The PLS approach in SmartPLS and moderated multiple regression analysis in SPSS version 20.0 for Windows were applied to analyze and interpret interactions. We used SmartPLS version 3.0 to analyze the coefficients of interaction terms. The significance of a moderator was confirmed by t value (t >1.96) for all interaction effects (path coefficients). SPSS version 20.0 for Windows was used to calculate the model fit (R2 without moderator), new model fit (R2 with moderator), difference between these R2 values, and significance of this difference for all endogenous latent variables.
Spss version 20.0 for window
Manufactured by IBM
Sourced in United States, Denmark
SPSS version 20.0 for Windows is a statistical software package that enables data analysis, management, and presentation. It provides a wide range of statistical procedures to help users gain insights from their data.
Automatically generated - may contain errors
Lab products found in correlation
Sas version 9, by SAS Institute (2 mentions)
Prism 8, by GraphPad (2 mentions)
Sas 9, by SAS Institute (2 mentions)
Spss statistic, by IBM (2 mentions)
Cfx manager software, by Bio-Rad (1 mentions)
Version 12, by MedCalc (1 mentions)
Stata version 15.0 for mac, by StataCorp (1 mentions)
Prism 6, by GraphPad (1 mentions)
Spss version 22, by IBM (1 mentions)
Statistical software version 18, by MedCalc (1 mentions)
Medcalc15, by MedCalc (1 mentions)
Stata 15, by IBM (1 mentions)
R software, by R Project for Statistical Computing (1 mentions)
Prism 7, by GraphPad (1 mentions)
Spss statistics for windows version 20, by IBM (1 mentions)
272 protocols using spss version 20.0 for window
1
Analyzing Interactions with PLS and Regression
2
Statistical Analysis of Numerical and Categorical Data
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The numerical data were described by means and standard deviations or medians and ranges. The categorical data were expressed as counts and percentages. The numerical and the categorical data were compared with the Student’s t-test and chi-square test. Two-sided tests were used, and a p-value of less than 0.05 was statistically significant. All data in the present study were analyzed with commercial statistical software (SPSS version 20.0 for Windows, SPSS Inc., Chicago, IL, USA).
3
Analyzing Risk Factors for AKI in Pregnant Women
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Quantitative data was expressed as mean ± SD. Data that do not meet the normal distribution was expressed as median and interquartile range; Categorical data was expressed as frequencies and percentages (n, %). Baseline characteristics of study population were compared using ANOVA test for continuous variables and χ2 tests for categorical variables. The Wilcoxon rank sum test was used for continuous variables that were not normally distributed. Logistic regression model was used to estimate the odds ratio (OR) of risk factors for AKI in hospitalized pregnant women, with adjustment of age, baseline SCr, length of stay in hospital, division, hospital and clinical comorbidities. We calculated the population attributable fractions (PAF) using the formula PAF = f(r-1)/[1 + f(r-1)], where r is the estimated relative risk and f is the proportion of AKI cases that were exposed to the risk factor of interest. We estimated the hazard ratio (HR) of AKI and other possible risk factors for in-hospital death in pregnant women with AKI using Cox proportional hazard model. The value of P < 0.05 was considered statistically significant. All the statistical analysis was performed using SPSS version 20.0 for windows (SPSS Inc., Chicago, IL, USA).
4
Statistical Analysis of Clinical Trial Outcomes
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The primary endpoint will be analyzed based on an intention-to-treat principle, regardless of whether they completed the originally allocated treatment study protocol. Any reasons for protocol violations will be described. All p values are two-tailed, and the significance level will be a p value <0.05.
Continuous variables will be expressed as means and standard deviations (normal distribution) or median with interquartile range (skewed distribution). Student’s t test (normal distribution) or Mann-Whitney U test (skewed distribution) will be used for group comparisons. Data will be presented as frequencies and percentages for categorical variables. Categorical variables will be compared using Pearson’s chi-squared test or Fisher’s exact test as appropriate. Time-dependent data will be presented as Kaplan-Meier curves. Statistical uncertainty will be expressed in terms of a relative risk and 95% confidence intervals.
Data will be analyzed using the statistical program SPSS version 20.0 for Windows (SPSS Inc., Chicago, IL, USA).
