Note: Data for covid-19 last updated 4/22/2020.
Data Set-up
# Data in use: BCG_covid19_DB_unfiltered_14.csv
df_unfiltered[df_unfiltered == ""] <- NA
df_unfiltered$BCG_mean_coverage <- ifelse(!is.na(df_unfiltered$BCG_policy) & is.na(df_unfiltered$BCG_mean_coverage), 0, df_unfiltered$BCG_mean_coverage)
df_unfiltered$BCG_median_coverage <- ifelse(!is.na(df_unfiltered$BCG_policy) & is.na(df_unfiltered$BCG_median_coverage), 0, df_unfiltered$BCG_median_coverage)
df_world <- subset(df_unfiltered, ISO3 != "USA_state")
df_filtered <- subset(df_unfiltered,
covid19_cumulative_deaths > 0
& population_million > 1
& ages_65_up > 15
& urban_percentage_2018 > 60
& population_density_2018 < 300
& HDI_2018 > 0.7
& ISO3 != "USA_state")
df_unfiltered <- df_unfiltered[-which(df_unfiltered$ISO3 == "USA"), ]
df_linear_models <- data.frame()
df_anova_models <- data.frame()
df_t_models <- data.frame()
Key for the dfs:
df_unfiltered: USA as states, no as country
df_world: USA as country, no as states
df_filtered: Social variables (population, age, urban, density, HDI) and USA as country, no as states.
df_filtered_2: Social varibales (popualtion, age, density, HDI) and USA as country, no as states.
VARIABLES
dependent_variables <- names(df_unfiltered)[c(23:28,30:33,35:50)]
dependent_variables
## [1] "total_deaths_per_million"
## [2] "days_to_reached_0.1_deaths_per_million"
## [3] "days_to_reached_1_deaths_per_million"
## [4] "mean_daily_deaths_per_million"
## [5] "median_daily_deaths_per_million"
## [6] "max_daily_deaths_per_million"
## [7] "total_deaths_week_3_per_million"
## [8] "median_daily_deaths_per_million_week_3"
## [9] "mean_daily_deaths_per_million_week_3"
## [10] "max_daily_deaths_per_million_week_3"
## [11] "total_deaths_month_1_per_million"
## [12] "median_daily_deaths_per_million_month_1"
## [13] "mean_daily_deaths_per_million_month_1"
## [14] "max_daily_deaths_per_million_month_1"
## [15] "log_total_deaths_per_million"
## [16] "log_mean_daily_deaths_per_million"
## [17] "log_median_daily_deaths_per_million"
## [18] "log_max_daily_deaths_per_million"
## [19] "log_total_deaths_week_3_per_million"
## [20] "log_median_daily_deaths_per_million_week_3"
## [21] "log_mean_daily_deaths_per_million_week_3"
## [22] "log_max_daily_deaths_per_million_week_3"
## [23] "log_total_deaths_month_1_per_million"
## [24] "log_median_daily_deaths_per_million_month_1"
## [25] "log_mean_daily_deaths_per_million_month_1"
## [26] "log_max_daily_deaths_per_million_month_1"
independent_variables_continuous <- names(df_unfiltered)[17:18]
independent_variables_continuous
## [1] "BCG_mean_coverage" "BCG_median_coverage"
independent_variables_categorical <- names(df_unfiltered)[12]
independent_variables_categorical
## [1] "BCG_policy"
confounding_varibales <- names(df_unfiltered)[c(7,51,6,10)]
confounding_varibales
## [1] "population_density_2018" "urban_percentage_2018"
## [3] "HDI_2018" "ages_65_up"
Models with UNFILTERED data
All data, including states of USA
Linear Models Unfiltered
model_results <- data.frame()
for(i in 1:length(independent_variables_continuous)){
for(j in 1:length(dependent_variables)){
linear_model <- lm(df_unfiltered[,dependent_variables[j]]~df_unfiltered[,independent_variables_continuous[i]])
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = independent_variables_labels_continuous$V2[i],
df = glance(linear_model)$df-1,
r_squared = summary(linear_model)$r.squared,
p_value = glance(linear_model)$p.value,
AIC = glance(linear_model)$AIC)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| Deaths/1 M (Total) |
BCG % (mean) |
1 |
0.1361260 |
0.0000000 |
2881.1695 |
YES |
| Days to 0.1 Death/1 M |
BCG % (mean) |
1 |
0.0301561 |
0.0149270 |
1338.3408 |
YES |
| Days to 1 Death/1 M |
BCG % (mean) |
1 |
0.1151209 |
0.0000129 |
1158.9959 |
YES |
| Deaths/day/1 M (mean) |
BCG % (mean) |
1 |
0.1554433 |
0.0000000 |
1019.2580 |
YES |
| Deaths/day/1 M (median) |
BCG % (mean) |
1 |
0.1428752 |
0.0000000 |
881.1248 |
YES |
| Deaths/day/1 M (max) |
BCG % (mean) |
1 |
0.0933998 |
0.0000103 |
1742.1516 |
YES |
| Deaths/1 M/week 3 (Total) |
BCG % (mean) |
1 |
0.0756698 |
0.0002023 |
1744.4458 |
YES |
| Deaths/1 M/week 3 (median) |
BCG % (mean) |
1 |
0.1448583 |
0.0000002 |
759.7916 |
YES |
| Deaths/1 M/week 3 (mean) |
BCG % (mean) |
1 |
0.0757124 |
0.0002014 |
1051.6875 |
YES |
| Deaths/1 M/week 3 (max) |
BCG % (mean) |
1 |
0.0410293 |
0.0066965 |
1454.9023 |
YES |
| Deaths/1 M/month 1 (Total) |
BCG % (mean) |
1 |
0.1564731 |
0.0000050 |
1489.9232 |
YES |
| Deaths/1 M/month 1 (median) |
BCG % (mean) |
1 |
0.1360215 |
0.0000231 |
496.9906 |
YES |
| Deaths/1 M/month 1 (mean) |
BCG % (mean) |
1 |
0.1569069 |
0.0000048 |
639.5211 |
YES |
| Deaths/1 M/month 1 (max) |
BCG % (mean) |
1 |
0.1113513 |
0.0001430 |
1069.3321 |
YES |
| Deaths/1 M (Total) |
BCG % (mean) |
1 |
0.2620092 |
0.0000000 |
841.1621 |
YES |
| Deaths/day/1 M log(mean) |
BCG % (mean) |
1 |
0.2754344 |
0.0000000 |
813.6563 |
YES |
