Rebuild under knitr 1.48

remlapmot · Jul 7, 2024 · 0e4ea9a · 0e4ea9a
1 parent e310bb4
commit 0e4ea9a
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Showing 45 changed files with 4,638 additions and 5,569 deletions.
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
@@ -24,15 +24,9 @@ plot(A, Y)
 summary(Y[A == 0])
 #>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 #>    10.0    27.5    60.0    67.5    87.5   170.0
-```
-
-``` r
 summary(Y[A == 1])
 #>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 #>    50.0   105.0   160.0   146.2   185.0   220.0
-```
-
-``` r
 
 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,
@@ -47,21 +41,12 @@ plot(A2, Y2)
 summary(Y2[A2 == 1])
 #>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 #>    40.0    47.5    65.0    70.0    87.5   110.0
-```
-
-``` r
 summary(Y2[A2 == 2])
 #>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 #>      30      45      60      80      95     170
-```
-
-``` r
 summary(Y2[A2 == 3])
 #>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 #>    50.0    95.0   120.0   117.5   142.5   180.0
-```
-
-``` r
 summary(Y2[A2 == 4])
 #>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 #>   150.0   187.5   205.0   195.0   212.5   220.0
@@ -107,15 +92,9 @@ summary(glm(Y3 ~ A3))
 #> AIC: 170.43
 #> 
 #> Number of Fisher Scoring iterations: 2
-```
-
-``` r
 predict(glm(Y3 ~ A3), data.frame(A3 = 90))
 #>      1 
 #> 216.89
-```
-
-``` r
 
 summary(glm(Y ~ A))
 #> 
@@ -168,9 +147,6 @@ summary(mod3)
 #> AIC: 170.39
 #> 
 #> Number of Fisher Scoring iterations: 2
-```
-
-``` r
 predict(mod3, data.frame(cbind(A3 = 90, Asq = 8100)))
 #>        1 
 #> 197.1269