Spss statistical software v26

Manufactured by IBM

Sourced in United States

SPSS statistical software v26.0 is a comprehensive data analytics platform that enables users to perform a wide range of statistical analyses. It provides advanced analytical capabilities for data management, exploration, modeling, and reporting. The software is designed to help users uncover insights and make data-driven decisions.

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Lab products found in correlation

Ethovision xt tracking software, by Noldus (1 mentions) R software, by IBM (1 mentions) Prism software v10, by GraphPad (1 mentions)

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SPSS statistical software (4399 citations) SPSS v26 (1880 citations) SPSSTM (8 citations) SPSS softwares (4 citations) SPSS v26 statistical software package (2 citations)

23 protocols using spss statistical software v26

Evaluation of 3D-Printed Swabs for COVID-19 Testing

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General data were analyzed using descriptive statistics: mean, standard deviation, and the range of values for quantitative variables; percentages and frequencies for categorical variables. Inferential analysis was performed with mean differences for two related groups, both to assess the presence of local adverse events and to measure efficacy through the Cq values. The concordance between the positive/negative results in both samples (collected with the control swabs and with the 3D-printed swabs) and the variability in the Cq values between both samples were evaluated using the Kappa index. All the analysis was performed with SPSS statistical software V.26 (http://www-01.ibm.com/software/uk/analytics/spss/; RRID: SCR_002865), considering a statistical significance when P ≤ 0.05.

Sanchez-Sandoval A.L., Sánchez-Pérez C., García-García J.A., Uriega-González S.P., Guerrero-Avendaño G.M, & Barrón-Palma E.V. (2023). Clinical validation of 3D-printed swabs in adults and children for SARS-CoV-2 detection. Biology Methods & Protocols, 8(1), bpad009.

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Cytotoxicity Evaluation and Statistical Analysis

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All results are presented as the mean ± standard deviation (SD). IC50 values were determined with the use of GraphPad Prism software (v. 8.0.0, San Diego, California USA, Trial Version) through regression analysis. Multiple comparisons of groups were analyzed using two-way ANOVA with the post hoc Tukey test. Parameters of LC50 were assessed using a regression Probit analysis (the chi-square test, Pearson goodness of fit test, and 95% confidence interval). Analyses were performed using SPSS statistical software v26 (IBM Corp., Armonk, NY, USA). Differences were considered significant at p-values < 0.05.

Zoi V., Galani V., Vartholomatos E., Zacharopoulou N., Tsoumeleka E., Gkizas G., Bozios G., Tsekeris P., Chousidis I., Leonardos I., Tzakos A.G., Kyritsis A.P, & Alexiou G.A. (2021). Curcumin and Radiotherapy Exert Synergistic Anti-Glioma Effect In Vitro. Biomedicines, 9(11), 1562.

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Statistical Analysis Using SPSS v.26

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SPSS statistical software v.26 (IBM) was used for all analyses. The normality of data was assessed for the quantitative variables.

Ariz U., Fernández‐Atutxa A., Rivas‐Fang O, & Ruiz‐Litago F. (2022). Physical Activity at School Recess: A Key Element in Balancing Social Disparities. The Journal of School Health, 92(10), 1005-1012.

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THC Effects on Larval Zebrafish Behavior

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Graphs and statistical analyses were processed by SPSS statistical software v26 (IBM Corp.). The lethal concentration (LC₅₀) values were assessed using Regression Probit analysis (chi-square test, Pearson goodness of fit test, 95% confidence interval). The effect of THC concentration on heart rate (dependent variable) was assessed with the aid of GLM analysis using the concentration as the independent variable and hpf as a covariate. In order to explore the locomotor activity of larvae, the distance moved and the velocity were recorded with EthoVision XT tracking software (ver. 14 Noldus, Wageningen, The Netherlands). The differences in locomotor activity regarding dark/light cycling were analyzed with the GLM using concentration as a dependent variable and time as a covariate. The vibrational startle response (VSR) test was performed with the aid of the EthoVision XT tracking software. Differences were considered significant at p < 0.001 and marginally significant at p < 0.05.

Chatzimitakos T., Chousidis I., Leonardos D., Stalikas C, & Leonardos I. (2022). In the Swim of Cannabis: Developmental Toxicity and Metabolomic Pathway Alterations of Zebrafish Larvae Exposed to THC for the Assessment of Its Potential Environmental and Human Health Impact. Molecules, 27(17), 5506.

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Crackle Characteristics Predict COPD

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Participants’ characteristics were described as frequencies and determined by COPD status (presence or absence), and differences between groups were analysed with χ² tests. Predictive values of crackle characteristics were evaluated by univariable logistic regression for the two observers separately. Main findings were adjusted for age and sex. Positive predictive values of the strongest COPD predictors were calculated, also in a subgroup of former or current smokers, statistical significance was analysed with χ² test. The presence of crackle characteristics among the participants with COPD was analysed by severity groups, using χ² test for trend. To study to which degree participants were classified with both early and coarse crackles and both late and fine crackles, such concordance in identification was evaluated by kappa statistics. Such analysis was also applied to assess the agreement between the two observers. SPSS statistical software V.26 (IBM) was used.
Written consent was provided by all study participants.

Melbye H., Aviles Solis J.C., Jácome C, & Pasterkamp H. (2021). Inspiratory crackles—early and late—revisited: identifying COPD by crackle characteristics. BMJ Open Respiratory Research, 8(1), e000852.

