## Recently Published

##### Skin Tone Scale

Three different skin tone color scale applied in social/racial research

##### PGM - Factors

Factors - Why needed them?

##### PGM - Distributions

Distributions: Joint - Conditioning - Marginalization

##### Getting the individual probability from Gradient Boosting Models

Goal:
+ Fitting logistic model vs GBM
+ Extract the individual probability from GBM
+ Calculating the accuracy between logistic vs GBM
+ Comparing individual probability between 2 methods

##### ReadMe --- HaiBiostats' Portfolio

"Entertainment" Projects' Outline

##### Fundamentals of Bayes' Theorem

Demonstrate the degree of belief (prior) interfered/updated the evidence (likelihood) to produce a piece of new evidence (posterior)

##### Variance, Standard Deviation and Standard Error Confusion

Explanation of Var, SD and SEM

##### Creating model diagrams in JAGS/Stan model String process: a tool to draw

- Introducing an useful tool to draw diagrams

##### Scaling Back the Standardized Betas in JAGS

Converting Standardized Beta Coefficient Estimates to Raw Data Scale

##### Bayes' Analysis 7 - Part 2

- Simple linear regression
- Hierarchical regression

##### Bayes' Analysis 8 - Part 1

- Multiple regression

##### When fitting random-intercept vs. random slope mixed-effect regression model

- Question
- Review
- Answer

##### Bayes' Analysis 7 - Part 1

- Compare 2 groups without predictors
- FNP vs Bayes in comparison of groups

##### ANOVA in Bayes

ANOVA one-way, two-way

##### Bayes' Analysis 6

- Normal model for 1 group
- Robust estimation using t-distribution

##### Bayes' Analysis 5

Introducing to STAN

##### Beta distribution in an intuitive explanation

- Describe beta dist. in an intuitive way
- With some math formulas

##### Interaction - Power analyses

- Explain the meaning of interaction
- Power analysis to detect an interaction effect
- Simulation of the power

##### COVID-19 Vaccine efficacy

VE and 95% CI of VE

##### Cox Models - PH assumption - ML applied in SA

KM - Cox - PH assumption - Machine learning in Survival Analysis

##### Three Phases in Clinical Trials

A short review of Phases in Clinical Trials - easier to remember

##### stringi vs. stringr

How stringi evolved from stringr!

##### Gentle Introduction to Shiny

Basic Steps in Create an App with Shiny

##### Functions inside a function

Review a function structure - An applicant

##### Centile Estimation using GAMLSS

Centile estimation:
- Intro
- Fitting centile curves, Plotting, Diagnostics
- Prediction, Quantile sheets

##### Regular Expressions applying in the Text Mining

- Review regular expression and functions in R dealing with Text Mining
- Demonstrating the applications

##### The Evolution of Reshaping Data

From stats::reshape -- all kinds of tidyr function (gather, spread, separate, unite)

##### Introduction to Bootstrap and Some Examples

Bootstrap
Examples

##### ML - Probabilistic Model Selection with AIC, BIC

- The Challenge of Model Selection
- Probabilistic Model Selection
- Akaike Information Criterion
- Bayesian Information Criterion
- Minimum Description Length
- Examples

##### Probabilistic Graphical Models - Template Models for Bayesian Networks

Overview - Temporal Models (DBNs, HMMs) - Plate Models

##### Probabilistic Graphical Models - Bayesian Network: Fundamentals

Bayesian networks build on the same intuitions as the naive Bayes model by exploiting conditional independence properties of the distribution in order to allow a compact and natural representation. We look at the fundamental of BNs

##### ML - Classifying with Trees -- Decision Trees

What are decision trees?
Using the recursive partitioning algorithm to predict animal classes
An important weakness of decision trees

##### Adjustment for Baseline Response in Longitudinal Analysis

- Review 4/6 strategies in baseline response adjustment

##### Probability of Distribution in R

- Some distributions often meet in R
- Data.Frame example

##### ML - Factor Analysis applied in Multiple Linear Regression Context using R

- Scree plot in PCA and FA
- Run fa and factanal
- Applying fa$scores in mutiple regression analysis, dimension reduction process.