Spss 24.0 version

Data were analyzed using SPSS 24.0 version statistical software (IBM Inc., Chicago, USA). Descriptive statistics (mean, standard deviation, frequencies and percentages) were used to describe the quantitative outcome variable (PPD, KTW), categorical outcome variables including (PI), (BOP), oral hygiene, Gingival color, consistency, and radiographic bone loss and other categorical study variables (age groups, gender, implant type, implant size, implant location, graft vs. none graft as well as graft type). In addition, oral hygiene status and KTW were evaluated. Student’s t-test for independent samples and one-way analysis of variance were used to compare the mean values of PPD in relation to the categorical study variables. Pearson’s Chi-square test was used to assess the association between the categorical study and outcome variables. Karl Pearson’s correlation coefficient was used to quantify the relationship between attached gingiva values and PPD scores. A p-value of < 0.05 was used to report the statistical significance of results.

Continuous data were presented as means (SDs) or medians (ranges) and interquartile range, as appropriate for each variable. Percentage change in size was calculated relative to the baseline estimated in ultrasound at diagnosis. A meaningful change in tumor size was defined as an increase greater than 3 mm from baseline before the initial fine-needle aspiration. The values obtained were compared using Chi² for categorical variables and a t test for comparison of two means for continuous variables with normal distribution. The statistical tests used to compare the differences between the groups were the Mann-Whitney U test for skewed variables and the Wilcoxon signed-rank test for paired skewed variables. All statistical analyses were conducted using SPSS, 24.0 version (IBM Corp).

Statistical Package for Social Sciences (SPSS) 24.0 version (IBM; Armonk, NY, USA; IBM–Corp) was used to carry out statistical analyses by α of 0.05 and statistically significant of p < 0.05 for a 95% confidence interval (CI).
Regarding quantitative data, the Shapiro–Wilk test was applied to determine normality distribution. Next, the Shapiro–Wilk test demonstrated parametric distribution if p ≥ 0.05. In addition, the Shapiro–Wilk test demonstrated non-parametric distribution if p < 0.05. All data were described as mean ± standard deviation (SD) and mean differences completed with their lower and upper limits for 95% CI, detailing the t statistic for parametric distribution and U statistic for non-parametric distribution.
According to between-group comparisons, p-values of the Student’s t-test for independent samples were used for parametric data according to Levene’s test for equality of variances. Furthermore, p-values of the Mann–Whitney U test for independent samples were used for non-parametric data. In addition, sex distribution was compared by the Fisher exact test. For outcome measurement differences after interventions, effect size was determined by the Cohen’s d and interpreted as very small effect size (d < 0.20), small effect size (d = 0.20–0.49), medium effect size (d = 0.50–0.79) and large effect size (d > 0.8) [34 (link)].