# Haibiostat

## 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.