Goodness‐of‐fit (calibration) for the models was assessed with the Hosmer–Lemeshow test. Multi‐collinearity between the variables in the model was assessed by calculation of the variance inflation factor. All statistical analyses were performed using Stata software (version 16.0, StataCorp, College Station, Texas, USA). Instrumental variable 2‐stage least squares regression models were completed using the IVREG2 module.23 All tests were 2‐tailed, and a P<0.05 was considered statistically significant. Because of multiple analyses, P<0.05 was expected to occur by chance in 1 out of 20 analyses. The validity of instrumental variables was examined by calculation of the standardized difference of variables that reflects known patient’s characteristics and procedural details in treated and untreated patients stratified on the calendar year during the study period. We used logistic regression to evaluate the predictive power of instruments for treatment with P2Y12 antagonists as well as for primary and secondary outcomes. All tests were 2‐tailed, and P<0.05 was considered statistically significant. All statistical analyses were performed using Stata software (version 16.0, StataCorp, College Station, Texas, USA). All tests were 2‐tailed and a P<0.05 was considered statistically significant.
Stata software
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Sourced in United States, United Kingdom, Denmark, Austria
Stata is a general-purpose statistical software package for data analysis, data management, and graphics. It provides a wide range of data manipulation, statistical, and graphical tools to help researchers and analysts effectively analyze and visualize data.
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Lab products found in correlation
Spss software, by IBM (26 mentions)
Sas software, by SAS Institute (22 mentions)
Stata statistical software, by StataCorp (13 mentions)
Stata statistical software release 13, by StataCorp (10 mentions)
Prism 6, by GraphPad (8 mentions)
Sas 9, by SAS Institute (7 mentions)
Prism 5, by GraphPad (6 mentions)
Spss statistical software, by IBM (6 mentions)
Stata statistical software release 15, by StataCorp (5 mentions)
Stata, by StataCorp (5 mentions)
Prism software, by GraphPad (5 mentions)
R software, by R Project for Statistical Computing (5 mentions)
Prism 8, by GraphPad (4 mentions)
Sas version 9, by SAS Institute (4 mentions)
Stata statistical software release 17, by StataCorp (3 mentions)
Sas statistical software, by SAS Institute (3 mentions)
Stata statistical software release 12, by StataCorp (3 mentions)
Excel for windows, by StataCorp (3 mentions)
Stata statistical software, by SAS Institute (3 mentions)
Stata statistical software release 14, by StataCorp (3 mentions)
2 069 protocols using stata software
1
Goodness-of-fit and multicollinearity analysis
2
Bayesian Network Meta-analysis of Art Therapies
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We used mean difference (MD) and its 95% credible interval (CrI) to describe the results of continuous data. Considering the expected heterogeneity between studies, we conducted random-effects network meta-analyses for each outcome within a Bayesian framework by using Markov Chains Monte Carlo in R software (version 4.1.3). The relative efficacy of art therapies was estimated in accordance with the surface under the cumulative ranking curve (SUCRA) values. The network plots for each outcome were drawn in Stata software (version 15.0). The Egger’s test was used to evaluate the presence of publication bias in Stata software (version 15.0) when more than nine studies were included in analysis (17 (link)). The node-splitting analysis was used to assess the inconsistency if the outcome was a closed loop. Heterogeneity was evaluated with the I2statistics, and the I2 values were considered as none (0%), low (25%), moderate (50%) and high (75%) (18 (link)). To conduct the sensitivity analyses, we removed the study with the smallest sample size for each outcome. And then, the same methods to conduct Bayesian network analysis were repeated. The quality of evidence was evaluated by two authors based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework (19 (link)).
3
Epidemiology of GBS Colonization in Pregnant Women
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Data analysis was performed using Stata Software. Bivariate analysis was performed using Chi-Square and Fisher’s Exact to evaluate the association between risk factors to colonization of GBS in pregnant woman. Logistic regression was performed to compute Odds Ratio (OR) with 95% Confidence Interval (CI).
Power of the test was computed using Stata Software. Previous study found the prevalent of GBS colonization in pregnant woman in Indonesia was 31% (P0 = 0.31) [10 ] and we estimated an increase of 10% (∂ = 0.1) therefor Pa was 41%. Using these parameters, we found the power of the test for a sample size of 179 with alpha 0.05 was 74.3%.
Power of the test was computed using Stata Software. Previous study found the prevalent of GBS colonization in pregnant woman in Indonesia was 31% (P0 = 0.31) [10 ] and we estimated an increase of 10% (∂ = 0.1) therefor Pa was 41%. Using these parameters, we found the power of the test for a sample size of 179 with alpha 0.05 was 74.3%.
4
Multimodal MRI Evaluation of Degenerative Cervical Myelopathy
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Statistical analysis was performed using Stata software (version 16; StataCorp LP, College Station, TX). Mean age was higher in DCM patients compared to healthy controls (DCM, 54.9 ± 11.0; healthy control, 41.6 ± 15.0; p = 0.001 [mean ± SD]); thus, age was considered as a covariate of no interest in our linear regression models. Macrostructural morphometric measurements (i.e., SCA, GMA, and WMA) were compared between healthy controls and DCM patients by means of a one-tailed t-test. Next, microstructural DTI indices (FA, AD, MD, and RD) within the cervical and lumbar cord were compared between groups using a two-sample t-test (unpaired, onetailed, p < 0.05). Patients were divided into two groups depending on the presence versus absence of T2-hyperintensity signal in the cervical cord as a sign of cervical myelopathy. Measurements of MSCC and MCC, volumetric and microstructural MRI readouts, as well as clinical scores were compared between groups using a two-sample t-test (unpaired, one-tailed; p < 0.05). Finally, linear regression and Pearson's correlation analysis in Stata software (StataCorp LP) were performed to reveal possible relationships between volumetric and microstructural MRI readouts in cervical and lumbar cord and clinical and electrophysiological outcomes, adjusted for age, using a level of significance set to p < 0.05.
