The largest database of trusted experimental protocols

835 protocols using spss statistics v25

1

Comparative Statistical Analysis of Gene Expression

Check if the same lab product or an alternative is used in the 5 most similar protocols
All data were analyzed by using the IBM SPSS Statistics v.25.0 program. Data were used to compare the patient and control groups via the software. Using the obtained Ct (Cycle of threshold) values, the ∆Ct values of the groups were calculated by formulating with the IBM SPSS Statistics v.25.0 program. The comparison of the groups was evaluated using the chi-square test. Pearson product-moment and Spearman-Brown rank correlations were calculated to determine the direction and the level of the relationships between independent variables. Furthermore, statistical significance values were calculated at the 95% confidence interval of the relations between the variables (p < 0.05 was accepted).
+ Open protocol
+ Expand
2

Multivariate Analysis of Rumen Microbiome and Metabolites

Check if the same lab product or an alternative is used in the 5 most similar protocols
Statistical analysis of RT-qPCR data was performed using the independent samples t-test in the IBM SPSS Statistics (V.25) software module and was statistically significant at the p < 0.05 level. In this study, the correlation analysis between rumen VFAs, rumen microbiota 16S rRNA and rumen epithelial miRNAs was performed by Spearman’s method: firstly, the monotonic relationship between the variable data was detected using the IBM SPSS Statistics (V.25) software; secondly, Spearman’s method was used to calculate the correlation coefficient; and finally, the two-tailed method was used to test the significance, correlation coefficient threshold 0.8, significance p < 0.01. The methods and results of the cold- and warm-season Tibetan sheep rumen VFAs and microbiota 16S rRNA [32 (link)] and microbiota metabolite [33 (link)] were determined and described in detail in a previous report.
+ Open protocol
+ Expand
3

Evaluating Extracellular Matrix Scores

Check if the same lab product or an alternative is used in the 5 most similar protocols
Data are reported as mean (range). Means were compared by independent sample and paired Student's t‐tests performed using IBM SPSS® statistics v25 (IBM, Portsmouth, UK). Relationships between donor parameters and EM scores were assessed by two‐tailed Pearson correlation coefficients calculated using IBM SPSS® statistics v25. Graphs were created using GraphPad Prism v8 (GraphPad, San Diego, CA, USA).
+ Open protocol
+ Expand
4

Multivariate Analysis of Incomplete Resection

Check if the same lab product or an alternative is used in the 5 most similar protocols
Continuous variables are presented as the mean with standard deviation or the median with range and were evaluated by the t-test. Categorical data are expressed as numbers and percentages, and analysis was conducted through a chi-square test. Binary Logistic regression analysis was used for multivariate analysis for factors related to incomplete resection. Statistical analysis was performed using IBM SPSS Statistics v.25.0.0 (IBM Corp, New York), and p < 0.05 (two-tail) was considered statistically significant.
+ Open protocol
+ Expand
5

Statistical Analysis of Continuous and Categorical Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
Statistical analysis was performed using IBM SPSS Statistics V. 25.0.0 (IBM Corp, New York). Continuous variables are expressed as the mean ± standard deviation (SD) or median and interquartile range, and statistical analysis was performed using a t test. Other data are expressed as numbers and percentages and were analyzed by the chi-square test. Two-tailed p values were used for all statistical tests, and P values < 0.05 were considered statistically significant.
+ Open protocol
+ Expand
6

Normality Assessment and Statistical Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols
The distribution of the data was assessed for normality with Kolmogorov-Smirnov test. Nonparametric data was presented as median, interquartile range, and analyzed with Kruskal Wallis. Chi square and linear regressions were also performed. The statistical analyses were performed with IBM SPSS Statistics V25.0.0.
The study was approved by the New York University Langone Health Institutional Review Board (IRB). Subjects were paid $0.75 for each completed survey.
+ Open protocol
+ Expand
7

Bland-Altman Analysis of Operator Variability

Check if the same lab product or an alternative is used in the 5 most similar protocols
A Bland–Altman analysis was used to evaluate the planned point and actual point by using Med-calc trial version (MEDCalc Inc, Acacialaan, Belgium), and the RM-ANOVA was used to compare the significant differences among the operators and among the attached regions by using IBM SPSS Statistics, v25.00 (IBM Corp, NewYork, USA).
+ Open protocol
+ Expand
8

Evaluation of Phantom Fabrication Accuracy

Check if the same lab product or an alternative is used in the 5 most similar protocols
A Bland–Altman analysis was used to evaluate the planned and actual points using Med-Calc ver. 19 (MedCalc Software Ltd., Acacialaan, Belgium). The fabrication accuracies of the phantom and 3DP-KSG were also analyzed using Bland–Altman analysis. The intraclass correlation coefficient (ICC) was used to compare significant differences among the operators using IBM SPSS Statistics v25.00 (IBM Corp., New York, USA). The ICC value was used to represent the level of precision at a 95% confidence interval.
+ Open protocol
+ Expand
9

Lymph Node Metastasis Predictors

Check if the same lab product or an alternative is used in the 5 most similar protocols
Continuous variables are presented as the mean with standard deviation (SD) or the median with range and were evaluated by the t-test. Categorical data are expressed as numbers and percentages, and analysis was conducted through a chi-square test. The predictors of lymph node metastasis were analysed by binary logistic regression. The Kaplan–Meier method was used to plot survival curves. Survival analyses were compared using Cox proportional hazard regression. Double-tailed p values were used for all statistical tests, and 0.05 was set as the significance threshold. Statistical analysis was performed using IBM SPSS Statistics v.25.0.0 (IBM Corp, New York). The survival curves were produced by GraphPad Prism 8.0.1 (GraphPad Software Inc., San Diego).
+ Open protocol
+ Expand
10

Factors Predicting Pursuit of Migraine Behavioral Therapy

Check if the same lab product or an alternative is used in the 5 most similar protocols
The distribution of the data was assessed for normality with Kolmogorov-Smirnov test. Ordinal variables were presented as median, interquartile range, and analyzed with t-tests for factor and covariate groups. Data not meeting parametric assumptions was presented as median, interquartile range, and analyzed with Kruskal-Wallis. Ordinal regressions were performed to determine associations for whom might be most likely to pursue behavioral therapy. We evaluated a pre-specified set of covariates for the ordinal regressions, and removed non-significant covariates until only significant covariates remained. Self-reported likelihood to pursue behavioral therapy for migraine prevention (1 = not at all likely, 5 = strongly likely) was the outcome. Predictors in the model were demographic data, headache characteristics, and method and cost of behavioral treatment for migraine. Statistical significance was defined as p < 0.05. Tests were two-tailed. The statistical analyses were performed with IBM SPSS Statistics V25.0.0.
The study was approved by the New York University Langone Health Institutional Review Board (IRB). As this was an online survey, written consent was not required. Participants were provided with an introductory screen indicating that consent was voluntary, and consent was implied by completion of the survey. Subjects were paid $0.75 for each completed survey.
+ 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!