| Deaths/day/1 M log(median) |
BCG % (mean) |
1 |
0.3033121 |
0.0000000 |
430.0039 |
YES |
| Deaths/day/1 M loglog(max) |
BCG % (mean) |
1 |
0.2947645 |
0.0000000 |
766.1058 |
YES |
| Deaths/1 M/week 3 log(Total) |
BCG % (mean) |
1 |
0.2595466 |
0.0000000 |
637.9625 |
YES |
| Deaths/1 M/week 3 log(median) |
BCG % (mean) |
1 |
0.3063559 |
0.0000000 |
414.8523 |
YES |
| Deaths/1 M/week 3 log(mean) |
BCG % (mean) |
1 |
0.2649374 |
0.0000000 |
635.8839 |
YES |
| Deaths/1 M/week 3 log(max) |
BCG % (mean) |
1 |
0.2842838 |
0.0000000 |
599.3573 |
YES |
| Deaths/1 M/month 1 log(Total) |
BCG % (mean) |
1 |
0.2422890 |
0.0000000 |
519.1898 |
YES |
| Deaths/1 M/month 1 log(median) |
BCG % (mean) |
1 |
0.2820385 |
0.0000000 |
338.3441 |
YES |
| Deaths/1 M/month 1 log(mean) |
BCG % (mean) |
1 |
0.2473710 |
0.0000000 |
518.0925 |
YES |
| Deaths/1 M/month 1 log(max) |
BCG % (mean) |
1 |
0.3127480 |
0.0000000 |
475.1724 |
YES |
| Deaths/1 M (Total) |
BCG % (median) |
1 |
0.1407637 |
0.0000000 |
2879.9261 |
YES |
| Days to 0.1 Death/1 M |
BCG % (median) |
1 |
0.0358504 |
0.0078625 |
1337.1866 |
YES |
| Days to 1 Death/1 M |
BCG % (median) |
1 |
0.1178717 |
0.0000100 |
1158.5040 |
YES |
| Deaths/day/1 M (mean) |
BCG % (median) |
1 |
0.1602067 |
0.0000000 |
1018.1211 |
YES |
| Deaths/day/1 M (median) |
BCG % (median) |
1 |
0.1459009 |
0.0000000 |
880.4140 |
YES |
| Deaths/day/1 M (max) |
BCG % (median) |
1 |
0.0953403 |
0.0000082 |
1741.7209 |
YES |
| Deaths/1 M/week 3 (Total) |
BCG % (median) |
1 |
0.0763381 |
0.0001891 |
1744.3171 |
YES |
| Deaths/1 M/week 3 (median) |
BCG % (median) |
1 |
0.1468238 |
0.0000001 |
759.3820 |
YES |
| Deaths/1 M/week 3 (mean) |
BCG % (median) |
1 |
0.0763808 |
0.0001883 |
1051.5587 |
YES |
| Deaths/1 M/week 3 (max) |
BCG % (median) |
1 |
0.0414890 |
0.0063904 |
1454.8170 |
YES |
| Deaths/1 M/month 1 (Total) |
BCG % (median) |
1 |
0.1574993 |
0.0000046 |
1489.7711 |
YES |
| Deaths/1 M/month 1 (median) |
BCG % (median) |
1 |
0.1366783 |
0.0000220 |
496.8956 |
YES |
| Deaths/1 M/month 1 (mean) |
BCG % (median) |
1 |
0.1579324 |
0.0000045 |
639.3689 |
YES |
| Deaths/1 M/month 1 (max) |
BCG % (median) |
1 |
0.1122710 |
0.0001337 |
1069.2027 |
YES |
| Deaths/1 M (Total) |
BCG % (median) |
1 |
0.2785653 |
0.0000000 |
836.6015 |
YES |
| Deaths/day/1 M log(mean) |
BCG % (median) |
1 |
0.2927808 |
0.0000000 |
808.7858 |
YES |
| Deaths/day/1 M log(median) |
BCG % (median) |
1 |
0.3253688 |
0.0000000 |
426.1755 |
YES |
| Deaths/day/1 M loglog(max) |
BCG % (median) |
1 |
0.3138860 |
0.0000000 |
760.5807 |
YES |
| Deaths/1 M/week 3 log(Total) |
BCG % (median) |
1 |
0.2800072 |
0.0000000 |
633.5071 |
YES |
| Deaths/1 M/week 3 log(median) |
BCG % (median) |
1 |
0.3260764 |
0.0000000 |
411.5066 |
YES |
| Deaths/1 M/week 3 log(mean) |
BCG % (median) |
1 |
0.2856561 |
0.0000000 |
631.3379 |
YES |
| Deaths/1 M/week 3 log(max) |
BCG % (median) |
1 |
0.3044250 |
0.0000000 |
594.8187 |
YES |
| Deaths/1 M/month 1 log(Total) |
BCG % (median) |
1 |
0.2621527 |
0.0000000 |
515.8692 |
YES |
| Deaths/1 M/month 1 log(median) |
BCG % (median) |
1 |
0.3003552 |
0.0000000 |
335.9149 |
YES |
| Deaths/1 M/month 1 log(mean) |
BCG % (median) |
1 |
0.2674310 |
0.0000000 |
514.7157 |
YES |
| Deaths/1 M/month 1 log(max) |
BCG % (median) |
1 |
0.3349844 |
0.0000000 |
471.0610 |
YES |
Anova Models Unfiltered
model_results <- data.frame()
for(i in 1:length(independent_variables_categorical)){
for(j in 1:length(dependent_variables)){
aov_model <- aov(df_unfiltered[,dependent_variables[j]]~df_unfiltered[,independent_variables_categorical[i]])
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = independent_variables_labels_categorical$V2[i],
F_statistic = glance(aov_model)$statistic,
df = glance(aov_model)$df-1,
df.residual = glance(aov_model)$df.residual,
r_squared = glance(aov_model)$r.squared,
p_value = glance(aov_model)$p.value,
AIC = glance(aov_model)$AIC)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| Deaths/1 M (Total) |
BCG Policy |
22.651874 |
2 |
226 |
0.1669853 |
0.0000000 |
2851.6834 |
YES |
| Days to 0.1 Death/1 M |
BCG Policy |
9.237080 |
2 |
192 |
0.0877740 |
0.0001479 |
1322.5557 |
YES |
| Days to 1 Death/1 M |
BCG Policy |
12.061801 |
2 |
155 |
0.1346757 |
0.0000135 |
1157.4651 |
YES |
| Deaths/day/1 M (mean) |
BCG Policy |
21.469455 |
2 |
196 |
0.1797066 |
0.0000000 |
1007.0192 |
YES |
| Deaths/day/1 M (median) |
BCG Policy |
20.425812 |
2 |
196 |
0.1724777 |
0.0000000 |
869.1265 |
YES |
| Deaths/day/1 M (max) |
BCG Policy |
11.928408 |
2 |
196 |
0.1085107 |
0.0000129 |
1725.2938 |
YES |
| Deaths/1 M/week 3 (Total) |
BCG Policy |
7.968327 |
2 |
175 |
0.0834657 |
0.0004875 |
1744.9382 |
YES |
| Deaths/1 M/week 3 (median) |
BCG Policy |
17.817025 |
2 |
175 |
0.1691752 |
0.0000001 |
756.6566 |
YES |
| Deaths/1 M/week 3 (mean) |
BCG Policy |
7.973209 |
2 |
175 |
0.0835125 |
0.0004854 |
1052.1790 |
YES |
| Deaths/1 M/week 3 (max) |
BCG Policy |
4.157750 |
2 |
175 |
0.0453617 |
0.0172147 |