5
Prognostic Value of Ferritin Staining
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Univariate and multivariate Cox regression analyses were performed using Stata software (version 12.0). Hazard ratios (HR) and the corresponding 95% confidence interval (CI) were calculated based on stratified groups of patients. Kaplan-Meier analyses were performed using Stata software (version 12.0) and GraphPad Prism 5 (version 5.01). Based on visual observation of Kaplan-Meier curves, optimal cutoffs of cFTH1 and nFTH1 staining were determined for reporting. Nonparametric Spearman correlation and Wilcoxon rank-sum test were used for analyzing IHC staining data.
6
Metabolic Syndrome Predictors Analysis
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Data analysis in the present study was performed using STATA software (version 14.0, Stata Corp, College Station, TX, USA). Qualitative data were reported as numbers and percentages. Considering the large sample size, the distribution of all variables in our study was normal and quantitative data were reported as averages and standard deviations. Comparison between qualitative data between the two groups was done using chi‐squared test and comparison between quantitative variables between the two groups was done using independent t‐test. Univariate and multivariate regression analyses were performed to identify the predictors of metabolic syndrome in patients.
ROC analysis was performed using STATA software (version 14.0, Stata Corp) to determine the sensitivity and specificity of the main variables in predicting metabolic syndrome in patients. The p values lower than .05 were considered statistically significant.
ROC analysis was performed using STATA software (version 14.0, Stata Corp) to determine the sensitivity and specificity of the main variables in predicting metabolic syndrome in patients. The p values lower than .05 were considered statistically significant.
7
Determinants of Household Income: Econometric Analysis
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Both descriptive and econometric models were used to analyze the data. Multiple linear regression was used to analyze the determinants (including WTU) of HHI using OLS and 2SLS estimation methods. SPSS and STATA Softwares were employed for the analysis of the data. The following methods were used as model adequacy checking: standardized residuals, test for normality assumption of the error term, checking for multicollinearity, test for presence of hetroscedasticity, test for error term is uncorrelated with explanatory variables, Cook's distance and DFBETAS j(i) . Since the variable time use (TU) was not fixed, the coefficients of regression model were estimated using two stage least square (2SLS), instead of Ordinary least square (OLS) (MADDALA, 1992) . 2SLS model is given by: W here;
-regression parameter/s, X-covariate variables, Z-is instrumental variables and y-is dependent variable (household income). R-Square (R 2 ) and Adjusted R-square (
) were used for model selection criteria and the model was well fitted.
-regression parameter/s, X-covariate variables, Z-is instrumental variables and y-is dependent variable (household income). R-Square (R 2 ) and Adjusted R-square (
) were used for model selection criteria and the model was well fitted.
8
Differential miRNA Expression and Smoking
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For each miRNA, Ct or ΔCt values (Ct target − Ct reference gene), and FC were reported as median and interquartile range (IQR). Subgroup analyses were performed by considering current smokers compared with those who were not current smokers, and by restricting the main analyses to the cases with an early stage of disease at diagnosis (stage I and II).
Comparison of the FCs was carried out using the Wilcoxon rank-sum test and the Dunn multiple comparison test. Results with a P < 0.05 after multiple comparison correction were considered significant.
In addition, we investigated the significance of the interaction between miRNA expression levels and smoking status by including an interaction term in logistic regression models.
Analysis was performed using R 3.5.1 (https://www.r-project.org/ ) and Stata softwares (StataCorp. 2016. Stata Statistical Software: Release 16. StataCorp LP).
Comparison of the FCs was carried out using the Wilcoxon rank-sum test and the Dunn multiple comparison test. Results with a P < 0.05 after multiple comparison correction were considered significant.
In addition, we investigated the significance of the interaction between miRNA expression levels and smoking status by including an interaction term in logistic regression models.
Analysis was performed using R 3.5.1 (
9
Sociodemographic Predictors of Weight Management Practices
10
Respiratory Syncytial Virus Detection Protocol
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A total of 45 samples were assessed for RSV expression and a minimum of 11 samples were used to compare RSV plaque assay formation in each treatment group. All samples were run in duplicate and all experiments completed at least twice to ensure reproducibility. Odd’s ratios and relative risk for RSV detected in cord samples were calculated using cross-tabulations with Fishers exact analysis. Due to an absence of data regarding the prevalence of RSV in CBMs, post-hoc power analysis was used to assess if the study interpretations were feasible based on the sample size available. The observed power was calculated at 82% based on the relative risks of RSV detection and sample size used. In order to mitigate concerns surrounding use of observed power and demonstrate the precision of these findings, confidence intervals are reported for the effect sizes calculated. Due to the small sample size and skewed distribution of the dataset, Mann Whitney-U analysis was used to compare RSV expression between birth seasons, and to assess differences in RSV plaque numbers between non-treated and treated co-cultured cells. Stata software by StataCorp (College Station, Texas, USA) was used to complete graphs and statistical analysis for this study with significance taken as p = <0.05 for two-tailed tests. Graphs represent median values with interquartile ranges unless stated otherwise.
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