Spss statistical software package version 13

Manufactured by IBM

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SPSS statistical software package version 13.0 is a comprehensive data analysis and statistical software tool. It provides a wide range of data management, analysis, and reporting capabilities for professionals and researchers. The software is designed to handle a variety of data types and supports statistical techniques for data exploration, modeling, and prediction.

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23 protocols using spss statistical software package version 13

Analysis of Fatal Construction Site Falls

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SPSS statistical software package Version 13 was used for data analysis. The associations between the frequencies of the participants with fatal injuries from falls at construction sites, the demographics, and work-related variables were analyzed. The statistical analysis included Pearson χ² test, and Kruskal-Wallis tests. Significance level was set at p< 0.05. Table 1. Sociodemographic Characteristics of the Study Population
The following variables were evaluated in terms of their distribution and completeness: The outcome (fatal injury type), dependent, sociodemographic characteristics (sex, age, level of education), type of employment (full time: regular work more than 36 hours/week, part time: regular work less than 36 hours/ week, causal; has no guaranteed hours of work and usually works irregular hours, fixed term, employed for a specific period of time or task, shift worker: works shifts and gets an extra payment for working shift hours), and occupation place at the time of the occupational injury, insurance state. The dependent versus the outcome variables were plotted to identify outliers and trends in the data. Categorical and ordinal variables were derived where appropriate. The categories of the cause and nature of injury variables were collapsed to group the least frequently occurring categories.

Khodabandeh F., Kabir-Mokamelkhah E, & Kahani M. (2016). Factors associated with the severity of fatal accidents in construction workers. Medical Journal of the Islamic Republic of Iran, 30, 469.

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Statistical Analysis of Research Data

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The data were analyzed using Student's t test using the SPSS statistical software package version 13 (SPSS Inc., Chicago, IL). All data were expressed as mean ± SD. For all analyses a two-sided p value of less than 0.05 was deemed statistically significant.

Ju L., Zhou Z., Jiang B., Lou Y, & Guo X. (2017). Autocrine VEGF and IL-8 Promote Migration via Src/Vav2/Rac1/PAK1 Signaling in Human Umbilical Vein Endothelial Cells. Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology, 41(4).

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Quantitative Analysis of Intact MPO

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Data pertaining to quantitative variables are expressed as Mean ± Standard deviation (SD); between-group differences were assessed by t test. Data from intact MPO was used as control. A P-value <0.05 was considered This website utilizes technologies such as cookies to enable essential site functionality, as well as for analytics, personalization, and targeted advertising. To learn more, view the following link: Privacy Policy indicative of a statistically significant difference. Analysis was performed with SPSS statistical software package, version 13 (SPSS Inc., Chicago, IL, USA).

Wang J., Li J.N., Cui Z, & Zhao M.H. (2018). Deglycosylation influences the oxidation activity and antigenicity of myeloperoxidase. Nephrology (Carlton, Vic.), 23(1).

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Statistical Analysis of Quantitative and Qualitative Data

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Differences of quantitative parameters were assessed using the t‐test for data that were normally distributed, or nonparametric test for data that were not normally distributed. Differences of qualitative data were compared using chi‐square test and Fisher's exact test. Data from animal experiments are expressed as mean ± S.E.M. All statistical analyses were two‐tailed, and P value <0.05 was considered significant. Analysis was performed using SPSS statistical software package, version 13.0 (SPSS Inc., Chicago, IL, USA).

Hu S., Gu Q., Wang J., Wang M., Jia X., Cui Z, & Zhao M. (2017). The pathogenicity of T cell epitopes on human Goodpasture antigen and its critical amino acid motif. Journal of Cellular and Molecular Medicine, 21(9), 2117-2128.

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Statistical Analysis of Clinical Outcomes

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All the statistical analyses were performed using SPSS statistical software package, version 13.0 (SPSS Inc., Chicago, IL, USA). Differences of quantitative parameters were assessed using the t-test for data that were normally distributed or nonparametric test for data that were not normally distributed. Differences of qualitative data were compared using the chi-square test/Fisher’s exact test, otherwise, the Kruskal–Wallis or Mann–Whitney U tests were performed. Correlations of quantitative parameters were analyzed using the Pearson correlation coefficient analysis for data that were normally distributed and Spearman correlation coefficient analysis for data that were not normally distributed. Kaplan–Meier curves were used to analyze the clinical treatment outcomes of patients (Log-rank test). If the P value of the candidate predictor in univariate survival analysis was less than 0.05, this predictor would be included into the multivariable Cox regression models. All statistical analyses were two-tailed and P value < 0.05 was considered significant.

Gu Q.H., Cao X., Mao X.M., Jia J.Y, & Yan T.K. (2022). Significance of thyroid dysfunction in the patients with primary membranous nephropathy. BMC Nephrology, 23, 398.

