Data are presented as mean ± standard deviation (SD) values. All statistical analyses were performed using the Mann–Whitney U-test with SPSS software (version 14.0; SPSS Inc.; Chicago, IL, USA). A probability value of <0.05 was considered to be statistically significant.
Spss software version 14
Manufactured by IBM
Sourced in United States
SPSS software version 14.0 is a statistical analysis tool that allows users to manage, analyze, and visualize data. It provides a comprehensive set of features for data manipulation, regression analysis, and statistical modeling.
Automatically generated - may contain errors
86 protocols using spss software version 14
1
Nonparametric Analysis of Experimental Data
2
Statistical Analysis of Clinical Variables
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Continuous variables are expressed as the mean±SD or medians (min-max) in the presence of abnormal distributions, and categorical variables are expressed as percentages. Comparisons between groups of patients were performed using the χ2 test for categorical variables, independent samples t test for normally distributed continuous variables, and Mann-Whitney U test when the distribution was skewed. Correlations were evaluated using the Spearman correlation test. The Kruskal-Wallis test was used for comparison of enzyme levels according to the length of hospital stay. All statistical procedures were performed using SPSS software version 14.0 (SPSS Inc., Chicago, IL, USA). A p-value of 0.05 was considered significant.
3
Predictors of Major Bleeding and Pacemaker Hematoma
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Continuous variables were expressed as mean ± standard deviation or median (min-max) in the presence of abnormal distribution, and categorical variables as percentages. Comparisons between groups of patients were made by use of a χ2 test for categorical variables, independent samples t test for normally distributed continuous variables, and Mann-Whitney U test when the distribution was skewed. We used univariate logistic regression analysis to quantify the association of variables with occurrence major bleeding and PH. Age, presence of LV thrombus, history of recent stent implantation, spironolactone use, periprocedural warfarin use, periprocedural warfarin plus DAPT use, ICD device implantation, three lead implantation, and topical TXA use during CIED implantation were entered into the multivariate logistic regression model for determining the independent predictors of PH. Hypertension, history of recent stent implantation, spironolactone use, periprocedural warfarin use, periprocedural warfarin plus DAPT use, and topical TXA use during implantation were entered into the multivariate logistic regression model in order to determine the independent predictors of MBC. All statistical procedures were performed using SPSS software version 14.0 (SPSS Inc., Chicago, IL). A p value of 0.05 was considered as statistically significant.
4
Statistical Analysis of Categorical and Continuous Data
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Categorical data were presented as number and percentage and analyzed using Chi-Square test or Fisher's exact test as appropriate. Continuous data were presented as mean ± standard deviation (SD) and compared using the unpaired Student's t-test. A two-sided P < 0.05 was considered statistically significant. The analyses were performed using the SPSS software version 14.0 (SPSS, Inc., Chicago, IL, USA).
5
Predictors of Colonoscopy Reporting Failure
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Data are reported as numbers of cases (%) or as medians with interquartile ranges. For comparisons of categorical variables, Fisher exact test and the chi-square test were used. Differences in continuous variables were assessed with the Mann-Whitney test. Bonferroni's correction was performed when there were multiple comparisons. To determine the independent predictive factors for failure to use a colonoscopy reporting system, a logistic regression analysis was performed using variables for which statistically significant associations were identified in a univariate analysis. A two-tailed P-value <0.05 was considered statistically significant. SPSS software version 14.0 (SPSS Inc., Chicago, IL, USA) was used for the statistical analysis.
6
Gemcitabine Pharmacogenomics: SNP-SNP Interactions
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SNP-SNP interactions of 21 non-synonymous SNPs in 9 genes involved in gemcitabine transport, metabolism and activity were deduced in silico as reported previously [12 (link)]. Briefly, Fisher’s exact probability test was used to show that POLA + 1747 GG/GA SNP (rs487989) was the most statistically significant SNP to be associated with mortality. Chi-squared test was employed to assess the association between POLA + 1747 GG/GA SNP and SLC28A2 + 65 CC SNP, which confirmed that this SNP pair gave the best survival outcome [12 (link)]. All statistical tests were two-sided and performed using SPSS software version 14.0 (SPSS Inc., Chicago, IL). Differences were considered statistically significant when the p-value was less than 0.05.
7
Factors Influencing Inpatient Expenditure
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The variables we collected include gender, age, therapeutic effects, treatments, CCs, admission condition, and followed up situation of the patients. Single-factor analysis and multiple linear regression method were used to select and group the variables.[10 (link)] Since the dependent variable (inpatient medical expenditure) is not subject to normal distribution (Z = 0.69, P < 0.001), Kruskal-Wallis test (nonparametric statistical analysis) was used in single-factor analysis, and multiple linear stepwise regression analysis was carried out after the conversion of hospitalization expense by square root data.[11 (link)] All the data and material collected were entered into Excel 2010 software for Microsoft (Microsoft Corporation, Washington, USA), and statistical analyses were performed using SPSS software version 14.0 (SPSS Inc., Chicago, IL, USA).
8
Randomized, Blinded Hepatic Failure Trial
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With the aid of SPSS software (version: 14.0) (SPSS Institute, Anhui Medical University, Hefei, China), permuted-block randomization was carried out based on a computer system that used an allotment list to produce random numbers (in a 1-to-1 ratio). This was carried out by a statistician who was not a member of the research team to maintain the integrity and blinding of the research. The outcomes of the random sampling process were enclosed in prenumbered envelopes and kept at the location of the research until the study’s conclusion was reached. The study medicines were delivered by a research nurse following the random assignment sequence. Both the research participants and the patients were unaware of which medicine was being applied in the trial. In the event of an emergency, such as acute hepatic failure, 2 experts might recommend that the treatment allotment be unmasked and that the study medicine be adjusted or discontinued if needed, according to the protocol. All of the occurrences were recorded in detail. Then, we acquired information on the patient’s demographics, medical histories, and pertinent investigation findings.
9
Comparative Statistical Analysis of Experimental Data
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Data were expressed as mean ± standard deviation (SD). Statistical differences among groups were compared using one-way ANOVA and post hoc test with the aid of SPSS software, version 14.0 (SPSS Inc. Chicago, IL, USA).
10
Survival Analysis of Recurrent Disease
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Comparisons between the two groups for categorical variables were analyzed using the chi-square test or Fisher's exact test. Survival rates were estimated using the Kaplan-Meier method, and survival distributions between the two groups were compared using log-rank tests. A Cox proportional hazards model was used to determine which risk factors had an independent effect on survival after recurrence. P ≤ 0.05 was considered statistically significant. Statistical analyses were conducted using SPSS software, version 14.0 (SPSS Inc., Chicago, IL, USA) and R (version 2.12.0: www.r-project.org ).
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