1456.0963 |
YES |
| Deaths/1 M/month 1 (Total) |
BCG Policy |
10.964452 |
2 |
122 |
0.1523593 |
0.0000418 |
1492.5314 |
YES |
| Deaths/1 M/month 1 (median) |
BCG Policy |
10.345279 |
2 |
122 |
0.1450030 |
0.0000708 |
497.6844 |
YES |
| Deaths/1 M/month 1 (mean) |
BCG Policy |
10.999720 |
2 |
122 |
0.1527745 |
0.0000405 |
642.1322 |
YES |
| Deaths/1 M/month 1 (max) |
BCG Policy |
7.456168 |
2 |
122 |
0.1089189 |
0.0008810 |
1071.6738 |
YES |
| Deaths/1 M (Total) |
BCG Policy |
89.762284 |
2 |
196 |
0.4780634 |
0.0000000 |
762.5743 |
YES |
| Deaths/day/1 M log(mean) |
BCG Policy |
93.491717 |
2 |
196 |
0.4882285 |
0.0000000 |
737.8344 |
YES |
| Deaths/day/1 M log(median) |
BCG Policy |
44.116434 |
2 |
115 |
0.4341466 |
0.0000000 |
403.8535 |
YES |
| Deaths/day/1 M loglog(max) |
BCG Policy |
86.155087 |
2 |
196 |
0.4678398 |
0.0000000 |
703.5123 |
YES |
| Deaths/1 M/week 3 log(Total) |
BCG Policy |
56.390419 |
2 |
156 |
0.4196015 |
0.0000000 |
601.2384 |
YES |
| Deaths/1 M/week 3 log(median) |
BCG Policy |
41.756647 |
2 |
113 |
0.4249753 |
0.0000000 |
395.0969 |
YES |
| Deaths/1 M/week 3 log(mean) |
BCG Policy |
58.068272 |
2 |
156 |
0.4267584 |
0.0000000 |
598.3488 |
YES |
| Deaths/1 M/week 3 log(max) |
BCG Policy |
57.291321 |
2 |
156 |
0.4234663 |
0.0000000 |
566.9736 |
YES |
| Deaths/1 M/month 1 log(Total) |
BCG Policy |
48.282277 |
2 |
122 |
0.4418125 |
0.0000000 |
482.9889 |
YES |
| Deaths/1 M/month 1 log(median) |
BCG Policy |
36.942619 |
2 |
91 |
0.4481010 |
0.0000000 |
315.6173 |
YES |
| Deaths/1 M/month 1 log(mean) |
BCG Policy |
49.584277 |
2 |
122 |
0.4483845 |
0.0000000 |
481.2524 |
YES |
| Deaths/1 M/month 1 log(max) |
BCG Policy |
57.157905 |
2 |
122 |
0.4837417 |
0.0000000 |
441.4106 |
YES |
T-test Models Unfiltered
df_unfiltered$BCG_TF <- 1
df_unfiltered[which(df_unfiltered$BCG_policy == "never"),]$BCG_TF <- 0
df_unfiltered[which(df_unfiltered$BCG_policy == "interrupted"),]$BCG_TF <- 0
df_unfiltered$BCG_TF_2 <- 1
df_unfiltered[which(df_unfiltered$BCG_policy == "never"),]$BCG_TF_2 <- 0
df_unfiltered[which(df_unfiltered$BCG_policy == "interrupted"),]$BCG_TF_2 <- NA
independent_variables_t_test <- names(df_unfiltered)[c(ncol(df_unfiltered)-1, ncol(df_unfiltered))] #BCG_TF
independent_variables_t_test
## [1] "BCG_TF" "BCG_TF_2"
independent_variables_t_test_labels <- c("BCG Yes/No", "BCG Yes/No 2")
model_results <- data.frame()
for(i in 1:length(independent_variables_t_test)){
for(j in 1:length(dependent_variables)){
t_test_model <- t.test(df_unfiltered[,dependent_variables[j]]~df_unfiltered[,independent_variables_t_test[i]], paired = FALSE, na.action = na.pass, alternative="greater", var.equal = TRUE)
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = independent_variables_t_test_labels[i],
t_statistic = glance(t_test_model)$statistic,
df = glance(t_test_model)$parameter,
p_value = glance(t_test_model)$p.value)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| t |
Deaths/1 M (Total) |
BCG Yes/No |
6.939394 |
236 |
0.0000000 |
YES |
| t1 |
Days to 0.1 Death/1 M |
BCG Yes/No |
-3.976275 |
198 |
0.9999510 |
|
| t2 |
Days to 1 Death/1 M |
BCG Yes/No |
-4.042137 |
160 |
0.9999589 |
|
| t3 |
Deaths/day/1 M (mean) |
BCG Yes/No |
6.662134 |
203 |
0.0000000 |
YES |
| t4 |
Deaths/day/1 M (median) |
BCG Yes/No |
6.544694 |
203 |
0.0000000 |
YES |
| t5 |
Deaths/day/1 M (max) |
BCG Yes/No |
4.671407 |
203 |
0.0000027 |
YES |
| t6 |
Deaths/1 M/week 3 (Total) |
BCG Yes/No |
3.931218 |
179 |
0.0000603 |
YES |
| t7 |
Deaths/1 M/week 3 (median) |
BCG Yes/No |
6.084141 |
179 |
0.0000000 |
YES |
| t8 |
Deaths/1 M/week 3 (mean) |
BCG Yes/No |
3.932301 |
179 |
0.0000601 |
YES |
| t9 |
Deaths/1 M/week 3 (max) |
BCG Yes/No |
2.757321 |
179 |
0.0032160 |
YES |
| t10 |
Deaths/1 M/month 1 (Total) |
BCG Yes/No |
4.673863 |
125 |
0.0000038 |
YES |
| t11 |
Deaths/1 M/month 1 (median) |
BCG Yes/No |
4.647118 |
125 |
0.0000042 |
YES |
| t12 |
Deaths/1 M/month 1 (mean) |
BCG Yes/No |
4.680721 |
125 |
0.0000037 |
YES |
| t13 |
Deaths/1 M/month 1 (max) |
BCG Yes/No |
3.616805 |
125 |
0.0002156 |
YES |
| t14 |
Deaths/1 M (Total) |
BCG Yes/No |
13.195005 |
203 |
0.0000000 |
YES |
| t15 |
Deaths/day/1 M log(mean) |
BCG Yes/No |
13.280831 |
203 |
0.0000000 |
YES |
| t16 |
Deaths/day/1 M log(median) |
BCG Yes/No |
9.552910 |
117 |
0.0000000 |
YES |
| t17 |
Deaths/day/1 M loglog(max) |
BCG Yes/No |
12.386055 |
203 |
0.0000000 |
YES |
| t18 |
Deaths/1 M/week 3 log(Total) |
BCG Yes/No |
10.273627 |
160 |
0.0000000 |
YES |
| t19 |
Deaths/1 M/week 3 log(median) |
BCG Yes/No |
9.148268 |
114 |
0.0000000 |
YES |
| t20 |
Deaths/1 M/week 3 log(mean) |
BCG Yes/No |
10.414801 |
160 |
0.0000000 |
YES |
| t21 |
Deaths/1 M/week 3 log(max) |
BCG Yes/No |
10.017302 |
160 |
0.0000000 |
YES |
| t22 |
Deaths/1 M/month 1 log(Total) |
BCG Yes/No |
9.553772 |
125 |
0.0000000 |
YES |
| t23 |
Deaths/1 M/month 1 log(median) |
BCG Yes/No |
8.641484 |
92 |
0.0000000 |
YES |
| t24 |
Deaths/1 M/month 1 log(mean) |
