Features of outputs in the Area 3

Statistical results includes statistical tables and plots.

1. Statistical tables

Most tables in MEPHAS are shown by DT package.

• Tables are shown for Data Preview and display the Results

• The tables are easy to save and search numbers

2. Statistical plots

2.1. Three types of plots

Plots in MEPHAS are shown by ggplot2 package and plotly package. 2D ggolot, 2D plotly, and 3D plotly are used in MEPHAS. These plots are easy to save.

• Save ggolot2 plots: right click can save the plot as image

• Save 2D plotly plots: click the camera icon.

• Save 3D plotly plots: click the camera icon. 3D plots need some time to load.

3. The overview of statistical plots

3.1. 2D ggplot

• Distribution plot

3.2. 2D plotly

3.2.1. To plot distribution

• Histogram

• Density plot

• QQ plot

3.2.2. To plot descriptive statistics

• Box plot

• Mean and SD plot

3.2.2. To plot proportion

• Pie plot

• Bar plot

3.2.3. Plots in ANOVA

• Mean plot in line to show the marginal mean plot

3.2.4. Plots in Linear regression

• Scatter plot between 2 continuous variables

• Residuals plot

3.2.5. Plots in logistic regression

• Scatter plot between binary variable and continuous variable

• ROC plot

3.2.6. Plots in survival analysis

• Survival / Hazard plots

• Martingale residuals, deviance residuals, and Cox-snell residuals plot

• Integrated Brier score plot

• Time-dependent AUC plot

3.2.6. Plots in PCA and EFA

• Parallel analysis plot to decide the number of components

• Correlation matrix plot

3.2.6. Plots in PCA, EFA, PCR, PLSR, and SPLSR

• Component plot

• Loading plot

• Biplot for component and loading

3.3. 3D plotly

• 3D Scatter plot in linear regression

• 3D biplot in dimensional analysis