Continuous variables are presented as mean ± standard deviation and categorical variables are presented as frequency and percent. Univariable analyses were carried out using binary logistic regression, Chi-square and Fisher’s exact tests, as appropriate. Post hoc testing for crosstabs exceeding 2×2 dimension was performed by calculating adjusted standardized residuals (z-scores) and associated p-values. Significance was evaluated after Bonferroni correction. Multivariable analysis was performed by integrating variables with a possible association (p < 0.15) with LVO. Stepwise backward elimination was performed and p-values of < 0.05 were considered statistically significant. Collinearity diagnostics were performed assessing correlation coefficients and variance inflation factors. Discrimination of predictive models was performed using the area under the receiver operating characteristic curve (AUC). Analysis of AUC, sensitivity/specificity criteria were calculated with MedCalc. Calibration of scores was tested using Hosmer and Lemeshow test. Comparison of receiver operating characteristic curves was performed using DeLong test. Statistical analyses, creation of figures and charts were performed using IBM SPSS version 22, MedCalc, MS Excel, and Adobe Photoshop CS5.
Spss version 22
Manufactured by MedCalc
Sourced in United States
SPSS version 22.0 is a statistical software package that provides data management, analysis, and presentation capabilities. It is designed for the analysis of quantitative data. The software offers a wide range of statistical techniques, including descriptive statistics, regression analysis, and multivariate analysis.
Automatically generated - may contain errors
Lab products found in correlation
Version 19, by MedCalc (3 mentions)
Version 20, by MedCalc (2 mentions)
Sas version 9, by SAS Institute (2 mentions)
Ms excel, by Adobe (1 mentions)
Statistical software version 18, by MedCalc (1 mentions)
Statistical software version 17, by MedCalc (1 mentions)
Software version 15, by MedCalc (1 mentions)
Prism 8, by GraphPad (1 mentions)
Version 14, by MedCalc (1 mentions)
18 protocols using spss version 22
1
Predictive Models for Large Vessel Occlusion
2
Atherogenic Indices and Metabolic Syndrome
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Outcome measures are presented as the mean ± standard deviation (M ± SD). Student’s t-test and the chi-square test were applied for the comparison of continuous and categorical variables, respectively. Subjects were divided into 4 quartiles according to the values of atherogenic indices. To evaluate the possible association between these atherogenic indices and MetS, odds ratios (ORs) with 95% confidence intervals (CIs) were reported by logistic regression analysis using crude and adjusted models (adjusted for age, BMI, physical activity, and smoking). The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was measured to compare the predictive capacity of the various atherogenic indices for identifying MetS. The best cutoff points were defined by the maximum value of Youden’s index (sensitivity + specificity 1). Data analysis was carried out using SPSS version 22 and medcalc version 2.0. A p-value < 0.05 was considered statistically significant.
3
Predicting 24-Hour Urine Sodium
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Stepwise multiple linear regression analysis was used to derive a prediction equation for 24-h urine sodium. Measured 24-h urine sodium was the dependent variable and gender, body weight, height, age, spot potassium, spot creatinine, and spot sodium were the predictive variables to form the equation. Variables with 5% level of significance were selected for the final variables to estimate 24-h urine sodium. Regression diagnostic and assumption checking were performed. All statistical analyses were conducted using SPSS version 22 and MedCalc Statistical software version 18.10 [19 ].
4
Diagnostic Accuracy Assessment Protocol
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Analyses were carried out in SPSS version 22 and MedCalc. Demographic and prevalence data were analysed using appropriate parametric or non-parametric tools. Diagnostic accuracy was assessed using receiver operating characteristic (ROC) curves, calculating Area Under the Curve (AUC), and 2 × 2 cross-tabulations of expert diagnosis and index tests to yield sensitivity, specificity, positive and negative predictive values, with 95% confidence intervals. As we used a priori index test cut-offs, we did not correct for multiple analyses. Post hoc exploratory cut-offs are clearly identified as such.
5
Evaluating Cupping and Acupuncture for COVID-19
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
At the time of design and registration of the proposal, no study had been conducted to investigate the effect of cupping and acupuncture on COVID-19. Therefore, using Power Analysis and Sample Size 11 (PASS-11) software, a sample size of 30 patients in each arm and a total of 90 participants was calculated in order to achieve 90% power (α = 0.05). As decided by the epidemiologist consultant, an Interim Analysis was performed during the study, to adjust sample size based on calculated power.
After data collection, all patients who completed the interventions were included in statistical analysis, which was performed using IBM SPSS version 22 and MedCalc software. Data is presented as mean with standard deviation (SD) and confidence interval (CI) for quantitative variables and frequency with percentage for qualitative ones. In case of normal distribution, one-way ANOVA with Bonferroni as post-hoc. For non-normally distributed data, Friedman test and Kruskal-Wallis test were utilized. To compare the frequency distribution between groups, χ2 or Fisher's exact test were used.
After data collection, all patients who completed the interventions were included in statistical analysis, which was performed using IBM SPSS version 22 and MedCalc software. Data is presented as mean with standard deviation (SD) and confidence interval (CI) for quantitative variables and frequency with percentage for qualitative ones. In case of normal distribution, one-way ANOVA with Bonferroni as post-hoc. For non-normally distributed data, Friedman test and Kruskal-Wallis test were utilized. To compare the frequency distribution between groups, χ2 or Fisher's exact test were used.