BCG Yes/No |
9.674140 |
125 |
0.0000000 |
YES |
| t25 |
Deaths/1 M/month 1 log(max) |
BCG Yes/No |
10.097245 |
125 |
0.0000000 |
YES |
| t26 |
Deaths/1 M (Total) |
BCG Yes/No 2 |
6.400807 |
216 |
0.0000000 |
YES |
| t27 |
Days to 0.1 Death/1 M |
BCG Yes/No 2 |
-4.029448 |
178 |
0.9999586 |
|
| t28 |
Days to 1 Death/1 M |
BCG Yes/No 2 |
-4.445051 |
140 |
0.9999911 |
|
| t29 |
Deaths/day/1 M (mean) |
BCG Yes/No 2 |
6.425030 |
183 |
0.0000000 |
YES |
| t30 |
Deaths/day/1 M (median) |
BCG Yes/No 2 |
6.201199 |
183 |
0.0000000 |
YES |
| t31 |
Deaths/day/1 M (max) |
BCG Yes/No 2 |
4.661817 |
183 |
0.0000030 |
YES |
| t32 |
Deaths/1 M/week 3 (Total) |
BCG Yes/No 2 |
3.875566 |
159 |
0.0000776 |
YES |
| t33 |
Deaths/1 M/week 3 (median) |
BCG Yes/No 2 |
6.063385 |
159 |
0.0000000 |
YES |
| t34 |
Deaths/1 M/week 3 (mean) |
BCG Yes/No 2 |
3.876865 |
159 |
0.0000772 |
YES |
| t35 |
Deaths/1 M/week 3 (max) |
BCG Yes/No 2 |
2.774742 |
159 |
0.0030934 |
YES |
| t36 |
Deaths/1 M/month 1 (Total) |
BCG Yes/No 2 |
4.700281 |
107 |
0.0000039 |
YES |
| t37 |
Deaths/1 M/month 1 (median) |
BCG Yes/No 2 |
4.957549 |
107 |
0.0000013 |
YES |
| t38 |
Deaths/1 M/month 1 (mean) |
BCG Yes/No 2 |
4.709514 |
107 |
0.0000037 |
YES |
| t39 |
Deaths/1 M/month 1 (max) |
BCG Yes/No 2 |
3.681038 |
107 |
0.0001829 |
YES |
| t40 |
Deaths/1 M (Total) |
BCG Yes/No 2 |
11.922752 |
183 |
0.0000000 |
YES |
| t41 |
Deaths/day/1 M log(mean) |
BCG Yes/No 2 |
12.168867 |
183 |
0.0000000 |
YES |
| t42 |
Deaths/day/1 M log(median) |
BCG Yes/No 2 |
8.729902 |
99 |
0.0000000 |
YES |
| t43 |
Deaths/day/1 M loglog(max) |
BCG Yes/No 2 |
11.562369 |
183 |
0.0000000 |
YES |
| t44 |
Deaths/1 M/week 3 log(Total) |
BCG Yes/No 2 |
10.024597 |
140 |
0.0000000 |
YES |
| t45 |
Deaths/1 M/week 3 log(median) |
BCG Yes/No 2 |
8.936436 |
97 |
0.0000000 |
YES |
| t46 |
Deaths/1 M/week 3 log(mean) |
BCG Yes/No 2 |
10.196845 |
140 |
0.0000000 |
YES |
| t47 |
Deaths/1 M/week 3 log(max) |
BCG Yes/No 2 |
9.976614 |
140 |
0.0000000 |
YES |
| t48 |
Deaths/1 M/month 1 log(Total) |
BCG Yes/No 2 |
8.828179 |
107 |
0.0000000 |
YES |
| t49 |
Deaths/1 M/month 1 log(median) |
BCG Yes/No 2 |
7.648712 |
76 |
0.0000000 |
YES |
| t50 |
Deaths/1 M/month 1 log(mean) |
BCG Yes/No 2 |
8.971739 |
107 |
0.0000000 |
YES |
| t51 |
Deaths/1 M/month 1 log(max) |
BCG Yes/No 2 |
9.644907 |
107 |
0.0000000 |
YES |
Models without USA states (UNFILTEREDish data)
All data, excluding states of USA
Linear Models without USA states
model_results <- data.frame()
for(i in 1:length(independent_variables_continuous)){
for(j in 1:length(dependent_variables)){
linear_model <- lm(df_world[,dependent_variables[j]]~df_world[,independent_variables_continuous[i]])
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = independent_variables_labels_continuous$V2[i],
df = glance(linear_model)$df-1,
r_squared = summary(linear_model)$r.squared,
p_value = glance(linear_model)$p.value,
AIC = glance(linear_model)$AIC)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| Deaths/1 M (Total) |
BCG % (mean) |
1 |
0.2366031 |
0.0000000 |
2140.5160 |
YES |
| Days to 0.1 Death/1 M |
BCG % (mean) |
1 |
0.0067255 |
0.3319204 |
1008.9422 |
|
| Days to 1 Death/1 M |
BCG % (mean) |
1 |
0.0066346 |
0.4110823 |
797.6343 |
|
| Deaths/day/1 M (mean) |
BCG % (mean) |
1 |
0.2415931 |
0.0000000 |
683.5829 |
YES |
| Deaths/day/1 M (median) |
BCG % (mean) |
1 |
0.2362020 |
0.0000000 |
563.0322 |
YES |
| Deaths/day/1 M (max) |
BCG % (mean) |
1 |
0.1258195 |
0.0000104 |
1226.1923 |
YES |
| Deaths/1 M/week 3 (Total) |
BCG % (mean) |
1 |
0.1083522 |
0.0001675 |
1253.1962 |
YES |
| Deaths/1 M/week 3 (median) |
BCG % (mean) |
1 |
0.1474357 |
0.0000091 |
430.2380 |
YES |
| Deaths/1 M/week 3 (mean) |
BCG % (mean) |
1 |
0.1083522 |
0.0001675 |
762.8268 |
YES |
| Deaths/1 M/week 3 (max) |
BCG % (mean) |
1 |
0.0766226 |
0.0017025 |
1063.2026 |
YES |
| Deaths/1 M/month 1 (Total) |
BCG % (mean) |
1 |
0.2336352 |
0.0000016 |
1053.4319 |
YES |
| Deaths/1 M/month 1 (median) |
BCG % (mean) |
1 |
0.1406704 |
0.0002930 |
316.0412 |
YES |
| Deaths/1 M/month 1 (mean) |
BCG % (mean) |
1 |
0.2336352 |
0.0000016 |
448.0188 |
YES |
| Deaths/1 M/month 1 (max) |
BCG % (mean) |
1 |
0.1658594 |
0.0000747 |
773.3003 |
YES |
| Deaths/1 M (Total) |
BCG % (mean) |
1 |
0.0679371 |
0.0014301 |
646.4148 |
YES |
| Deaths/day/1 M log(mean) |
BCG % (mean) |
1 |
0.0594069 |
0.0029308 |
625.0253 |
YES |
| Deaths/day/1 M log(median) |
BCG % (mean) |
1 |
0.2251042 |
0.0000195 |
287.4574 |
YES |
| Deaths/day/1 M loglog(max) |
BCG % (mean) |
1 |
0.0775044 |
0.0006394 |
586.0335 |
YES |
| Deaths/1 M/week 3 log(Total) |
BCG % (mean) |
1 |
0.0573318 |
0.0121553 |
461.7982 |
YES |
| Deaths/1 M/week 3 log(median) |
BCG % (mean) |
1 |
0.1002202 |
0.0067429 |
281.0635 |
YES |
| Deaths/1 M/week 3 log(mean) |
BCG % (mean) |
1 |
0.0573318 |
0.0121553 |
461.7982 |
YES |
| Deaths/1 M/week 3 log(max) |
BCG % (mean) |
1 |
0.0696141 |
0.0055685 |
437.6662 |
YES |
