Spss statistic for windows version 26

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SPSS Statistics for Windows, Version 26.0 is a comprehensive software package for statistical analysis. It provides a wide range of statistical techniques, including descriptive statistics, bivariate statistics, prediction for numerical outcomes, and prediction for identifying groups.

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SPSS 26 Statistics for Windows, Version 26 SPSS Statistics for Windows, Version 26.0 SPSS Statistics for Window, Version 26.0 SPSS Statistics 26 for Windows Statistics for Windows version 26 SPSS Statistics for Windows, Version SPSS for Windows version 26.0 SPSS Statistic version 26 SPSS Statistics version 26 SPSS Statistic for Windows

6 protocols using spss statistic for windows version 26

Predictors of Mortality and MACE in COVID-19 Patients

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Descriptive statistics were performed for all study variables. Continuous variables were expressed as mean ± standard deviation (SD) or median (interquartile [IQR]) for skewed variables. Categorical variables were expressed as percentages. Normality of data was tested using the Kolmogorov-Smirnov test. Comparison of continuous variables was performed using Student’s t-test or the Mann-Whitney U-test, and of binominal variables using the χ² or Fisher exact test, respectively. Comparison between three groups was performed using one-way ANOVA for continuous data. Univariable and multivariable Cox regression models were used to evaluate potential predictors of in-hospital mortality and MACE.
Kaplan-Meier survival curves were used to compare event-free and survival rates for COVID-19 patients by the log-rank test. Receiver operating characteristics (ROC) curves were constructed to determine the ability of baseline cTn T to predict mortality and MACE and to identify its sensitivity and specificity.
Data were analyzed using IBM SPSS Statistic for Windows, Version 26.0 (Armonk, NY: IBM Corp.). A p value < 0.05 was considered significant.

Luchian M.L., Motoc A.I., Lochy S., Magne J., Roosens B., Belsack D., Van den Bussche K., von Kemp B., Galloo X., François C., Scheirlynck E., Boeckstaens S., De Potter T., Seyler L., van Laethem J., Hennebicq S., Weytjens C., Droogmans S, & Cosyns B. (2021). Troponin T in COVID-19 hospitalized patients: Kinetics matter. Cardiology Journal, 28(6), 807-815.

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Statistical Analysis of Research Data

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Data analyses were made by using IBM SPSS Statistic for Windows (Version 26.0) software.
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All data were presented as mean ± standard deviation.

Subramaniam P.K., Al-Ahmad B.E., Mustafa N.S., Izhan N.A, & Shukor N.F. (2022). Effect of Visual Exposure versus Obstruction upon Patient's Quantitative and Qualitative Stress Parameters Changes during Minor Oral Surgery. European Journal of Dentistry, 17(3), 895-901.

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Thorax Motion in Firefighters with PPE

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The questionnaire survey consisted of 19 male FFs aged 21 to 53. Their average age, height, and BMI were 35.7, 170.8 cm, and 24.5. Thirty-seven percent of the respondents had less than 10 years of service. All of them were full-time and trained FFs. The demographic background of FFs involved in this study is described in Table 1.
The IBM SPSS Statistic for windows, version 26.0 (IBM Corp., Armonk, NY, USA) was used for data analysis. Descriptive statistics (Means M), standard deviations (SD), maximum value, and percentages were used to describe the angle deviation and angular acceleration of thorax extension collected by the motion capture. The ANOVA statistical test was used to analyze the comparison between the age and BMI groups. The t-test was used to analyze the comparison of the angle deviation and angular acceleration of the thorax between those without PPE and those with PPE.

Yunus M.N., Jaafar M.H., Mohamed A.S., Azraai N.Z., Amil N, & Zein R.M. (2022). Biomechanics Analysis of the Firefighters’ Thorax Movement on Personal Protective Equipment during Lifting Task Using Inertial Measurement Unit Motion Capture. International Journal of Environmental Research and Public Health, 19(21), 14232.

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Web-based Questionnaire Data Analysis

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All original data of this web-based questionnaire were downloaded as a .sav le format from the backstage management platform. Because all the questions in the web-based questionnaire were required, all the data were compliant with the integrity veri cation requirements. Data analysis was performed using IBM SPSS statistic for Windows, version 26.0 (IBM Corp., Armonk, NY., US). Frequency and related percentage were reported to describe classi ed variables. The arithmetic average was reported for continuous variables, as well as a bar chart to present the numerical distributions. Highcharts were used to analyze the open-ended questions.

Li H., Qian Y., Yang K., Ding W., Huang L., Ma X., Duan L., Wang D., Guan Y., Xiao N., & Zhou X. (2020). Assessment of China’s Contribution to the Regional Network for Asian Schistosomiasis: A Questionnaire survey.

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Statistical Analysis of Factors

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Data were analyzed using IBM SPSS Statistic for Windows, version 26 software (IBM Corp., Armonk, NY, USA). Factors with p-value < 0.25 on simple logistic regression were analyzed using forward methods of multiple logistic regression. The level of significance was set at a p-value of less than 0.05.

Nordin S., Yaacob N.A., Kelak J., Ilyas A.H, & Daud A. (2022). The Mental Health of Malaysia’s Northwest Healthcare Workers during the Relaxation of COVID-19 Restrictions and Its Associated Factors. International Journal of Environmental Research and Public Health, 19(13), 7794.

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Cyberbullying and Suicidal Behavior Among Malaysian Adolescents

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Data entry and analysis used IBM SPSS Statistic for Windows, Version 26 (IBM Corp. in Armonk, New York, NY, USA) [58 ]. Descriptive statistics for categorical variables were summarized as frequencies and percentages, while each continuous variable was summarized in the form of the mean and standard deviation (SD). The prevalence of cyberbullying and suicidal behaviour among secondary school adolescents in Peninsular Malaysia were presented in the form of frequency and percentage. Simple and multiple binary logistic regression were used to examine the association between independent variables and suicidal behaviour as a binary outcome. The strength of association was estimated using the crude and adjusted odds ratio (COR and AOR) with a 95% confidence interval (CI). Independent variables associated with the outcome at the p < 0.25 level in the simple logistic regression were included in multiple logistic regression models using the forward stepwise selection method by likelihood-ratio test, the backward stepwise selection method by likelihood-ratio test, and manual selection methods. The significance level was based on p < 0.05.

Mohd Fadhli S.A., Liew Suet Yan J., Ab Halim A.S., Ab Razak A, & Ab Rahman A. (2022). Finding the Link between Cyberbullying and Suicidal Behaviour among Adolescents in Peninsular Malaysia. Healthcare, 10(5), 856.

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