16-ASM-Causal-infer.Rmd

# (PART) 因果推斷 Causal Inference {-}



# Causal Languages 因果推斷的語法 {#grama-causal-infer}

> All models are wrong, but some are useful. 
> ~ George E. P. Box

```{block2, note-thankKarla, type='rmdnote'}
The Causal Inference lectures were orgainised and taught by Professor [Karla DiazOrdaz](https://scholar.google.com/citations?user=GSGcT-EAAAAJ&hl=en).
```

```{r ASM-causal-Session01, child = ('16-ASM-Causal-Infer/Session01.Rmd')}

```



# Graphical Models 因果推斷的圖形模型 {#graphical-models}

```{r ASM-causal-Session02, child = ('16-ASM-Causal-Infer/Session02.Rmd')}

```




# Regression Methods with continuous outcomes 結果變量爲連續型變量 {#reg-cont}



```{r ASM-causal-Session03, child = ('16-ASM-Causal-Infer/Session03.Rmd')}

```



# Regression Methods with binary outcomes 結果變量爲二進制變量  {#regre-binary}

```{r ASM-causal-Session04, child = ('16-ASM-Causal-Infer/Session04.Rmd')}

```

## Practical04 - causal inference

```{r ASM-causal-Practical04, child = ('16-ASM-Causal-Infer/Practical04.Rmd')}

```

# Prospensity Score 傾向性評分 {#prop-score}

## Practical05 - causal inference

```{r ASM-causal-Practical05, child = ('16-ASM-Causal-Infer/Practical05.Rmd')}

```

# Inverse probability weighted estimation and doubly robust methods 



# Causal mediation analysis