| Deaths/1 M/month 1 log(Total) |
BCG % (mean) |
1 |
0.0710927 |
0.0115453 |
390.9117 |
YES |
| Deaths/1 M/month 1 log(median) |
BCG % (mean) |
1 |
0.1228169 |
0.0056246 |
236.1278 |
YES |
| Deaths/1 M/month 1 log(mean) |
BCG % (mean) |
1 |
0.0710927 |
0.0115453 |
390.9117 |
YES |
| Deaths/1 M/month 1 log(max) |
BCG % (mean) |
1 |
0.1146359 |
0.0011728 |
359.4208 |
YES |
| Deaths/1 M (Total) |
BCG % (median) |
1 |
0.2482997 |
0.0000000 |
2137.7985 |
YES |
| Days to 0.1 Death/1 M |
BCG % (median) |
1 |
0.0029027 |
0.5242558 |
1009.4876 |
|
| Days to 1 Death/1 M |
BCG % (median) |
1 |
0.0080735 |
0.3643631 |
797.4836 |
|
| Deaths/day/1 M (mean) |
BCG % (median) |
1 |
0.2540927 |
0.0000000 |
681.1399 |
YES |
| Deaths/day/1 M (median) |
BCG % (median) |
1 |
0.2446902 |
0.0000000 |
561.3895 |
YES |
| Deaths/day/1 M (max) |
BCG % (median) |
1 |
0.1304179 |
0.0000070 |
1225.4170 |
YES |
| Deaths/1 M/week 3 (Total) |
BCG % (median) |
1 |
0.1090331 |
0.0001593 |
1253.0999 |
YES |
| Deaths/1 M/week 3 (median) |
BCG % (median) |
1 |
0.1537013 |
0.0000056 |
429.3086 |
YES |
| Deaths/1 M/week 3 (mean) |
BCG % (median) |
1 |
0.1090331 |
0.0001593 |
762.7306 |
YES |
| Deaths/1 M/week 3 (max) |
BCG % (median) |
1 |
0.0770338 |
0.0016524 |
1063.1465 |
YES |
| Deaths/1 M/month 1 (Total) |
BCG % (median) |
1 |
0.2334873 |
0.0000016 |
1053.4491 |
YES |
| Deaths/1 M/month 1 (median) |
BCG % (median) |
1 |
0.1419351 |
0.0002737 |
315.9101 |
YES |
| Deaths/1 M/month 1 (mean) |
BCG % (median) |
1 |
0.2334873 |
0.0000016 |
448.0360 |
YES |
| Deaths/1 M/month 1 (max) |
BCG % (median) |
1 |
0.1657452 |
0.0000751 |
773.3125 |
YES |
| Deaths/1 M (Total) |
BCG % (median) |
1 |
0.0855354 |
0.0003249 |
643.6127 |
YES |
| Deaths/day/1 M log(mean) |
BCG % (median) |
1 |
0.0767411 |
0.0006819 |
622.2910 |
YES |
| Deaths/day/1 M log(median) |
BCG % (median) |
1 |
0.2637837 |
0.0000029 |
283.6683 |
YES |
| Deaths/day/1 M loglog(max) |
BCG % (median) |
1 |
0.0988073 |
0.0001056 |
582.5990 |
YES |
| Deaths/1 M/week 3 log(Total) |
BCG % (median) |
1 |
0.0789881 |
0.0030733 |
459.2648 |
YES |
| Deaths/1 M/week 3 log(median) |
BCG % (median) |
1 |
0.1265373 |
0.0021655 |
278.9262 |
YES |
| Deaths/1 M/week 3 log(mean) |
BCG % (median) |
1 |
0.0789881 |
0.0030733 |
459.2648 |
YES |
| Deaths/1 M/week 3 log(max) |
BCG % (median) |
1 |
0.0918373 |
0.0013596 |
435.0310 |
YES |
| Deaths/1 M/month 1 log(Total) |
BCG % (median) |
1 |
0.0924947 |
0.0037608 |
388.8372 |
YES |
| Deaths/1 M/month 1 log(median) |
BCG % (median) |
1 |
0.1483364 |
0.0021765 |
234.3268 |
YES |
| Deaths/1 M/month 1 log(mean) |
BCG % (median) |
1 |
0.0924947 |
0.0037608 |
388.8372 |
YES |
| Deaths/1 M/month 1 log(max) |
BCG % (median) |
1 |
0.1416911 |
0.0002773 |
356.6587 |
YES |
Anova Models without USA states
model_results <- data.frame()
for(i in 1:length(independent_variables_categorical)){
for(j in 1:length(dependent_variables)){
aov_model <- aov(df_world[,dependent_variables[j]]~df_world[,independent_variables_categorical[i]])
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = independent_variables_labels_categorical$V2[i],
F_statistic = glance(aov_model)$statistic,
df = glance(aov_model)$df-1,
df.residual = glance(aov_model)$df.residual,
r_squared = glance(aov_model)$r.squared,
p_value = glance(aov_model)$p.value,
AIC = glance(aov_model)$AIC)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| Deaths/1 M (Total) |
BCG Policy |
70.0171070 |
2 |
171 |
0.4502213 |
0.0000000 |
2062.9673 |
YES |
| Days to 0.1 Death/1 M |
BCG Policy |
0.9957736 |
2 |
138 |
0.0142262 |
0.3720762 |
1003.6961 |
|
| Days to 1 Death/1 M |
BCG Policy |
0.7311560 |
2 |
101 |
0.0142717 |
0.4838823 |
798.8317 |
|
| Deaths/day/1 M (mean) |
BCG Policy |
48.4725905 |
2 |
142 |
0.4057214 |
0.0000000 |
642.7717 |
YES |
| Deaths/day/1 M (median) |
BCG Policy |
34.4402350 |
2 |
142 |
0.3266328 |
0.0000000 |
540.9820 |
YES |
| Deaths/day/1 M (max) |
BCG Policy |
26.8070302 |
2 |
142 |
0.2740808 |
0.0000000 |
1186.4926 |
YES |
| Deaths/1 M/week 3 (Total) |
BCG Policy |
16.2457856 |
2 |
123 |
0.2089603 |
0.0000005 |
1240.1111 |
YES |
| Deaths/1 M/week 3 (median) |
BCG Policy |
18.2586556 |
2 |
123 |
0.2289238 |
0.0000001 |
419.5799 |
YES |
| Deaths/1 M/week 3 (mean) |
BCG Policy |
16.2457856 |
2 |
123 |
0.2089603 |
0.0000005 |
749.7417 |
YES |
| Deaths/1 M/week 3 (max) |
BCG Policy |
13.0322419 |
2 |
123 |
0.1748537 |
0.0000074 |
1051.0305 |
YES |
| Deaths/1 M/month 1 (Total) |
BCG Policy |
15.3620035 |
2 |
86 |
0.2632193 |
0.0000020 |
1051.9282 |
YES |
| Deaths/1 M/month 1 (median) |
BCG Policy |
8.4820719 |
2 |
86 |
0.1647578 |
0.0004344 |
315.5109 |
YES |
| Deaths/1 M/month 1 (mean) |
BCG Policy |
15.3620035 |
2 |
86 |
0.2632193 |
0.0000020 |
446.5150 |
YES |
| Deaths/1 M/month 1 (max) |
BCG Policy |
13.8077419 |
2 |
86 |
0.2430609 |
0.0000063 |
766.6567 |
YES |
| Deaths/1 M (Total) |
BCG Policy |
42.1632816 |
2 |
142 |
0.3725880 |
0.0000000 |
580.5231 |
YES |
| Deaths/day/1 M log(mean) |
