Automated build.

Files changed:
M	.setup/build/semmcci.pdf
M	.setup/build/semmcci_1.1.4.9000.tar.gz
A	.setup/latex/bib/quarto.bib
M	.setup/latex/figures/pdf/cfa.pdf
M	.setup/latex/figures/pdf/kwan-2011-example-1.pdf
M	.setup/latex/figures/pdf/kwan-2011-example-2.pdf
M	.setup/latex/figures/pdf/kwan-2011-example-two-regressors.pdf
M	.setup/latex/figures/pdf/latent.pdf
M	.setup/latex/figures/pdf/regression.pdf
M	.setup/latex/figures/pdf/serial.pdf
M	.setup/latex/figures/pdf/simple.pdf
D	.setup/latex/pdf/.gitignore
D	.setup/latex/pdf/bib.bib
D	.setup/latex/pdf/semmcci-001-description.pdf
D	.setup/latex/pdf/semmcci-999-session.pdf
D	.setup/latex/pdf/semmcci-zzz-references.pdf
D	.setup/latex/pdf/semmcci-zzz-tests-benchmark.pdf
D	.setup/latex/pdf/semmcci-zzz-tests-external.pdf
D	.setup/latex/pdf/semmcci-zzz-tests-internal.pdf
D	.setup/latex/pdf/semmcci-zzz-tests-staging.pdf
M	README.md

.setup/latex/bib/quarto.bib

@@ -0,0 +1,11 @@
+@Article{Wright-1918,
+  author = {Sewall Wright},
+  date = {1918-07},
+  journaltitle = {Genetics},
+  title = {On the nature of size factors},
+  doi = {10.1093/genetics/3.4.367},
+  number = {4},
+  pages = {367--374},
+  volume = {3},
+  publisher = {Oxford University Press ({OUP})},
+}

README.md

@@ -83,12 +83,12 @@ library(lavaan)
 ``` r
 summary(df)
 #>        X                  M                  Y           
-#>  Min.   :-2.78083   Min.   :-3.66347   Min.   :-3.31635  
-#>  1st Qu.:-0.66337   1st Qu.:-0.58777   1st Qu.:-0.65206  
-#>  Median : 0.00892   Median : 0.02008   Median : 0.04507  
-#>  Mean   : 0.03152   Mean   : 0.01944   Mean   : 0.00918  
-#>  3rd Qu.: 0.71045   3rd Qu.: 0.67004   3rd Qu.: 0.62906  
-#>  Max.   : 3.66732   Max.   : 3.29521   Max.   : 3.27620  
+#>  Min.   :-3.43030   Min.   :-3.81719   Min.   :-3.17158  
+#>  1st Qu.:-0.60747   1st Qu.:-0.67350   1st Qu.:-0.65074  
+#>  Median : 0.03675   Median : 0.06059   Median : 0.03110  
+#>  Mean   : 0.04401   Mean   : 0.01307   Mean   : 0.02672  
+#>  3rd Qu.: 0.73892   3rd Qu.: 0.66442   3rd Qu.: 0.72955  
+#>  Max.   : 4.02046   Max.   : 2.92444   Max.   : 3.19471  
 #>  NA's   :100        NA's   :100        NA's   :100
 ```
 
