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remlapmot · Mar 2, 2024 · 2b17c26 · 2b17c26
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diff --git a/data/fig1.dta b/data/fig1.dta
diff --git a/data/fig2.dta b/data/fig2.dta
diff --git a/data/fig3.dta b/data/fig3.dta
diff --git a/data/nhefs-formatted.dta b/data/nhefs-formatted.dta
diff --git a/data/nhefs-highprice.dta b/data/nhefs-highprice.dta
diff --git a/data/nhefs-ps.dta b/data/nhefs-ps.dta
diff --git a/data/nhefs-wcens.dta b/data/nhefs-wcens.dta
diff --git a/data/nhefs_std.dta b/data/nhefs_std.dta
diff --git a/data/nhefs_std1.dta b/data/nhefs_std1.dta
diff --git a/data/nhefs_std2.dta b/data/nhefs_std2.dta
diff --git a/data/nhefs_surv.dta b/data/nhefs_surv.dta
diff --git a/data/observe.mmat b/data/observe.mmat
diff --git a/docs/11-why-model-r.md b/docs/11-why-model-r.md
@@ -22,11 +22,11 @@ plot(A, Y)
 
 ```r
 summary(Y[A == 0])
-##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-##    10.0    27.5    60.0    67.5    87.5   170.0
+#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
+#>    10.0    27.5    60.0    67.5    87.5   170.0
 summary(Y[A == 1])
-##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-##    50.0   105.0   160.0   146.2   185.0   220.0
+#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
+#>    50.0   105.0   160.0   146.2   185.0   220.0
 
 A2 <- c(1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4)
 Y2 <- c(110, 80, 50, 40, 170, 30, 70, 50, 110, 50, 180,
@@ -39,17 +39,17 @@ plot(A2, Y2)
 
 ```r
 summary(Y2[A2 == 1])
-##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-##    40.0    47.5    65.0    70.0    87.5   110.0
+#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
+#>    40.0    47.5    65.0    70.0    87.5   110.0
 summary(Y2[A2 == 2])
-##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-##      30      45      60      80      95     170
+#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
+#>      30      45      60      80      95     170
 summary(Y2[A2 == 3])
-##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-##    50.0    95.0   120.0   117.5   142.5   180.0
+#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
+#>    50.0    95.0   120.0   117.5   142.5   180.0
 summary(Y2[A2 == 4])
-##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-##   150.0   187.5   205.0   195.0   212.5   220.0
+#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
+#>   150.0   187.5   205.0   195.0   212.5   220.0
 ```
 
 
@@ -74,47 +74,47 @@ plot(Y3 ~ A3)
 ```r
 
 summary(glm(Y3 ~ A3))
-## 
-## Call:
-## glm(formula = Y3 ~ A3)
-## 
-## Coefficients:
-##             Estimate Std. Error t value Pr(>|t|)    
-## (Intercept)  24.5464    21.3300   1.151 0.269094    
-## A3            2.1372     0.3997   5.347 0.000103 ***
-## ---
-## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
-## 
-## (Dispersion parameter for gaussian family taken to be 1944.109)
-## 
-##     Null deviance: 82800  on 15  degrees of freedom
-## Residual deviance: 27218  on 14  degrees of freedom
-## AIC: 170.43
-## 
-## Number of Fisher Scoring iterations: 2
+#> 
+#> Call:
+#> glm(formula = Y3 ~ A3)
+#> 
+#> Coefficients:
+#>             Estimate Std. Error t value Pr(>|t|)    
+#> (Intercept)  24.5464    21.3300   1.151 0.269094    
+#> A3            2.1372     0.3997   5.347 0.000103 ***
+#> ---
+#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
+#> 
+#> (Dispersion parameter for gaussian family taken to be 1944.109)
+#> 
+#>     Null deviance: 82800  on 15  degrees of freedom
+#> Residual deviance: 27218  on 14  degrees of freedom
+#> AIC: 170.43
+#> 
+#> Number of Fisher Scoring iterations: 2
 predict(glm(Y3 ~ A3), data.frame(A3 = 90))
-##      1 
-## 216.89
+#>      1 
+#> 216.89
 
 summary(glm(Y ~ A))
-## 
-## Call:
-## glm(formula = Y ~ A)
-## 
-## Coefficients:
-##             Estimate Std. Error t value Pr(>|t|)   
-## (Intercept)    67.50      19.72   3.424  0.00412 **
-## A              78.75      27.88   2.824  0.01352 * 
-## ---
-## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
-## 
-## (Dispersion parameter for gaussian family taken to be 3109.821)
-## 
-##     Null deviance: 68344  on 15  degrees of freedom
-## Residual deviance: 43538  on 14  degrees of freedom
-## AIC: 177.95
-## 
-## Number of Fisher Scoring iterations: 2
+#> 
+#> Call:
+#> glm(formula = Y ~ A)
+#> 
+#> Coefficients:
+#>             Estimate Std. Error t value Pr(>|t|)   
+#> (Intercept)    67.50      19.72   3.424  0.00412 **
+#> A              78.75      27.88   2.824  0.01352 * 
+#> ---
+#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
+#> 
+#> (Dispersion parameter for gaussian family taken to be 3109.821)
+#> 
+#>     Null deviance: 68344  on 15  degrees of freedom
+#> Residual deviance: 43538  on 14  degrees of freedom
+#> AIC: 177.95
+#> 
+#> Number of Fisher Scoring iterations: 2
 ```
 
 ## Program 11.3
@@ -128,26 +128,26 @@ Asq <- A3 * A3
 
 mod3 <- glm(Y3 ~ A3 + Asq)
 summary(mod3)
-## 
-## Call:
-## glm(formula = Y3 ~ A3 + Asq)
-## 
-## Coefficients:
-##             Estimate Std. Error t value Pr(>|t|)  
-## (Intercept) -7.40688   31.74777  -0.233   0.8192  
-## A3           4.10723    1.53088   2.683   0.0188 *
-## Asq         -0.02038    0.01532  -1.331   0.2062  
-## ---
-## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
-## 
-## (Dispersion parameter for gaussian family taken to be 1842.697)
-## 
-##     Null deviance: 82800  on 15  degrees of freedom
-## Residual deviance: 23955  on 13  degrees of freedom
-## AIC: 170.39
-## 
-## Number of Fisher Scoring iterations: 2
+#> 
+#> Call:
+#> glm(formula = Y3 ~ A3 + Asq)
+#> 
+#> Coefficients:
+#>             Estimate Std. Error t value Pr(>|t|)  
+#> (Intercept) -7.40688   31.74777  -0.233   0.8192  
+#> A3           4.10723    1.53088   2.683   0.0188 *
+#> Asq         -0.02038    0.01532  -1.331   0.2062  
+#> ---
+#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
+#> 
+#> (Dispersion parameter for gaussian family taken to be 1842.697)
+#> 
+#>     Null deviance: 82800  on 15  degrees of freedom
+#> Residual deviance: 23955  on 13  degrees of freedom
+#> AIC: 170.39
+#> 
+#> Number of Fisher Scoring iterations: 2
 predict(mod3, data.frame(cbind(A3 = 90, Asq = 8100)))
-##        1 
-## 197.1269
+#>        1 
+#> 197.1269
 ```