BCG Policy |
38.1751417 |
2 |
142 |
0.3496688 |
0.0000000 |
565.4862 |
YES |
| Deaths/day/1 M log(median) |
BCG Policy |
25.7859864 |
2 |
70 |
0.4242094 |
0.0000000 |
264.5246 |
YES |
| Deaths/day/1 M loglog(max) |
BCG Policy |
34.3488636 |
2 |
142 |
0.3260487 |
0.0000000 |
534.7549 |
YES |
| Deaths/1 M/week 3 log(Total) |
BCG Policy |
19.9412074 |
2 |
106 |
0.2733874 |
0.0000000 |
435.4232 |
YES |
| Deaths/1 M/week 3 log(median) |
BCG Policy |
13.6730223 |
2 |
69 |
0.2838315 |
0.0000100 |
266.6306 |
YES |
| Deaths/1 M/week 3 log(mean) |
BCG Policy |
19.9412074 |
2 |
106 |
0.2733874 |
0.0000000 |
435.4232 |
YES |
| Deaths/1 M/week 3 log(max) |
BCG Policy |
18.3335492 |
2 |
106 |
0.2570116 |
0.0000001 |
415.1500 |
YES |
| Deaths/1 M/month 1 log(Total) |
BCG Policy |
21.1959276 |
2 |
86 |
0.3301756 |
0.0000000 |
363.8093 |
YES |
| Deaths/1 M/month 1 log(median) |
BCG Policy |
17.0795265 |
2 |
58 |
0.3706533 |
0.0000015 |
217.8737 |
YES |
| Deaths/1 M/month 1 log(mean) |
BCG Policy |
21.1959276 |
2 |
86 |
0.3301756 |
0.0000000 |
363.8093 |
YES |
| Deaths/1 M/month 1 log(max) |
BCG Policy |
23.2284605 |
2 |
86 |
0.3507323 |
0.0000000 |
333.8171 |
YES |
T-test Models without USA states
df_world$BCG_TF <- 1
df_world[which(df_world$BCG_policy == "never"),]$BCG_TF <- 0
df_world[which(df_world$BCG_policy == "interrupted"),]$BCG_TF <- 0
df_world$BCG_TF_2 <- 1
df_world[which(df_world$BCG_policy == "never"),]$BCG_TF_2 <- 0
df_world[which(df_world$BCG_policy == "interrupted"),]$BCG_TF_2 <- NA
independent_variables_t_test <- names(df_world)[c(ncol(df_world)-1, ncol(df_world))] #BCG_TF
independent_variables_t_test
## [1] "BCG_TF" "BCG_TF_2"
model_results <- data.frame()
for(i in 1:length(independent_variables_t_test)){
for(j in 1:length(dependent_variables)){
t_test_model <- t.test(df_world[,dependent_variables[j]]~df_world[,independent_variables_t_test[i]], paired = FALSE, na.action = na.pass, alternative="greater", var.equal = TRUE)
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = independent_variables_t_test_labels[i],
t_statistic = glance(t_test_model)$statistic,
df = glance(t_test_model)$parameter,
p_value = glance(t_test_model)$p.value)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| t |
Deaths/1 M (Total) |
BCG Yes/No |
8.6688316 |
181 |
0.0000000 |
YES |
| t1 |
Days to 0.1 Death/1 M |
BCG Yes/No |
-1.3248692 |
144 |
0.9063435 |
|
| t2 |
Days to 1 Death/1 M |
BCG Yes/No |
-0.9523412 |
106 |
0.8284547 |
|
| t3 |
Deaths/day/1 M (mean) |
BCG Yes/No |
7.6369304 |
149 |
0.0000000 |
YES |
| t4 |
Deaths/day/1 M (median) |
BCG Yes/No |
7.9914050 |
149 |
0.0000000 |
YES |
| t5 |
Deaths/day/1 M (max) |
BCG Yes/No |
4.7064001 |
149 |
0.0000029 |
YES |
| t6 |
Deaths/1 M/week 3 (Total) |
BCG Yes/No |
3.7083465 |
127 |
0.0001552 |
YES |
| t7 |
Deaths/1 M/week 3 (median) |
BCG Yes/No |
6.1693230 |
127 |
0.0000000 |
YES |
| t8 |
Deaths/1 M/week 3 (mean) |
BCG Yes/No |
3.7083465 |
127 |
0.0001552 |
YES |
| t9 |
Deaths/1 M/week 3 (max) |
BCG Yes/No |
2.8855427 |
127 |
0.0022963 |
YES |
| t10 |
Deaths/1 M/month 1 (Total) |
BCG Yes/No |
4.4487645 |
89 |
0.0000124 |
YES |
| t11 |
Deaths/1 M/month 1 (median) |
BCG Yes/No |
4.1421637 |
89 |
0.0000391 |
YES |
| t12 |
Deaths/1 M/month 1 (mean) |
BCG Yes/No |
4.4487645 |
89 |
0.0000124 |
YES |
| t13 |
Deaths/1 M/month 1 (max) |
BCG Yes/No |
3.3084646 |
89 |
0.0006775 |
YES |
| t14 |
Deaths/1 M (Total) |
BCG Yes/No |
8.8361166 |
149 |
0.0000000 |
YES |
| t15 |
Deaths/day/1 M log(mean) |
BCG Yes/No |
8.3384083 |
149 |
0.0000000 |
YES |
| t16 |
Deaths/day/1 M log(median) |
BCG Yes/No |
7.0595723 |
72 |
0.0000000 |
YES |
| t17 |
Deaths/day/1 M loglog(max) |
BCG Yes/No |
7.5996555 |
149 |
0.0000000 |
YES |
| t18 |
Deaths/1 M/week 3 log(Total) |
BCG Yes/No |
6.0640919 |
110 |
0.0000000 |
YES |
| t19 |
Deaths/1 M/week 3 log(median) |
BCG Yes/No |
5.2333074 |
70 |
0.0000008 |
YES |
| t20 |
Deaths/1 M/week 3 log(mean) |
BCG Yes/No |
6.0640919 |
110 |
0.0000000 |
YES |
| t21 |
Deaths/1 M/week 3 log(max) |
BCG Yes/No |
5.6006445 |
110 |
0.0000001 |
YES |
| t22 |
Deaths/1 M/month 1 log(Total) |
BCG Yes/No |
6.2896413 |
89 |
0.0000000 |
YES |
| t23 |
Deaths/1 M/month 1 log(median) |
BCG Yes/No |
5.8512544 |
59 |
0.0000001 |
YES |
| t24 |
Deaths/1 M/month 1 log(mean) |
BCG Yes/No |
6.2896413 |
89 |
0.0000000 |
YES |
| t25 |
Deaths/1 M/month 1 log(max) |
BCG Yes/No |
6.3646151 |
89 |
0.0000000 |
YES |
| t26 |
Deaths/1 M (Total) |
BCG Yes/No 2 |
12.6073605 |
161 |
0.0000000 |
YES |
| t27 |
Days to 0.1 Death/1 M |
BCG Yes/No 2 |
-0.6575432 |
124 |
0.7439748 |
|
| t28 |
Days to 1 Death/1 M |
BCG Yes/No 2 |
-0.3956464 |
86 |
0.6533272 |
|
| t29 |
Deaths/day/1 M (mean) |
BCG Yes/No 2 |
10.8134151 |
129 |
0.0000000 |
YES |
| t30 |
Deaths/day/1 M (median) |
BCG Yes/No 2 |
9.7895438 |
129 |
0.0000000 |
YES |
| t31 |
Deaths/day/1 M (max) |
BCG Yes/No 2 |
6.9818895 |
129 |
0.0000000 |
YES |
| t32 |
Deaths/1 M/week 3 (Total) |
BCG Yes/No 2 |
5.4794354 |
