Data analysis was done using MedCalc® Statistical Software version 19.8 (MedCalc Software Ltd, Ostend, Belgium). Continuous data were expressed as medians and interquartile ranges (IQR). Chi‐squared test was used for the comparison of two independent proportions. p Values below 0.05 (two‐tailed) were considered statistically significant. The sensitivity and specificity (with 95% CIs) of XN‐31 and routine microscopy (consensus of two microscopists) were compared to that of the reference. For phase 1, the reference method was expert microscopy, and for phase 2, it was expert microscopy and PCR (for residual discrepancies post‐expert microscopy).
Statistical software version 19
Manufactured by MedCalc
Sourced in Belgium, United States
MedCalc Statistical Software version 19.2.6 is a comprehensive software package for biomedical statistics. It provides a wide range of statistical analysis tools and functions to assist researchers, clinicians, and other healthcare professionals in analyzing and interpreting their data.
Automatically generated - may contain errors
Lab products found in correlation
Spss statistics for windows version 23, by IBM (4 mentions)
Spss statistics for windows version 25, by IBM (4 mentions)
Prism 9, by GraphPad (3 mentions)
Spss statistics version 25, by IBM (3 mentions)
Spss version 25, by IBM (3 mentions)
Spss version 22, by IBM (3 mentions)
Spss statistics version 23, by IBM (2 mentions)
Spss v23, by IBM (2 mentions)
Spss statistics for window, by IBM (2 mentions)
Prism 8, by GraphPad (2 mentions)
Jmp software version 10, by SAS Institute (2 mentions)
Spss statistics for windows version 27, by IBM (2 mentions)
Prism 7, by GraphPad (2 mentions)
Spss statistics for windows version 26, by IBM (2 mentions)
Spss statistics for windows version 22, by IBM (2 mentions)
Spss version 20, by IBM (2 mentions)
Sas 9, by SAS Institute (2 mentions)
Statistical package for social sciences spss v25, by IBM (1 mentions)
Stata statistical software version 17, by StataCorp (1 mentions)
Statistical package for the social sciences statistics for windows version 19, by IBM (1 mentions)
435 protocols using statistical software version 19
1
Evaluation of XN-31 for malaria diagnosis
2
Sepsis Mortality Prediction Evaluation
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Categorical data were expressed as absolute frequencies and percentages, while means ± standard deviation (SD) were reported for continuous variables. Differences between patients deceased or discharged for sepsis were compared with the Pearson’s X2, student t tests and Mann–Whitney tests as appropriate. The association between IHM and the investigated tools (i.e., NEWS, qSOFA, MqSOFA and the lactate assay) was studied with univariated and multivariated logistic regression analysis. Odds ratios (ORs) and their 95% confidence intervals (CI) were reported. Moreover, the areas under the curve (AUC) of the receiver operating characteristic (ROC) curves were pairwise compared to identify the tool with the best discriminative ability. Because of lactates showed a non-normal distribution, the natural logarithm of lactates was calculated to obtain ORs. Moreover, similar analysis with ROC curves were performed with five different groups of sepsis aetiologies, such as respiratory, urinary, abdominal, miscellaneous and indeterminate.
The Statistical Product and Service Solution (SPSS) 23.0 for Windows (IBM Corp., Armonk, NY, USA) and MedCalc® Statistical Software version 19.8 (MedCalc Software Ltd, Ostend, Belgium) were used for statistical analyses and the significance level was set for p < 0.05.
The Statistical Product and Service Solution (SPSS) 23.0 for Windows (IBM Corp., Armonk, NY, USA) and MedCalc® Statistical Software version 19.8 (MedCalc Software Ltd, Ostend, Belgium) were used for statistical analyses and the significance level was set for p < 0.05.
3
Oxidative Stress and Bronchiectasis Analysis
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SPSS 17.0 (Chicago Inc., 2008) and MedCalc® Statistical Software version 19.8 (MedCalc Software Ltd, Ostend, Belgium; https://www.medcalc.org ; 2021) were used for the statistical analysis. Categorical variables were indicated as frequency (n) and percentage (%). The fitness of the continuous variables to normal distribution was tested using the Kolmogorov–Smirnov method. The NT and TT levels, identified to display a normal distribution, were indicated as mean and standard deviation, while other laboratory parameters (disulfide, SS-SH, SS-TT, SH-TT, and IMA) were indicated as median and interquartile range as they do not display a normal distribution. Student's t-test and Mann–Whitney U tests were used for the binary comparison of the continuous variables. As for the categorical variables, they were analyzed using the Pearson chi-squared and Fisher's exact tests. The correlation between bronchiectasis and oxidative stress parameters was analyzed using Spearman's correlation test. p < 0.05 was accepted for significance.
