Multiple comparison one-way ANOVA test was performed to examine the significant differences between the biofilm cells-treated in the absence (controls) or presence of an iron chelator (DFO), and the percentage of cell viability (LIVE/DEAD) ratio. The Spearman’s correlation was computed to evaluate the relative gene expression between biofilm and CAZ biofilm-challenged cells using IBM SPSS statistical software [v19] (IBM Corp., USA); the p < 0.01 and 0.05 indicated a significant difference of cell viability levels, influence of DFO in biofilm, and the pattern of gene-correlated expression.
Spss statistical software v19
Manufactured by IBM
Sourced in United States
SPSS Statistical Software v19.0 is a comprehensive data analysis and statistical software package designed for a wide range of applications. It provides a suite of tools for data management, analysis, and reporting, enabling users to perform a variety of statistical procedures and generate customizable reports.
Automatically generated - may contain errors
Lab products found in correlation
20 protocols using spss statistical software v19
1
Biofilm Viability Analysis via ANOVA
2
Survival Analysis of Prognostic Factors
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Normally distributed continuous variables were presented as the mean with SD, and variables with a skewed distribution as the median with IQR. These variables were compared using the t test (two-tailed) and the Mann-Whitney U-test, respectively. Categorical variables were presented as numbers and percentages, and were compared using the χ2 test for trends. Cumulative event rates were estimated using the Kaplan-Meier method and compared using the log-rank test. Univariable and multivariable stepwise Cox proportional hazards regression models (with a p value=0.25 as a criterion to enter a variable into the model) were used to identify independent correlates of the 5-year outcome. All statistical analyses were performed using SPSS statistical software (V.19) (IBM, USA). If not prescribed, a p value less than 0.05 was considered to indicate statistical significance.
3
Reliability and Muscle Activation Analysis
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All data were coded and analyzed using the SPSS statistical software v19.0 (SPSS inc., USA). In order to establish the reliability of the test posture angles and reliability of muscle activation in the reference upright posture and the eight test postures, intraclass correlation coefficient (ICC (2,1)) was computed [24 (link)]. Repeated measures ANOVA was performed along with associated F-tests to allow calculation of the Standard Error of the Measurement (SEM) and to determine if there were significant differences in muscle activation between each of the paired movements. An alpha level of p < 0.05 was set to determine significance.
4
Statistical Analysis of Categorical and Continuous Data
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For categorical variables chi-square tests or the Fischer’s exact test were used as appropriate, and 2-sided significance values were evaluated. For continuous variables analysis was performed with the two sample t-test, after ensuring normal distribution of data. Data with no normal distribution were analyzed by Wilcoxon rank sum test. Continuous variables are presented as mean±standard deviation (SD) unless otherwise noted. P < 0.05 was considered statistically significant. All P-values above 0.10 are denoted NS (non-significant) in tables. Data entry and analysis was performed blinded to group allocation. All statistical analyses were performed using SPSS statistical software v.19.0 (SPSS inc, Chicago IL).
5
Statistical Analysis of Periodontitis Factors
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For continuous data, statistical differences were evaluated using Student’s t-test or the Mann-Whitney U test, depending on the data distribution. Categorical variables are presented as frequencies (per cent) and were analysed using the χ2 test. To determine whether any of the variables were independently related to periodontitis, a multivariate analysis of variables with a p value <0.05 in the univariate analysis was performed using linear logistic regression analysis. All statistical analyses were conducted using SPSS statistical software, V.19.0, and statistical significance was set at p<0.05 (two-sided).
6
Survival and Tumor Growth Analysis
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Differences between groups were evaluated by performing the unpaired t‐test. Each experiment was performed three times per group. The Kaplan–Meier method was used to calculate the cumulative survival time and differences in survival were analyzed with the log‐rank test. OS was defined as the interval between the start of the treatment and death. RFS was defined as the time from the day of surgery to the day of first recurrence or last follow‐up. Patients who died from other causes were considered to be censored with no event when calculating RFS. An unpaired t‐test was used to compare tumor growth between the groups. Data are presented as the mean ± SD (standard deviation). All data were analyzed with two‐tailed tests, with p <0.05 defining statistical significance. All statistical analyses were performed with statistical product and service solutions (SPSS) statistical software V19.0 (SPSS Inc., Chicago, IL, USA).
7
Quantitative and Qualitative Analysis of Clinical Data
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A descriptive analysis of the variables was performed using frequency analysis and measures of central tendency and dispersion for quantitative variables. Results were expressed as absolute numbers, percentages, mean and standard deviation.
Data processing and analysis were conducted using SPSS statistical software v. 19.0, Chi-square test was used to compare the variables. Alpha level was set at 0.05.
Qualitative data from clinical records were checked. These data were codified into category labels, and were then ordered into groups. Data were analyzed and compared; first within each category, and then between categories. The goal was to find links between them. To do such analysis, latent contents and context were taken into account.
The statement of the informants has been transcribed verbatim. These transcriptions have been filed separately from the text and in quotation marks.
Data processing and analysis were conducted using SPSS statistical software v. 19.0, Chi-square test was used to compare the variables. Alpha level was set at 0.05.
Qualitative data from clinical records were checked. These data were codified into category labels, and were then ordered into groups. Data were analyzed and compared; first within each category, and then between categories. The goal was to find links between them. To do such analysis, latent contents and context were taken into account.
The statement of the informants has been transcribed verbatim. These transcriptions have been filed separately from the text and in quotation marks.
8
Effects of Exercise Training on VO2 Peak
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Categorical data were presented in frequency and percentage. Numeric data were presented as mean±SD. Significance differences between pretraining and post-training in primary outcome, V̇O2 peak and secondary outcomes, such as MPO and blood markers, were determined using paired sample t-test. A two-tailed p value of <0.05 was considered statistically significant. Statistical analysis was performed with SPSS statistical software, V.19.0.
9
Survival Analysis and Tumor Growth Comparison
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Differences between groups were evaluated by performing the Unpaired T test. Each experiment was performed three times with 3–4 mice per group. The Kaplan-Meier method was used to calculate the cumulative survival time, and differences in survival were analyzed with the log-rank test. Overall survival (OS) was defined as the interval between the start of the treatment and death. Unpaired t-test was used to compare tumor growth between the groups. Data are presented as the mean ± SD (standard deviation). All data were analyzed with two-tailed tests, with P<0.05 considered to show statistical significance. All statistical analyses were performed with SPSS statistical software V19.0 (SPSS Inc., Chicago, IL, USA).
10
Dissolution Analysis of Drug Brands
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The data were analyzed with SPSS statistical software v19.0 [10] . Descriptive statistics such as mean SD, range, and percentage dissolution of the different brands in the three dissolution media, were obtained. To determine statistically significant differences in dissolution of drug brands in the different media, and the interaction between them, a 2-way analysis of variance was used. Multiple Range test (Fisher's LSD test) was applied to determine homogeneity in the dissolution media and the different drug brands. The significance level for each test was set at p < 0.05 and two tails. The coefficient of variation (% CV) was calculated to determine if samples of the buffer medium complied with the provisions of "Farmacopea de los Estados Unidos Mexicanos" (FEUM); CV ≤ 3 % [9].
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