107 |
0.0000001 |
YES |
| t33 |
Deaths/1 M/week 3 (median) |
BCG Yes/No 2 |
6.2679344 |
107 |
0.0000000 |
YES |
| t34 |
Deaths/1 M/week 3 (mean) |
BCG Yes/No 2 |
5.4794354 |
107 |
0.0000001 |
YES |
| t35 |
Deaths/1 M/week 3 (max) |
BCG Yes/No 2 |
4.8561118 |
107 |
0.0000021 |
YES |
| t36 |
Deaths/1 M/month 1 (Total) |
BCG Yes/No 2 |
5.6889062 |
71 |
0.0000001 |
YES |
| t37 |
Deaths/1 M/month 1 (median) |
BCG Yes/No 2 |
4.8163410 |
71 |
0.0000040 |
YES |
| t38 |
Deaths/1 M/month 1 (mean) |
BCG Yes/No 2 |
5.6889062 |
71 |
0.0000001 |
YES |
| t39 |
Deaths/1 M/month 1 (max) |
BCG Yes/No 2 |
4.9264382 |
71 |
0.0000026 |
YES |
| t40 |
Deaths/1 M (Total) |
BCG Yes/No 2 |
5.7336526 |
129 |
0.0000000 |
YES |
| t41 |
Deaths/day/1 M log(mean) |
BCG Yes/No 2 |
5.2659604 |
129 |
0.0000003 |
YES |
| t42 |
Deaths/day/1 M log(median) |
BCG Yes/No 2 |
4.6623847 |
54 |
0.0000105 |
YES |
| t43 |
Deaths/day/1 M loglog(max) |
BCG Yes/No 2 |
5.0930708 |
129 |
0.0000006 |
YES |
| t44 |
Deaths/1 M/week 3 log(Total) |
BCG Yes/No 2 |
3.9753289 |
90 |
0.0000708 |
YES |
| t45 |
Deaths/1 M/week 3 log(median) |
BCG Yes/No 2 |
2.4161023 |
53 |
0.0095828 |
YES |
| t46 |
Deaths/1 M/week 3 log(mean) |
BCG Yes/No 2 |
3.9753289 |
90 |
0.0000708 |
YES |
| t47 |
Deaths/1 M/week 3 log(max) |
BCG Yes/No 2 |
3.8964772 |
90 |
0.0000937 |
YES |
| t48 |
Deaths/1 M/month 1 log(Total) |
BCG Yes/No 2 |
3.9743529 |
71 |
0.0000838 |
YES |
| t49 |
Deaths/1 M/month 1 log(median) |
BCG Yes/No 2 |
2.3929547 |
43 |
0.0105758 |
YES |
| t50 |
Deaths/1 M/month 1 log(mean) |
BCG Yes/No 2 |
3.9743529 |
71 |
0.0000838 |
YES |
| t51 |
Deaths/1 M/month 1 log(max) |
BCG Yes/No 2 |
4.3619597 |
71 |
0.0000214 |
YES |
Models with FILTERED data
All data, filtered as follows
df_filtered <- subsoet(df_unfiltered,
covid19_cumulative_deaths > 0
& population_million > 1
& ages_65_up > 15
& urban_percentage_2018 > 60
& population_density_2018 < 300
& HDI_2018 > 0.7
& ISO3 != "USA_state")
Linear Models Filtered
model_results <- data.frame()
for(i in 1:length(independent_variables_continuous)){
for(j in 1:length(dependent_variables)){
linear_model <- lm(df_filtered[,dependent_variables[j]]~df_filtered[,independent_variables_continuous[i]])
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = independent_variables_labels_continuous$V2[i],
df = glance(linear_model)$df-1,
r_squared = summary(linear_model)$r.squared,
p_value = glance(linear_model)$p.value,
AIC = glance(linear_model)$AIC)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| Deaths/1 M (Total) |
BCG % (mean) |
1 |
0.2315898 |
0.0200810 |
289.73459 |
YES |
| Days to 0.1 Death/1 M |
BCG % (mean) |
1 |
0.0490357 |
0.3098944 |
143.65850 |
|
| Days to 1 Death/1 M |
BCG % (mean) |
1 |
0.0822410 |
0.1846061 |
165.77632 |
|
| Deaths/day/1 M (mean) |
BCG % (mean) |
1 |
0.2432249 |
0.0167913 |
104.90964 |
YES |
| Deaths/day/1 M (median) |
BCG % (mean) |
1 |
0.2211632 |
0.0235405 |
107.10708 |
YES |
| Deaths/day/1 M (max) |
BCG % (mean) |
1 |
0.2212832 |
0.0234976 |
153.75040 |
YES |
| Deaths/1 M/week 3 (Total) |
BCG % (mean) |
1 |
0.0607500 |
0.2688315 |
165.03485 |
|
| Deaths/1 M/week 3 (median) |
BCG % (mean) |
1 |
0.0590461 |
0.2758677 |
73.23700 |
|
| Deaths/1 M/week 3 (mean) |
BCG % (mean) |
1 |
0.0607500 |
0.2688315 |
79.41480 |
|
| Deaths/1 M/week 3 (max) |
BCG % (mean) |
1 |
0.0688437 |
0.2381408 |
105.98417 |
|
| Deaths/1 M/month 1 (Total) |
BCG % (mean) |
1 |
0.1820186 |
0.0606641 |
211.99767 |
|
| Deaths/1 M/month 1 (median) |
BCG % (mean) |
1 |
0.0368319 |
0.4176019 |
52.61515 |
|
| Deaths/1 M/month 1 (mean) |
BCG % (mean) |
1 |
0.1820186 |
0.0606641 |
75.94978 |
|
| Deaths/1 M/month 1 (max) |
BCG % (mean) |
1 |
0.2748073 |
0.0176593 |
122.43004 |
YES |
| Deaths/1 M (Total) |
BCG % (mean) |
1 |
0.1490677 |
0.0688078 |
89.22857 |
|
| Deaths/day/1 M log(mean) |
BCG % (mean) |
1 |
0.1156751 |
0.1123067 |
85.60804 |
|
| Deaths/day/1 M log(median) |
BCG % (mean) |
1 |
0.1461186 |
0.0872487 |
77.05683 |
|
| Deaths/day/1 M loglog(max) |
BCG % (mean) |
1 |
0.1247578 |
0.0982779 |
82.46990 |
|
| Deaths/1 M/week 3 log(Total) |
BCG % (mean) |
1 |
0.0067133 |
0.7169883 |
88.19857 |
|
| Deaths/1 M/week 3 log(median) |
BCG % (mean) |
1 |
0.0434929 |
0.3915494 |
75.95261 |
|
| Deaths/1 M/week 3 log(mean) |
BCG % (mean) |
1 |
0.0067133 |
0.7169883 |
88.19857 |
|
| Deaths/1 M/week 3 log(max) |
BCG % (mean) |
1 |
0.0126939 |
0.6176365 |
82.56393 |
|
| Deaths/1 M/month 1 log(Total) |
BCG % (mean) |
1 |
0.0789809 |
0.2300306 |
77.21616 |
|
| Deaths/1 M/month 1 log(median) |
BCG % (mean) |
1 |
0.0144304 |
0.6460633 |
65.85636 |
|
| Deaths/1 M/month 1 log(mean) |
BCG % (mean) |
1 |
0.0789809 |
0.2300306 |
77.21616 |
|
| Deaths/1 M/month 1 log(max) |
BCG % (mean) |
1 |
0.1700604 |
0.0707810 |
68.60796 |
|
| Deaths/1 M (Total) |
BCG % (median) |
1 |
0.2592818 |
0.0130794 |
288.89041 |
YES |
| Days to 0.1 Death/1 M |
BCG % (median) |
1 |
0.0515939 |
0.2972757 |
143.59654 |
|
| Days to 1 Death/1 M |
