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Spss for statistics

Manufactured by IBM

SPSS for Statistics is a software package used for statistical analysis. It provides a comprehensive set of tools for data management, analysis, and reporting. The core function of SPSS is to enable users to perform a wide range of statistical techniques, including descriptive statistics, correlations, regression analysis, and hypothesis testing.

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Lab products found in correlation

2 protocols using spss for statistics

1

Predictors of Reduced IKDC Scores in Revision ACLR

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Statistical analysis was performed using SPSS for Statistics (Version 29; IBM). For continuous variables the mean ± SD was used. The mean differences among the 3 SSD groups (<3, 3-5, ≥6 mm) were compared with the Kruskal-Wallis test, with the Dunn test for comparison of ≥2 groups and for nonnormally distributed parameters due to nonnormal distribution of the values. Categorical parameters were compared using the chi-square test. In case of small subgroups (n < 5), the Fisher exact text was used for categorical parameters. A P value of <.05 was considered significant.
In addition, we performed multiple linear regression analysis to identify predictors for reduced postoperative IKDC score after revision ACLR, including SSD of 3 to 5 mm, SSD ≥6 mm, body mass index (BMI), and medial meniscal lesions. Medial meniscal lesion and obesity were chosen as independent variables in the multiple linear regression analysis, as they are proven in the literature to be related to a worse functional outcome.4 (link)
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2

Clinical Data Collection and Analysis

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A structured questionnaire was used to collate the clinical information. Study data were collected and managed using REDCap electronic data capture tools hosted at the University of Nebraska Medical Center [19 (link)]. IBM SPSS for statistics was used for data analysis. Dichotomous variables were analyzed using χ2 or χ2 for trend tests [20 ].
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