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Prediabetes Awareness and Outcomes

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Chi-squared tests for proportions and t-test for continuous variables were performed to determine whether Prediabetes-Aware and -Unaware groups differed with respect to their demographic and clinical characteristics and to their perception of health, dietary, and physical activity outcomes. All analyses were conducted in the matched samples. Criteria were a = 0.002 for statistical significance. Individual tests were evaluated for significance using a Bonferroni corrected a = 0.002. SPSS Statistical Software v.26 (IBM, Armonk, NY) was used for data management and analysis.

Li E., Silverio A., Cunningham A., LaNoue M.D, & Mills G. (2021). Association of Prediabetes Status Awareness With Behaviors and Perception of Health. Journal of the American Board of Family Medicine : JABFM, 34(1).

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Statistical Analysis of Diagnostic Pathology

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χ² analysis or Fisher’s exact tests were used to compare categorical data, and Mann-Whitney U test was used to compare continuous variables. Sensitivity and specificity were calculated using standard 2×2 contingency tables for cases with confirmed diagnostic pathology. All statistical analyses were performed using the SPSS Statistical software, V.26 (IBM, Armonk, NY) and statistical significance was defined as a P value of <.05.

Paniccia A., Polanco P.M., Boone B.A., Wald A.I., McGrath K., Brand R.E., Khalid A., Kubiliun N., O’Broin-Lennon A.M., Park W.G., Klapman J., Tharian B., Inamdar S., Fasanella K., Nasr J., Chennat J., Das R., DeWitt J., Easler J.J., Bick B., Singh H., Fairley K.J., Sarkaria S., Sawas T., Skef W., Slivka A., Tavakkoli A., Thakkar S., Kim V., Vanderveldt H.D., Richardson A., Wallace M.B., Brahmbhatt B., Engels M., Gabbert C., Dugum M., El-Dika S., Bhat Y., Ramrakhiani S., Bakis G., Rolshud D., Millspaugh G., Tielleman T., Schmidt C., Mansour J., Marsh W., Ongchin M., Centeno B., Monaco S.E., Ohori N.P., Lajara S., Thompson E.D., Hruban R.H., Bell P.D., Smith K., Permuth J.B., Vandenbussche C., Ernst W., Grupillo M., Kaya C., Hogg M., He J., Wolfgang C.L., Lee K.K., Zeh H., Zureikat A., Nikiforova M.N, & Singhi A.D. (2022). Prospective, Multi-Institutional, Real-Time Next-Generation Sequencing of Pancreatic Cyst Fluid Reveals Diverse Genomic Alterations That Improve the Clinical Management of Pancreatic Cysts. Gastroenterology, 164(1), 117-133.e7.

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Mental Health Risk Factors Among Students and Professionals

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Sample characteristics were reported with as percentages (%) for categorical data and mean (SD) for continuous data. Chi-square and Kruskal–Wallis tests were used to compare sample characteristics of students and working professionals. To determine risk factors for poor mental health, bivariate correlations and multivariable (adjusted) logistic regression models were conducted with binary outcome variables. These binary variables used standard cutoff values for anxiety (≥10) and perceived stress (≥6) (see 2.2.1. Mental Health Outcomes. Only statistically significant predictors in the correlation analyses were used in the multivariable models. A two-tailed test with a significance level of p < 0.05 was judged statistically significant. R software and SPSS statistical software (V 26) were used for all analyses.

Patwary M.M., Bardhan M., Disha A.S., Kabir M.P., Hossain M.R., Alam M.A., Haque M.Z., Billah S.M., Browning M.H., Kabir R., Swed S, & Shoib S. (2022). Mental Health Status of University Students and Working Professionals during the Early Stage of COVID-19 in Bangladesh. International Journal of Environmental Research and Public Health, 19(11), 6834.

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Comparing Emergency Department Attendance Trends

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We compared the patient attendance, characteristics, management and disposition variables across the three time periods defined above. Categorical variables were described using frequencies and percentages, while continuous data were presented using mean [standard deviation (SD)] or median [interquartile range (IQR)], depending on normality. Since the monthly data for chest pain attendance rates, cardiac enzyme usage and admission rates were non-parametric, we presented median (IQR), and three-way comparisons were analysed using Kruskal-Wallis test. Categorical variables were analysed using the Chi-square test or Fisher’s exact test, where appropriate. We used the SPSS statistical software v26 (Chicago) to perform the analysis. Statistical significance was taken at P<0.05.

Tan J.Z., Zhang D.Z., Sundararaghavan S., Ganapathy S., Choo J.T., Rajendram M.F, & Chong S.L. (2023). Chest pain attendances to a Paediatric Emergency Department pre- and post-COVID-19 vaccination. Translational Pediatrics, 12(11), 2010-2019.

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Fluoxetine Pharmacokinetics and Genetics

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Individual parameters (clearance and half‐life time) and plasma concentrations of fluoxetine and norfluoxetine were associated with clinical, anthropometric, and genetic information. Analysis of the continuous data using the Kolmogorov–Smirnov normality test showed that the data collected were non‐parametric data, and therefore their subsequent analysis was carried out through the Spearman´s correlation and Mann–Whitney U test.
The analysis of the data was performed using SPSS^® Statistical software v.26.

Sagahón‐Azúa J., Medellín‐Garibay S.E., Chávez‐Castillo C.E., González‐Salinas C.G., Milán‐Segovia R.D, & Romano‐Moreno S. (2021). Factors associated with fluoxetine and norfluoxetine plasma concentrations and clinical response in Mexican patients with mental disorders. Pharmacology Research & Perspectives, 9(5), e00864.

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