Spss v22.0 software for windows

Manufactured by IBM

Sourced in United States

SPSS v22.0 for Windows is a statistical analysis software package developed by IBM. It provides a comprehensive set of tools for data manipulation, analysis, and visualization. The software is designed to help users explore, analyze, and present data effectively.

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SPSS Statistics V22.0 software for Windows SPSS V22.0 statistical software for Windows SPSS v22 for Windows SPSS for Windows software SPSS software for Windows SPSS software v22.0 SPSS for Window SPSS v22 SPSS (SPSS v22.0, Windows SPSS software

5 protocols using spss v22.0 software for windows

Surgical Fixation Rate Comparison

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Sample size calculation was determined by the pre-experimental results and our clinical experience. The SFR in the treatment group and control group were expected to be 87 and 73%, respectively. With a two-tailed of 0.05 and a (1 − β) of 0.80, we calculated the sample size by power analysis. This yielded a total sample of 275 patients, after considering a 10% dropout or missed follow-up patients. Finally, we expanded the sample size to 300 to compare the differences between the groups.
SPSS v.22.0 software for Windows (IBM Corp., Armonk, NY, United States) was used for statistical analysis. Categorical variables were analyzed using the Chi-square test and continuous variables were analyzed using the Student’s test. In all tests, p < 0.05 was considered to indicate a significant difference.

Li Y, & Lv J. (2023). Effect of external physical vibration lithecbole in obese patients with lower pole stones <15 mm after ESWL: a single-centre, randomized, open label clinical trial. Frontiers in Medicine, 10, 1101811.

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Factors Influencing COVID-19 Vaccine Acceptance

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Statistical analysis was performed using IBM SPSS v22.0 software for Windows with a significance level determined at p < 0.05. Chi-squared (χ²) test was used to analyze associations between categorical variables and univariate analysis was used to assess the possible association between beliefs about SARS-CoV-2 origin and vaccine acceptance with different covariates that include: age, sex, educational level, residence, relationship status and monthly income. Multinomial regression analysis was used to eliminate possible confounding factors in the assessment of COVID-19 vaccine acceptance, COVID-19 vaccine uptake and their predictors.

Lounis M., Abdelhadi S., Rais M.A., Bencherit D, & Sallam M. (2022). Intention to get COVID-19 vaccination and its associated predictors: A cross-sectional study among the general public in Algeria. Vacunas (English Edition), 23, S52-S59.

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Factors Influencing COVID-19 Vaccine Acceptance

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Statistical Analysis of Experimental Data

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Statistical analysis was performed using SPSS software v22.0 for Windows (IBM Corp., Armonk, NY, USA). Results are expressed as the mean ± standard deviation (SD) of three independent experiments. Data were subjected to one-way analysis of variance, and the significant differences between samples were calculated using Duncan’s multiple range test. Differences were considered statistically significant at p < 0.05.

Bhardwaj M., Cho H.J., Paul S., Jakhar R., Khan I., Lee S.J., Kim B.Y., Krishnan M., Khaket T.P., Lee H.G, & Kang S.C. (2017). Vitexin induces apoptosis by suppressing autophagy in multi-drug resistant colorectal cancer cells. Oncotarget, 9(3), 3278-3291.

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Statistical Analysis of Experimental Data

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Statistical analysis was performed using SPSS software v22.0 for Windows (IBM Corp., Armonk, NY, USA). All results were expressed as mean ± standard deviation. Statistical significance was tested by Student’s t-test. Values were considered significant when p-value is lower than 0.05.

Carev I, & Sarikurkcu C. (2021). LC-MS/MS Profiles and In Vitro Biological Activities of Extracts of an Endemic Species from Turkey: Stachys cretica ssp. anatolica. Plants, 10(6), 1054.

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