Continuous variables will be expressed as means and standard deviations (normal distribution) or median with interquartile range (skewed distribution). Student’s t test (normal distribution) or Mann-Whitney U test (skewed distribution) will be used for group comparisons. Data will be presented as frequencies and percentages for categorical variables. Categorical variables will be compared using Pearson’s chi-squared test or Fisher’s exact test as appropriate. Time-dependent data will be presented as Kaplan-Meier curves. Statistical uncertainty will be expressed in terms of a relative risk and 95% confidence intervals.
Data will be analyzed using the statistical program SPSS version 20.0 for Windows (SPSS Inc., Chicago, IL, USA).
5
Diagnostic Efficiency of miR-338-3p
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All study data were stored in a standard EXCEL database. All the statistical analysis was performed using SPSS version 20.0 for windows (SPSS Inc., Chicago, IL, USA). Continuous variables were expressed as mean (x) ± SD. Categorical variables were expressed as frequencies and percentages (n, %). Baseline characteristics were analyzed by chi-square test or Fisher exact tests, if appropriate, and analysis of variance (ANOVA). Tukey’s multiple comparison test was used after the overall analysis in ANOVA. Diagnostic efficiency of miR-338-3p was analyzed by receiver operating characteristic (ROC) curve analysis. Repeated measurement data were analyzed by repeated ANOVA and generalized estimating equations (GEE). The value of p < 0.05 was considered statistically significant.
6
Factors Influencing Treatment Preferences
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The data was cleaned, coded and analyzed using the SPSS version 20.0 for Windows. It was checked for its distribution and outliers before analysis. Multi co-linearity was checked for independent variables and the variance inflation factor (VIF) was found to range between 1.005 and 1.053 for each of the independent variables. VIF conveys the degree to which multicollinearity amongst the predictors degrades the precision of an estimate. If the value of VIF is higher, there is high probability of multicollinearity amongst the predictors in the model. In general, VIF should not be greater than 10. Descriptive analysis, including frequency distribution, cross tabulation and summary measures were computed. Tests of association between predictors and outcome variables were investigated using Chi square test bivariate and multivariate logistic regression analysis. The association between traditional disease explanatory model and preferred treatment option was computed by controlling for potential confounders. P value less than 0.05 was considered statistically significant.
7
Statistical Analysis of Experimental Data
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
All the experiments were repeated at least three times. Differences between the experiment group and the untreated control group were statistically analyzed by SPSS (version 20.0 for Windows). One-way ANOVA and post hoc Tukey's multiple-comparison test were applied for the comparison of multiple means. The chosen level of significance was set at P < 0.05.
8
Post-traumatic Stress Disorder Prevalence
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Descriptive and inferential statistics were calculated using SPSS version 20.0 for Windows (SPSS Inc, Chicago IL). Means were calculated to summarize continuous variables. For categorical variables, group proportions were calculated. The one-way analysis of variance (ANOVA) and independent t-test were employed to identify the effect of demographic factors on the psychological outcome measure (IES-R). A total score of IES-R > 20 was used to estimate the prevalence of PTSD symptoms. ANOVA was used for age, level of education, profession, marital status, and monthly income, whilst t-test was used for gender, ethnicity, and residence. All statistical tests were two-sided and a P value < 0.05 was considered statistically significant.
9
Hemodynamic Data Analysis Protocol
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Hemodynamic data obtained in subsequent treatments were averaged to account for repeated measurements in the same subject Results are presented as the mean value ± SD or the median and interquartile range. Normal distribution of the data was verified by the Kolmogorov-Smirnov test. Statistical methods used were two-sample t-test for comparison of means and single factor variance analyses with repeated measurement for analyses of temporal changes. The reproducibility of repeated individual measurements was evaluated by Pearson’s correlation coefficient r and Wilcoxon signed rank test. A p < 0.05 was considered significant. Statistical calculations were done with SPSS, Version 20.0 for Windows (SPSS Inc., Chicago, IL, USA).
10
Comparison of Glucose Levels
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Results are presented as mean ± standard deviation (SD) for quantitative variables and were summarized by frequency (percentage) for categorical variables. Continuous variables were compared using the t test or the Mann–Whitney U test whenever the data had normal distribution or not. The within-group comparisons were examined by the paired t-test or the Wilcoxon signed rank test. Categorical variables were, on the other hand, compared using the Chi-square test. For evaluating the changes in serum glucose in the studied groups, repeated measure ANOVA was used. For the statistical analysis, the statistical software SPSS version 20.0 for windows (SPSS Inc., Chicago, IL, USA) was used. P values of 0.05 or less were considered statistically significant.
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!