@@ -128,18 +128,18 @@ mc <- MC(fit, R = 20000L, alpha = 0.05)
 mc
 #> Monte Carlo Confidence Intervals
 #>              est     se     R    2.5%  97.5%
-#> cp        0.2360 0.0315 20000  0.1747 0.2986
-#> b         0.5027 0.0307 20000  0.4420 0.5621
-#> a         0.5044 0.0284 20000  0.4485 0.5606
-#> X~~X      1.0135 0.0475 20000  0.9211 1.1078
-#> Y~~Y      0.5593 0.0272 20000  0.5056 0.6130
-#> M~~M      0.7097 0.0341 20000  0.6427 0.7763
-#> Y~1      -0.0015 0.0253 20000 -0.0511 0.0481
-#> M~1       0.0053 0.0282 20000 -0.0498 0.0606
-#> X~1       0.0297 0.0331 20000 -0.0352 0.0945
-#> indirect  0.2536 0.0210 20000  0.2133 0.2952
-#> direct    0.2360 0.0315 20000  0.1747 0.2986
-#> total     0.4896 0.0296 20000  0.4321 0.5480
+#> cp        0.2471 0.0295 20000  0.1899 0.3050
+#> b         0.4709 0.0277 20000  0.4162 0.5253
+#> a         0.5367 0.0295 20000  0.4790 0.5944
+#> X~~X      1.0690 0.0499 20000  0.9710 1.1668
+#> Y~~Y      0.5365 0.0259 20000  0.4855 0.5870
+#> M~~M      0.8177 0.0390 20000  0.7417 0.8939
+#> Y~1      -0.0027 0.0249 20000 -0.0514 0.0465
+#> M~1      -0.0040 0.0302 20000 -0.0634 0.0548
+#> X~1       0.0509 0.0341 20000 -0.0148 0.1182
+#> indirect  0.2527 0.0203 20000  0.2141 0.2932
+#> direct    0.2471 0.0295 20000  0.1899 0.3050
+#> total     0.4999 0.0278 20000  0.4454 0.5545
 ```
 
 ### Monte Carlo Confidence Intervals - Multiple Imputation
@@ -173,15 +173,15 @@ mcmi <- MCMI(fit, mi = mi, R = 20000L, alpha = 0.05, seed = 42)
 mcmi
 #> Monte Carlo Confidence Intervals (Multiple Imputation Estimates)
 #>             est     se     R   2.5%  97.5%
-#> cp       0.2372 0.0319 20000 0.1748 0.2990
-#> b        0.5011 0.0311 20000 0.4405 0.5622
-#> a        0.5027 0.0282 20000 0.4472 0.5583
-#> X~~X     1.0152 0.0481 20000 0.9214 1.1097
-#> Y~~Y     0.5584 0.0276 20000 0.5041 0.6117
-#> M~~M     0.7105 0.0335 20000 0.6448 0.7767
-#> indirect 0.2519 0.0209 20000 0.2119 0.2940
-#> direct   0.2372 0.0319 20000 0.1748 0.2990
-#> total    0.4891 0.0299 20000 0.4304 0.5481
+#> cp       0.2442 0.0295 20000 0.1864 0.3019
+#> b        0.4724 0.0278 20000 0.4178 0.5274
+#> a        0.5376 0.0294 20000 0.4798 0.5956
+#> X~~X     1.0689 0.0503 20000 0.9700 1.1671
+#> Y~~Y     0.5364 0.0264 20000 0.4850 0.5878
+#> M~~M     0.8191 0.0397 20000 0.7418 0.8961
+#> indirect 0.2539 0.0206 20000 0.2152 0.2959
+#> direct   0.2442 0.0295 20000 0.1864 0.3019
+#> total    0.4981 0.0276 20000 0.4436 0.5521
 ```
 
 ### Standardized Monte Carlo Confidence Intervals
@@ -194,30 +194,30 @@ passing the result of the `MC()` function or the `MCMI()` function to
 MCStd(mc, alpha = 0.05)
 #> Standardized Monte Carlo Confidence Intervals
 #>              est     se     R   2.5%  97.5%
-#> cp        0.2398 0.0315 20000 0.1783 0.3014
-#> b         0.4991 0.0282 20000 0.4425 0.5524
-#> a         0.5163 0.0252 20000 0.4656 0.5649
+#> cp        0.2574 0.0302 20000 0.1981 0.3163
+#> b         0.5034 0.0273 20000 0.4491 0.5566
+#> a         0.5230 0.0246 20000 0.4734 0.5697
 #> X~~X      1.0000 0.0000 20000 1.0000 1.0000
-#> Y~~Y      0.5697 0.0255 20000 0.5194 0.6197
-#> M~~M      0.7335 0.0260 20000 0.6809 0.7832
-#> indirect -0.0015 0.0195 20000 0.2196 0.2958
-#> direct    0.0054 0.0315 20000 0.1783 0.3014
-#> total     0.0295 0.0262 20000 0.4445 0.5473
+#> Y~~Y      0.5447 0.0248 20000 0.4952 0.5931
+#> M~~M      0.7264 0.0257 20000 0.6755 0.7759
+#> indirect -0.0027 0.0192 20000 0.2259 0.3009
+#> direct   -0.0038 0.0302 20000 0.1981 0.3163
+#> total     0.0492 0.0248 20000 0.4710 0.5680
 ```
 
 ``` r
 MCStd(mcmi, alpha = 0.05)
 #> Standardized Monte Carlo Confidence Intervals
 #>             est     se     R   2.5%  97.5%
-#> cp       0.2310 0.0320 20000 0.1787 0.3033
-#> b        0.5085 0.0281 20000 0.4423 0.5517
-#> a        0.4988 0.0250 20000 0.4648 0.5627
+#> cp       0.2476 0.0303 20000 0.1954 0.3136
+#> b        0.5257 0.0277 20000 0.4507 0.5595
+#> a        0.5279 0.0245 20000 0.4741 0.5699
 #> X~~X     1.0000 0.0000 20000 1.0000 1.0000
-#> Y~~Y     0.5709 0.0261 20000 0.5179 0.6201
-#> M~~M     0.7512 0.0257 20000 0.6834 0.7840
-#> indirect 0.2536 0.0194 20000 0.2185 0.2944
-#> direct   0.2310 0.0320 20000 0.1787 0.3033
-#> total    0.4846 0.0269 20000 0.4440 0.5492
+#> Y~~Y     0.5250 0.0250 20000 0.4958 0.5939
+#> M~~M     0.7213 0.0255 20000 0.6752 0.7752
+#> indirect 0.2775 0.0194 20000 0.2276 0.3030
+#> direct   0.2476 0.0303 20000 0.1954 0.3136
+#> total    0.5251 0.0248 20000 0.4694 0.5659
 ```
 
 ## Documentation