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Spss statistics package v 25

Manufactured by IBM
Sourced in United States

SPSS Statistics Package v.25 is a comprehensive software suite used for statistical analysis. It provides a wide range of statistical procedures, data management tools, and visualization options to help users analyze and interpret data. The software is designed to handle a variety of data types and can be used for a wide range of applications, including market research, social sciences, and scientific research.

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Lab products found in correlation

3 protocols using spss statistics package v 25

1

Predictors of Infection in Fracture Patients

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Descriptive statistics were used for demographics. Normality of the data was
evaluated with the Shapiro–Wilk test. For normally distributed data, mean  ±  SD was presented, while for skewed data, median  ±  interquartile
range (IQR) was used. T  test was utilised for comparing groups of normally
distributed data and the non-parametric Mann–Whitney U  test otherwise. Chi-squared test was used for categorical data analysis. Regression analysis was
used for testing the hypothesis of whether infection had an effect on Barthel
index score. Except infection, the variables tested included age, sex,
smoking, dementia, diabetes mellitus, previous accommodation, previous
mobilisation status, use of anti-coagulants, haemoglobin, albumin, ASA score,
fracture type, method of fixation, length of stay, operative time and waiting
time until surgery. Finally, logistic regression analysis was employed for
the search of any predisposing factors to infection among the same
variables. SPSS statistics package v.25 (IBM, Armonk, New York, USA) was used for statistical
analyses.
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2

Preoperative and Postoperative Knee Scores

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Statistical analysis was performed using SPSS Statistics Package v. 25 (IBM, USA). Paired t-tests were used for parametric continuous data, with two tailed p-values reported and statistical significance set at p < 0.05, with 95% confidence intervals. Preoperative, two-year postoperative, and five-year postoperative AKSS and OKS scores were compared using the paired t-tests (following Shapiro-Wilk test of normality) to identify significant differences.
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3

Comparing Alignment Distributions in Healthy and Arthritic Groups

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Scatterplots for each population were created to demonstrate alignment distributions for healthy and arthritic groups. Normality of data distribution was assessed for continuous variables using Shapiro-Wilk test and Q-Q plots. An independent-samples t-test was used to compare differences in means for normally distributed data and Mann-Whitney U test for non-parametric data. The chi-squared test and Fisher’s exact test were used for categorical data analysis. Statistical significance was set at a p-value ≤ 0.05. Statistical analyses were performed using XLSTAT v22.3.1 (Addinsoft, New York, New York, USA) and SPSS Statistics Package v.25 (IBM, Armonk, New York, USA).
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