All statistical analyses were performed using SPSS statistical software for Windows, version 16. Student's t-test was used to compare the expression of ZNF545 in CRC tissues and adjacent normal tissues. The four table Chi-square test or the t-test were used to analyze categorical variables. A value of p<0.05 was considered statistically significant.
Spss statistical software for windows version 16
Manufactured by IBM
Sourced in United States
SPSS for Windows, version 16 is a statistical software package developed by IBM. The software is designed to analyze and manage data, providing users with a range of statistical tools and techniques for data analysis.
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Lab products found in correlation
13 protocols using spss statistical software for windows version 16
1
Expression Analysis of ZNF545 in CRC
2
Prelaminar Tissue Thickness in OAG Patients
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The data were analyzed using SPSS statistical software for Windows, version 16 (SPSS, Chicago, IL, USA). The data were tested for normal distribution using the Shapiro-Wilk test. One-way analysis of variance with a Bonferroni post hoc test was used to compare the clinical characteristics of OAG patients with or without type 2 diabetes and control subjects. Categorical parameters in baseline characteristics and the distribution of VF defects in each group were compared using the χ2 test. For the multiple comparisons, a Bonferroni correction was applied. To determine factors associated with the prelaminar tissue thickness in OAG patients, multivariate linear regression analyses were used. The dependent variable was the prelaminar tissue thickness. For multiple linear regression analyses, variables with P < 0.15 (presence of type 2 DM, disc area, and mean deviation) in univariate analyses were included in the multivariate model. A value of P < 0.05 was considered statistically significant.
3
Statistical Analysis of Radiographic Measurements
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Statistical analysis was performed using SPSS statistical software for Windows
Version 16 (SPSS Inc). The chi-square test compared ordinal or nominal variables
between the 2 groups. The normality of the distribution of variables was
determined via the Kolmogorov-Smirnov test. For variables with normal
distribution, parametric tests (independent t test) were used to compare the
mean radiographic measurements between the 2 groups. For variables with
non-normal distribution, nonparametric tests (U Mann-Whitney test) were used.
Multivariate logistic regression analysis was used to control confounding
variables. Variables with P < 0.15 in the univariate
analysis test were entered into a multivariate logistic regression analysis
using the backward selection method. The adjusted odds ratio (ORAdj) was used to
report the results. Statistical significance was set at P <
0.05.
Version 16 (SPSS Inc). The chi-square test compared ordinal or nominal variables
between the 2 groups. The normality of the distribution of variables was
determined via the Kolmogorov-Smirnov test. For variables with normal
distribution, parametric tests (independent t test) were used to compare the
mean radiographic measurements between the 2 groups. For variables with
non-normal distribution, nonparametric tests (U Mann-Whitney test) were used.
Multivariate logistic regression analysis was used to control confounding
variables. Variables with P < 0.15 in the univariate
analysis test were entered into a multivariate logistic regression analysis
using the backward selection method. The adjusted odds ratio (ORAdj) was used to
report the results. Statistical significance was set at P <
0.05.
4
Opportunistic Pathogen Infections in HIV/AIDS
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The data collected from both questionnaires and stool samples were keyed into Microsoft Excel 2007 (Microsoft Corporation) and analyzed using SPSS statistical Software for Windows version 16 (SPSS Inc.). The prevalence of each protozoan pathogenic infection was estimated using proportions. All statistical associations in this study were tested using Pearson chi-square test; p-value ≤ 0.05 was considered statistically significant. Multivariate-adjusted statistics at 95% confidence interval (CI) was used as robust statistics to confirm risk factors associated with the exposure of HIV/AIDS patients to opportunistic pathogens.
5
Evaluating Statistical Protocols for Data Analysis
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The data generated were expressed as mean± SD and performed using the SPSS statistical software for Windows (version 16; SPSS Inc., Chicago, IL, USA). The data were analyzed using One-way ANOVA and post-hoc test (Duncan Multiple Range Test). Values of (P ≤ 0.05) were considered significant.
6
Gingival Recession and Clinical Attachment Level Study
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The study power was calculated using PC-SIZE software (Dallal GE, Boston, MA, USA) considering the standard deviation of each group prior to the study. A difference of 1 mm in gingival recession and CAL between the groups was considered clinically significant. This analysis indicated that the study would have >80% power to detect a 1 mm difference in gingival recession and CAL for intergroup comparison with 18 subjects in each group (11) . SPSS statistical software for Windows, version 16 (SPSS Inc., Chicago, IL, USA) was used for data analysis, and Fisher exact test was used to analyze the qualitative variables in the three groups. Normality of data was analyzed by the Shapiro-Wilk test; normally distributed baseline and changes (Δ) data were analyzed by one-way ANOVA test, and intergroup pairwise comparisons were done using the Duncan test when statistically significant differences were found. The changes (Δ) in data, which were not normally distributed, were analyzed by Kruskal-Wallis test, and pairwise comparisons were done by Dunn test when statistically significant differences were found. Comparisons of normally distributed data within the groups were assessed by repeated measures ANOVA, and pairwise comparisons were done using the Bonferroni test. Furthermore, Friedman test and pairwise Dunn test were used for non-normally distributed variables.
7
Analyzing Statistical Significance in Research
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All data are expressed as the mean (X) ± standard deviation (SD). The chi-square test, analysis of variance (one-way ANOVA), Student's t-test, and the Mann–Whitney U test were performed using SPSS statistical software for Windows, version 16.0 (SPSS, Chicago, IL, USA). A P value < 0.05 was considered to be statistically significant.
8
Quantitative Data Analysis with SPSS
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Statistical analyses were performed using SPSS statistical software for Windows, version 16.0 (SPSS, Chicago, IL, USA). Values were expressed as the mean ± SD. Quantitative data in paired groups were determined using the Student’s t-test. One-way analysis of variance was performed for multiple group comparisons. A value of P < 0.05 indicated a significant difference.
9
Cardiac Function Improvement Analysis
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In this study, data are presented as a mean ± standard deviation with 95% confidence intervals. The significance of between‐group differences was analyzed using the unpaired Student's t test for continuous variables and the chi‐squared test for categorical variables. In addition, we analyzed the time‐course changes in the hemodynamic parameters using two‐way repeated measures analysis of variance. If significant changes were observed, we performed posthoc tests with Bonferroni‐adjusted pairwise comparisons. In addition, we performed the univariate and multivariate logistic regression analyses to assess variables associated with the cardiac function improvement. The variables with P < .100 in the univariate analysis were included in the multivariate analysis. Furthermore, receiver‐operating characteristic curve analyses were performed to assess the optimal cutoff values for estimating the cardiac function improvement following ablation. We considered P < .050 as statistically significant. Furthermore, statistical analysis was performed using SPSS statistical software for Windows version 16.0 (SPSS Inc., Chicago, IL).
10
Statistical Analysis of Experimental Data
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All data are expressed as the mean ± SD. Student's t test was used to determine significant differences between two sets of data, and one‐way analysis of variance was used for multiple comparisons using SPSS statistical software for Windows, version 16.0 (Chicago, Illinois). A value of P < .05 was considered statistically significant.
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