4
Correlation Analysis of Research Data
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Data recording and processing were performed using Microsoft Excel 2016. The correlation analysis and graph generation were assessed by Bland–Altman and Passing–Bablok regression analyses using MedCalc® Statistical Software version 19.8 (MedCalc Software Ltd).
5
Insect Survivorship Assessment Protocol
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The survivorship of tested insects was described using the restricted mean survival time (RMST) analysis and Kaplan–Meier survival curves were constructed by using the MedCalc Statistical Software version 19.8 (MedCalc Software Ltd, Ostend, Belgium; https://www.medcalc.org ). The restricted mean survival time (RMST) is a measure of average survival from the beginning of the study to a specified time point to allow statistical comparison between study groups. In our study, the time point for RMST is determined by the Medcalc statistical software, set to the lowest time point of the last event among the different groups. The statistical significance for fecundity and nymphal development was determined by independent t-test. For enzyme biochemical assays, KT100, and percentage mortality 48 h post-treatment, significance was assessed based on the one-way ANOVA and Duncan’s multiple range test. All statistical analyses were performed using the IBM Statistical Package for Social Sciences (SPSS) v.25 at a significance level of α = 0.05.
6
Evaluating COVID-19 Rapid Antigen Tests
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Descriptive statistics were used in the analysis of staff demographics, job role, and concordance between positive LFD and PCR results. For statistical analysis, MedCalc Statistical Software Version 19.8 was used. A positive predictive value for the LFD was calculated. Patient demographics between groups were analysed using Chi-Squared test. Significance threshold was set to p < 0.05.
7
Evaluating Risk Factors for Low Birth Weight
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Categorical variables were presented as frequencies and percentages. Continuous data were presented as mean ± SD. Logistic regression analysis was used to evaluate the risk factors associated with LBW. To determine potential factors associated with birth weight, we first performed univariate logistic regression analysis. This was followed by multivariate logistic regression analysis using the enter method for variables with p-values <0.05 after univariate analysis to identify independent risk factors. Statistical analysis was performed using Stata version 14.2, GraphPad Prism 8 and MedCalc statistical software version 19.8. The receiver operating characteristics (ROC) curve was computed at an estimated prevalence of LBW, 9.69% and confidence interval (CI) of 95%. All tests were two-sided and p-value < 0.05 was considered statistically significant.
8
Evaluation of uNGAL for AKI Diagnosis
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Data were analyzed by MedCalc® Statistical Software version 19.8 (MedCalc Software Ltd., Ostend, Belgium). The continuous variables were presented as Mean ± SD and the categorical variables were represented as percentage values. Student's t-test and Chi-square test was used to compare the means. ANOVA followed by a Bonferroni post hoc test for comparison of three or more groups. Bivariate analysis was used to evaluate factors associated with 30-day mortality, factors found significant were analyzed in multivariate analysis. The receiver operating curve (ROC) curve was used to evaluate uNGAL as a diagnostic marker for AKI. p-value < 0.05 is statistically significant.
9
Intraobserver and Interobserver Reliability Evaluation
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Using the Bonett method for sample size calculation,3 (link)
given an expected intraclass correlation coefficient (ICC) reliability of 0.85 with a precision of ±0.09,23 (link)
a confidence level of 95%, 6 raters, and an expected dropout rate of 0%, we calculated a minimum sample size of 21 images per item. We calculated the ICC (2-way model, absolute agreement) with 95% CI to determine the intraobserver reliability and interobserver reproducibility. All statistical analyses were conducted using MedCalc Statistical Software Version 19.8 (2021).
given an expected intraclass correlation coefficient (ICC) reliability of 0.85 with a precision of ±0.09,23 (link)
a confidence level of 95%, 6 raters, and an expected dropout rate of 0%, we calculated a minimum sample size of 21 images per item. We calculated the ICC (2-way model, absolute agreement) with 95% CI to determine the intraobserver reliability and interobserver reproducibility. All statistical analyses were conducted using MedCalc Statistical Software Version 19.8 (2021).
10
Quantitative Imaging Biomarkers for Nodule Evaluation
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All results were expressed as mean ± standard deviation (SD) unless indicated. Ki and perfusion indices BV and AF of benign and malignant nodules were statistically compared using the nonparametric Mann-Whitney U test. The accuracy of the different techniques and parameters was tested with area under the curve (AUC) in receiver operating characteristic (ROC) analysis with 95% confidence interval (CI). Comparison between the ROCs was performed using DeLongs test. Youdin index analysis was used to derive the optimised cut-point values. Mann-Whitney U test and ROC curve analyses were performed on GraphPad Prism version 8.2.1 for Windows (GraphPad Software, San Diego, CA, USA). Youdin index analysis and nonparametric DeLongs test were performed on MedCalc Statistical Software version 19.8 (MedCalc Software Ltd, Ostend, Belgium; https://www.medcalc.org;2021). A p value < 0.05 was considered statistically significant.
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