Continuous variables are expressed as mean ± standard deviation (SD) and compared using Student’s t test. Categorical variables are expressed as percentages and compared using the Chi-squared test. The CCI and other comorbidities were used as independent variables. Binary logistic regression models were used to examine the relationship of CCI with complications, surgical choice, time-to-surgery, transfusion, anti-coagulation, analgesia, and complications after hip fractures. Linear regression analysis was performed to examine the relationship of length of hospital stay and hospital expenses with CCI, age-adjusted CCI, osteoporosis, and hypertension. The results are presented as crude and adjusted regression coefficients and 95% confidence intervals, standardized coefficients, and P values. All statistical tests of significance were two-tailed, and P values < 0.05 were considered statistically significant. Statistical analyses were performed using SPSS 16.0 statistics software (SPSS Inc. Chicago, IL, USA).
Spss 16.0 statistics software
Manufactured by IBM
Sourced in United States
SPSS 16.0 is a statistical software package developed by IBM. It is designed to perform a wide range of data analysis and statistical tests, including descriptive statistics, regression analysis, and hypothesis testing. The software provides a user-friendly interface and a comprehensive set of tools for data management, visualization, and analysis.
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Lab products found in correlation
15 protocols using spss 16.0 statistics software
1
Hip Fracture Management Outcomes
2
Analyzing ALK Status Impact
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The relationship between ALK status and the clinicopathologic features was analyzed by using Chi square test and Fisher’s exact test. Kaplan–Meier curves with the log-rank test were applied for OS and PFS analysis. Cox proportional hazards models were used to compare independent predictive factors of each biological and clinicopathologic feature. A two-sided statistical significance was defined as P < 0.05. All analyses were performed with SPSS 16.0 Statistics software (SPSS Inc., Chicago, IL, USA).
3
Statistical Analysis of Patient Characteristics
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Descriptive statistics were calculated for patients' characteristics using mean, standard deviation, and percentages. All statistical data were performed using the SPSS 16.0 statistics software.
4
One-Way ANOVA Statistical Analysis
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Results were presented as the mean ± standard error of the mean (SEM). SPSS 16.0 statistics software (SPSS Inc., Chicago, IL, USA) was used for statistical analyses. Statistically significant differences were determined by one-way ANOVA followed by Tukey's multiple comparisons test. The significance threshold was set at P < 0.05.
5
Statistical Analysis of Prognostic Factors
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Statistical analysis consisted of Fisher’s exact test, the Chi-square test, and the Student’s t-test (comparison of means). The Kaplan-Meier method with a log-rank test was used to estimate OS. The Cox proportional hazards model was used to compare independent prognostic factors of biological and clinicopathological features. Two-sided statistical significance was defined as p < 0.05. All analyses were performed with SPSS 16.0 statistics software (SPSS Inc., Chicago, IL).
6
Repeated Experiments with Statistical Analysis
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All experiments were repeated three times and similar results were obtained. Statistical analysis was performed using the SPSS 16.0 statistics software (SPSS, Chicago, IL). Data were expressed as mean ±standard deviation (SD). Statistical analysis was performed using ANOVA and followed by the Student-Newman-Keuls post hoc tests or Student't test (two means comparison). P value of less than 0.05 was considered statistically significant.
7
Statistical Analysis of Experimental Data
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The analysis of variance (ANOVA) was conducted by using the SPSS 16.0 statistics software (SPSS Inc., Chicago, IL, USA). And the related data and graphs were processed by the software of Microsoft Office Excel (2019) and Origin (2018). All experiments were conducted in triplicate.
8
Statistical Analysis of Cell Viability and Survival Outcomes
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SPSS 16.0 statistics software (SPSS, Inc.) was employed for statistical analysis. To compare the mean or median of each group with that of the control group, the Mann-Whitney U-test was used. Data from the cell viability assay and clonogenic assay were examined using analysis of variance (ANOVA). If statistical significance of a treatment effect was obtained using ANOVA, Tukey's multiple-comparisons test was applied to determine the difference between treatment groups. To evaluate the associations between UBE2B expression and various clinicopathological variables, the χ2 test or Fisher's exact test was performed, depending on the group size. For the patient cohort, the following three endpoints were calculated: Disease-specific survival (DSS), distant metastasis-free survival (DMeFS), and local recurrence-free survival (LRFS), which were determined from the start date of the radiotherapy to the onset of an event. The Kaplan-Meier method with the log-rank test was applied to compare survival between groups. For multivariate analysis of factors influencing survival, linear logistic regression with the Cox proportional hazards model was applied. Two-sided tests were used for all analyses and P<0.05 was considered to indicate statistical significance.
9
Statistical Analysis of Continuous and Categorical Variables
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One-way analysis of variance (ANOVA) was used to evaluate differences in continuous variables among multiple groups. The Student's t test or Mann–Whitney nonparametric U test was used to evaluate differences in continuous variables between the two groups. The χ2 test or Fisher's exact test was used to compare the distributions of categorical variables. Variables with P values <.05 in univariate analyses were entered into a multivariate logistic regression analysis. All data analyses were performed using the SPSS 16.0 statistics software (Chicago, IL). P < .05 was considered statistically significant.
10
Data Collection and Analysis in Excel and SPSS
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Data collection was performed using Microsoft Excel 2011, and descriptive statistical analysis was performed using SPSS 16.0 statistics software (SPSS, Inc., Chicago, IL, USA).
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