Table 1

- Summary of type of statistical tests used for data analysis.

Descriptive Analysis	Frequency, percentage, mean, median, mode, range, standard deviation, and skewness of the data.
Bivariate analysis	a. T-test or Mann–Whitney U test depending on variables in the dataset, between a continuous and a dichotomous categorical variable. b. ANOVA or Kruskal–Walli’s test depending on variables in the dataset. In the case of ANOVA, a Post HOC ‘Scheffe/Tukey HSD’ test was also done for intergroup comparison of means. c. Chi-square test was done between two categorical variables. d. Correlation analysis: Spearmen or Pearson tests depending on variables in the dataset. e. Simple Linear Regression was done to find a linear relationship between two continuous variables.
Multivariate analysis	Multiple linear regression if the defined outcome was a continuous variable.

Descriptive Analysis

Frequency, percentage, mean, median, mode, range, standard deviation, and skewness of the data.

Bivariate analysis

a. T-test or Mann–Whitney U test depending on variables in the dataset, between a continuous and a dichotomous categorical variable.
b. ANOVA or Kruskal–Walli’s test depending on variables in the dataset. In the case of ANOVA, a Post HOC ‘Scheffe/Tukey HSD’ test was also done for intergroup comparison of means.
c. Chi-square test was done between two categorical variables.
d. Correlation analysis: Spearmen or Pearson tests depending on variables in the dataset.
e. Simple Linear Regression was done to find a linear relationship between two continuous variables.

Multivariate analysis

Multiple linear regression if the defined outcome was a continuous variable.

ANOVA: Analysis of variance, HSD: Honestly significant difference