0 statistical analysis software (IBM Corporation).
+ Open protocol
+ Expand
10

Statistical Analysis of Quantitative Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
SPSS22.0 statistical analysis software (SPSS Inc., Chicago, IL) was used for statistical analysis. All the quantitative data were expressed by mean ± standard deviation (x ± s), and the statistical analysis of the count data was performed byχ2 test. P < .05 was considered statistically significant.
+ Open protocol
+ Expand

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

Sign up now

Revolutionizing how scientists
search and build protocols!