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Statistical Analysis of Cancer Outcomes

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Continuous data were summarized as means and standard deviation. Categorical data were depicted using absolute frequencies and relative percentages. Statistical comparisons for quantitative data were performed using Wilcoxon rank sum test. Analysis of QLQ-C30 and QLQ-CX24 were done according to the EORTC quality of life group guidelines. Longitudinal analysis of the scores were performed using a linear mixed model with patients as random effect and time (in months), age (qualitative, age > 70), body mass index (BMI) (qualitative, BMI > 30), and their interaction as fixed effects. All statistical analyses were performed with R v. 4.0.1 and package lme4, and p-values lower than 0.05 were considered significant. Survival analysis for outcomes was performed considering overall survival (OS), calculated from the date of histological exam to the date of death from any cause or the date of last follow-up. Metastasis-free survival (MFS) was calculated from the date of the end of brachytherapy course to the date of either distant metastases or the date of the last follow-up. Kaplan-Meier product limit estimates were applied to estimate the rates of OS and DFS. SPSS statistical software package version 13.0 (SPSS, Chicago, IL, USA) was used for survival analysis.

Facondo G., Vullo G., Sanctis V.D., Vitiello C., Nieddu L., Alfò M., Scaringi C., Felice F.D., Rotondi M., Giacomo F.D., Ruscito I., Valeriani M, & Osti M.F. (2022). Quality of life and sexual functioning among endometrial cancer patients treated with one week adjuvant high-dose-rate vaginal brachytherapy schedule. Journal of Contemporary Brachytherapy, 14(4), 341-346.

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Statistical Analysis of In Vitro Experiments

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SPSS statistical software package version 13.0 (SPSS Inc., Chicago, IL, USA) was used for the analyses. All data were expressed as means ± standard deviation (SD) of at least 3 in vitro experiments. Statistical significance was tested using an independent-samples t-test to compare data between two groups. P-values of <0.05 were considered statistically significant.

Du A., Jiang Y, & Fan C. (2018). NDRG1 Downregulates ATF3 and Inhibits Cisplatin-Induced Cytotoxicity in Lung Cancer A549 Cells. International Journal of Medical Sciences, 15(13), 1502-1507.

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Statistical Analysis of Clinical Outcomes

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Results were expressed as mean ± standard deviation (for data that were normally distributed), or median and interquartile range (IQR) (for data that were not normally distributed). Differences of quantitative parameters between groups were assessed using the t test (for data that were normally distributed) or nonparametric test (for data that were not normally distributed). Differences of semiquantitative results were tested using the Mann–Whitney U test. Differences of qualitative results were compared using χ² test. Kaplan–Meier curves were used to analyze patient survival as well as renal survival. It was considered significant difference if the P value was < 0.05. Analysis was performed with SPSS statistical software package (version 13.0; Chicago, IL).

Zou R., Liu G., Cui Z., Chen M, & Zhao M.H. (2015). Clinical and Immunologic Characteristics of Patients With ANCA-Associated Glomerulonephritis Combined With Membranous Nephropathy: A Retrospective Cohort Study in a Single Chinese Center. Medicine, 94(37), e1472.

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Predictors of Renal Outcome

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Values are expressed as the mean ± standard deviation (SD) and median [interquartile range (IQR)] for continuous normally and non-normally distributed variables, respectively. Differences in quantitative parameters between groups were assessed with the t-test (for normally distributed data) or non-parametric test (for non-normally distributed data). Differences in qualitative results were compared with the chi-square test. Kaplan-Meier survival analysis was performed to analyze the renal outcome. Multivariate analysis of predictors of the renal outcome was performed with Cox proportional hazards regression and results are expressed as hazard ratios (HRs) with 95% confidence intervals (CI). P values less than 0.05 were considered statistically significant. Statistical analysis was performed using SPSS statistical software package (version 13.0, Chicago, IL).

Lv L., Chang D.Y., Li Z.Y., Chen M., Hu Z, & Zhao M.H. (2017). Persistent hematuria in patients with antineutrophil cytoplasmic antibody-associated vasculitis during clinical remission: chronic glomerular lesion or low-grade active renal vasculitis?. BMC Nephrology, 18, 354.

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Biochemical Failure and Survival Analysis

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The biochemical failure was defined as the PSA nadir +2 ng/mL according to Phoenix criteria [11 (link)]. Overall survival (OS) and disease free survival (DFS) were calculated using the Kaplan–Meier method. The chi-square test was performed to compare 4 times weekly and 5 times weekly treatment-related toxicities between these two groups. Statistical analyses were performed using SPSS statistical software package version 13.0 (SPSS, Inc., Chicago, IL). A p value lower than 0.05 was considered as statistically significant.

Valeriani M., Carnevale A., Osti M.F., DE Sanctis V., Agolli L, & Maurizi Enrici R. (2014). Image guided intensity modulated hypofractionated radiotherapy in high-risk prostate cancer patients treated four or five times per week: analysis of toxicity and preliminary results. Radiation Oncology (London, England), 9, 214.

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