6
Predicting Myocardial Injury after PCI
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Continuous variables are presented as mean ± SD or median (IQR, interquartile range), and were compared using Student t test or Mann-Whitney U test, as appropriate. Categorical variables are presented as percentage of patients; they were compared by chi-square or Fisher exact test. As the distribution of Ang-2 was skewed, a base-10 logarithmic transformation was applied. A 2-factor mixed ANOVA was used to test the interaction effect between PMI and time on Ang-2 levels after the procedure. One-way repeated-measures ANOVA test was used to analyze the Ang-2 levels over time in each group. ROC curve analysis was performed to evaluate the diagnostic value of relevant variables for PMI. Multivariable logistic regression model was constructed to assess the independent predictors of PMI, including the variables that were selected based on clinical judgement, or the known risk factors based on literature review [18 (link)], or P value < 0.05 in the univariate analysis. Ultimately, age, gender, hypertension, diabetes, renal dysfunction, SYNTAX score, multivessel lesion, left main artery lesion, left anterior descending artery lesion, total stent length, and NT-proBNP were included in the multivariate model. A 2-tailed P value < 0.05 was considered significant. Statistical analysis was performed using SPSS, version 22 and MedCalc, version 19.0.4.
7
Comparative Analysis of AKI Definitions
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Data analysis was performed on SPSS version 22 and MedCalc 19.5.3 analytical software. Descriptive characteristics of both groups were compared using independent t test for continuous variables and χ 2 or Fisher exact test for categorical variables. Absolute percent change was computed using baseline SCr or eGFR and highest postoperative SCr during the course of hospitalization and categorized as per definitions shown in Table 1. Comparative receiver operating characteristic curves were built and sensitivity, specificity, and area under the curves (AUCs) with 95% confidence interval were computed to assess the performance of all three AKI definitions for predicting the outcomes. A p value of <0.05 was considered significant.
8
Muscle T1-Value in Muscular Dystrophy
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The Shapiro-wilk test was used to evaluate the normality of the data distribution. The individual muscle T1-value among different grades of fat infiltration was compared by test for trend. The Spearman method with Benjamini-Hochberg correction was used to assess the correlation between T1-values, the Mercuri scale and clinical assessments. Mann-Whitney test for individual muscle T1-value and Mercuri scale was performed in DMD patients who used wheelchairs or not. Multiple linear regression analysis was used to determine the independent association of T1-value and clinical motor function. The above results were considered statistically significant when the P < 0.05. Bland-Altman plots and interclass correlation coefficient (ICC) were used to determine the inter-rater reliability of the T1-value ROI measurement. All statistical analyses were conducted with SPSS version 22.0 and MedCalc Version 20.011.
9
Comparative Analysis of Blood Pressure Measurements
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Continuous variables are reported as mean±SD. Frequencies are given as percentages. We compared agreement between BP measurements in 2 ways: We used the method of Bland and Altman with bias (defined as the mean value of the differences) and 95% limits of agreement with their confidence intervals; in addition, we calculated the intraclass correlation coefficient. Because the devices do not retain the replicate measurements but provide only the average, the study follows a paired measurements design. We used IBM SPSS version 22.0 and MedCalc statistical software version 17.11.5 for data analysis.
10
Maternal Age and Birth Defect Prevalence
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The characteristics of the mothers and offspring in the different maternal age groups were compared using the chi-square test or Fisher's exact test for categorical variables, as appropriate. The Cochran–Armitage test was used for trend analysis according to the annual changes and maternal age changes.
The prevalence of BDs was calculated as (the number of BDs among livebirths + spontaneous fetal loss + TOPFA)/ (the total number of births in the population) *10,000. For each BD subtype in teenage pregnancies, the crude relative ratios (RRs) and 95% confidence intervals (CIs) were calculated relative to the 25–29-year age group, while stratified analysis by infant sex for each BD subtypes was conducted. To depict the different profiles of the BD subtypes in the maternal age group, the BD subtypes were sorted in descending order of prevalence. Statistical analysis was performed using SPSS (version 22.0; Chicago, IL, USA) and MedCalc Software version 15.0 (Ostend, Belgium). Graphs and charts were constructed using GraphPad Prism 8 (GraphPad, San Diego, CA, USA). Statistical significance was set at P < 0.05, and all p-values were two-tailed.
The prevalence of BDs was calculated as (the number of BDs among livebirths + spontaneous fetal loss + TOPFA)/ (the total number of births in the population) *10,000. For each BD subtype in teenage pregnancies, the crude relative ratios (RRs) and 95% confidence intervals (CIs) were calculated relative to the 25–29-year age group, while stratified analysis by infant sex for each BD subtypes was conducted. To depict the different profiles of the BD subtypes in the maternal age group, the BD subtypes were sorted in descending order of prevalence. Statistical analysis was performed using SPSS (version 22.0; Chicago, IL, USA) and MedCalc Software version 15.0 (Ostend, Belgium). Graphs and charts were constructed using GraphPad Prism 8 (GraphPad, San Diego, CA, USA). Statistical significance was set at P < 0.05, and all p-values were two-tailed.
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!