Results: Confidence Intervals - Multivariate Normal - Data Missing Completely at Random

Ivan Jacob Agaloos Pesigan

2020-10-16

library(jeksterslabRmedsimple)
data(results_mvn_mcar_mc.mvn_ci, package = "jeksterslabRmedsimple")
data(results_mvn_mcar_nb.fiml_ci, package = "jeksterslabRmedsimple")
data(results_mvn_nb_ci, package = "jeksterslabRmedsimple")
data(results_mvn_sem_mc.mvn_ci, package = "jeksterslabRmedsimple")
results_mcar_ci <- rbind(
  results_mvn_mcar_mc.mvn_ci,
  results_mvn_mcar_nb.fiml_ci
)
results_mcar_10_ci <- results_mcar_ci[which(results_mcar_ci$missing == "MCAR.10"), ]
results_mcar_20_ci <- results_mcar_ci[which(results_mcar_ci$missing == "MCAR.20"), ]
results_mcar_30_ci <- results_mcar_ci[which(results_mcar_ci$missing == "MCAR.30"), ]
results_mcar_10_ci <- results_mcar_10_ci[which(results_mcar_10_ci$n > 20), ]
results_mcar_20_ci <- results_mcar_20_ci[which(results_mcar_20_ci$n > 20), ]
results_mcar_30_ci <- results_mcar_30_ci[which(results_mcar_30_ci$n > 20), ]
results_mcar_ci <- results_mcar_ci[which(results_mcar_ci$n > 20), ]
# results_mcar_power_ci <- rbind(
#  results_mcar_ci,
#  results_mvn_sem_mc.mvn_ci,
#  results_mvn_nb_ci
# )
results_mcar_power_ci <- results_mcar_ci[which(results_mcar_ci$n > 20 & results_mcar_ci$n < 150), ]

Plots

alpha 0.05

mcar

width <- 11.7
height <- 8.3
cairo_pdf("mcar-type1.pdf", width = width, height = height)
plot_type1(results_mcar_ci)
#> Warning: The shape palette can deal with a maximum of 6 discrete values because
#> more than 6 becomes difficult to discriminate; you have 9. Consider
#> specifying shapes manually if you must have them.
#> Warning: Removed 672 rows containing missing values (geom_point).
dev.off()
#> agg_png 
#>       2
cairo_pdf("mcar-power.pdf", width = width, height = height)
plot_power(results_mcar_power_ci)
#> Warning: The shape palette can deal with a maximum of 6 discrete values because
#> more than 6 becomes difficult to discriminate; you have 9. Consider
#> specifying shapes manually if you must have them.
#> Warning: Removed 279 rows containing missing values (geom_point).
dev.off()
#> agg_png 
#>       2
cairo_pdf("mcar-miss.pdf", width = width, height = height)
plot_miss(results_mcar_ci)
#> Warning: The shape palette can deal with a maximum of 6 discrete values because
#> more than 6 becomes difficult to discriminate; you have 9. Consider
#> specifying shapes manually if you must have them.
#> Warning: Removed 744 rows containing missing values (geom_point).
dev.off()
#> agg_png 
#>       2

mcar_10

cairo_pdf("mcar-10-type1.pdf", width = width, height = height)
plot_type1(results_mcar_10_ci)
dev.off()
#> agg_png 
#>       2
cairo_pdf("mcar-10-power.pdf", width = width, height = height)
plot_power(results_mcar_10_ci)
dev.off()
#> agg_png 
#>       2
cairo_pdf("mcar-10-miss.pdf", width = width, height = height)
plot_miss(results_mcar_10_ci)
dev.off()
#> agg_png 
#>       2

mcar_20

cairo_pdf("mcar-20-type1.pdf", width = width, height = height)
plot_type1(results_mcar_20_ci)
dev.off()
#> agg_png 
#>       2
cairo_pdf("mcar-20-power.pdf", width = width, height = height)
plot_power(results_mcar_20_ci)
dev.off()
#> agg_png 
#>       2
cairo_pdf("mcar-20-miss.pdf", width = width, height = height)
plot_miss(results_mcar_20_ci)
dev.off()
#> agg_png 
#>       2

mcar_30

cairo_pdf("mcar-30-type1.pdf", width = width, height = height)
plot_type1(results_mcar_30_ci)
dev.off()
#> agg_png 
#>       2
cairo_pdf("mcar-30-power.pdf", width = width, height = height)
plot_power(results_mcar_30_ci)
dev.off()
#> agg_png 
#>       2
cairo_pdf("mcar-30-miss.pdf", width = width, height = height)
plot_miss(results_mcar_30_ci)
dev.off()
#> agg_png 
#>       2