BCG % (median) |
1 |
0.0791804 |
0.1933569 |
165.85290 |
|
| Deaths/day/1 M (mean) |
BCG % (median) |
1 |
0.2769130 |
0.0098991 |
103.86230 |
YES |
| Deaths/day/1 M (median) |
BCG % (median) |
1 |
0.2275458 |
0.0213611 |
106.91781 |
YES |
| Deaths/day/1 M (max) |
BCG % (median) |
1 |
0.2495587 |
0.0152219 |
152.89973 |
YES |
| Deaths/1 M/week 3 (Total) |
BCG % (median) |
1 |
0.0560872 |
0.2886136 |
165.14379 |
|
| Deaths/1 M/week 3 (median) |
BCG % (median) |
1 |
0.0553037 |
0.2921062 |
73.32432 |
|
| Deaths/1 M/week 3 (mean) |
BCG % (median) |
1 |
0.0560872 |
0.2886136 |
79.52375 |
|
| Deaths/1 M/week 3 (max) |
BCG % (median) |
1 |
0.0628742 |
0.2603534 |
106.12476 |
|
| Deaths/1 M/month 1 (Total) |
BCG % (median) |
1 |
0.1831038 |
0.0598189 |
211.97112 |
|
| Deaths/1 M/month 1 (median) |
BCG % (median) |
1 |
0.0320625 |
0.4500354 |
52.71394 |
|
| Deaths/1 M/month 1 (mean) |
BCG % (median) |
1 |
0.1831038 |
0.0598189 |
75.92323 |
|
| Deaths/1 M/month 1 (max) |
BCG % (median) |
1 |
0.3029795 |
0.0119085 |
121.63759 |
YES |
| Deaths/1 M (Total) |
BCG % (median) |
1 |
0.1751143 |
0.0468943 |
88.51356 |
YES |
| Deaths/day/1 M log(mean) |
BCG % (median) |
1 |
0.1393051 |
0.0793990 |
84.98510 |
|
| Deaths/day/1 M log(median) |
BCG % (median) |
1 |
0.1617827 |
0.0706727 |
76.66802 |
|
| Deaths/day/1 M loglog(max) |
BCG % (median) |
1 |
0.1467794 |
0.0711571 |
81.88380 |
|
| Deaths/1 M/week 3 log(Total) |
BCG % (median) |
1 |
0.0085930 |
0.6815864 |
88.15689 |
|
| Deaths/1 M/week 3 log(median) |
BCG % (median) |
1 |
0.0445313 |
0.3858247 |
75.93197 |
|
| Deaths/1 M/week 3 log(mean) |
BCG % (median) |
1 |
0.0085930 |
0.6815864 |
88.15689 |
|
| Deaths/1 M/week 3 log(max) |
BCG % (median) |
1 |
0.0141842 |
0.5975727 |
82.53070 |
|
| Deaths/1 M/month 1 log(Total) |
BCG % (median) |
1 |
0.0903511 |
0.1978414 |
76.96771 |
|
| Deaths/1 M/month 1 log(median) |
BCG % (median) |
1 |
0.0170870 |
0.6170304 |
65.81048 |
|
| Deaths/1 M/month 1 log(mean) |
BCG % (median) |
1 |
0.0903511 |
0.1978414 |
76.96771 |
|
| Deaths/1 M/month 1 log(max) |
BCG % (median) |
1 |
0.1978513 |
0.0494013 |
67.92678 |
YES |
Anova Models Filtered
model_results <- data.frame()
for(i in 1:length(independent_variables_categorical)){
for(j in 1:length(dependent_variables)){
aov_model <- aov(df_filtered[,dependent_variables[j]]~df_filtered[,independent_variables_categorical[i]])
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = independent_variables_labels_categorical$V2[i],
F_statistic = glance(aov_model)$statistic,
df = glance(aov_model)$df-1,
df.residual = glance(aov_model)$df.residual,
r_squared = glance(aov_model)$r.squared,
p_value = glance(aov_model)$p.value,
AIC = glance(aov_model)$AIC)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| Deaths/1 M (Total) |
BCG Policy |
4.9213153 |
2 |
20 |
0.3298178 |
0.0182780 |
288.58878 |
YES |
| Days to 0.1 Death/1 M |
BCG Policy |
0.7034859 |
2 |
20 |
0.0657249 |
0.5066961 |
145.25127 |
|
| Days to 1 Death/1 M |
BCG Policy |
0.2388688 |
2 |
20 |
0.0233296 |
0.7897329 |
169.20725 |
|
| Deaths/day/1 M (mean) |
BCG Policy |
4.4953917 |
2 |
20 |
0.3101256 |
0.0244175 |
104.78084 |
YES |
| Deaths/day/1 M (median) |
BCG Policy |
3.0372701 |
2 |
20 |
0.2329683 |
0.0704910 |
108.75579 |
|
| Deaths/day/1 M (max) |
BCG Policy |
5.8771309 |
2 |
20 |
0.3701633 |
0.0098238 |
150.87011 |
YES |
| Deaths/1 M/week 3 (Total) |
BCG Policy |
1.4112872 |
2 |
19 |
0.1293420 |
0.2682578 |
165.36653 |
|
| Deaths/1 M/week 3 (median) |
BCG Policy |
1.9968146 |
2 |
19 |
0.1736842 |
0.1632630 |
72.37882 |
|
| Deaths/1 M/week 3 (mean) |
BCG Policy |
1.4112872 |
2 |
19 |
0.1293420 |
0.2682578 |
79.74649 |
|
| Deaths/1 M/week 3 (max) |
BCG Policy |
0.8962004 |
2 |
19 |
0.0862046 |
0.4246833 |
107.57012 |
|
| Deaths/1 M/month 1 (Total) |
BCG Policy |
1.7178052 |
2 |
17 |
0.1681188 |
0.2091805 |
214.33467 |
|
| Deaths/1 M/month 1 (median) |
BCG Policy |
2.2701622 |
2 |
17 |
0.2107825 |
0.1337124 |
50.63143 |
|
| Deaths/1 M/month 1 (mean) |
BCG Policy |
1.7178052 |
2 |
17 |
0.1681188 |
0.2091805 |
78.28678 |
|
| Deaths/1 M/month 1 (max) |
BCG Policy |
1.9305108 |
2 |
17 |
0.1850831 |
0.1755753 |
126.76302 |
|
| Deaths/1 M (Total) |
BCG Policy |
6.3166573 |
2 |
20 |
0.3871294 |
0.0074763 |
83.68046 |
YES |
| Deaths/day/1 M log(mean) |
BCG Policy |
5.3229454 |
2 |
20 |
0.3473840 |
0.0140145 |
80.61982 |
YES |
| Deaths/day/1 M log(median) |
BCG Policy |
5.1047601 |
2 |
18 |
0.3619175 |
0.0175344 |
72.93901 |
YES |
| Deaths/day/1 M loglog(max) |
BCG Policy |
5.7217908 |
2 |
20 |
0.3639401 |
0.0108388 |
77.12811 |
YES |
| Deaths/1 M/week 3 log(Total) |
BCG Policy |
0.6398720 |
2 |
19 |
0.0631045 |
0.5383513 |
88.91272 |
|
| Deaths/1 M/week 3 log(median) |
BCG Policy |
1.3983268 |
2 |
16 |
0.1487847 |
0.2756231 |
75.73677 |
|
| Deaths/1 M/week 3 log(mean) |
BCG Policy |
0.6398720 |
2 |
19 |
0.0631045 |
0.5383513 |
88.91272 |
|
| Deaths/1 M/week 3 log(max) |
BCG Policy |
0.5257399 |
2 |
19 |
0.0524390 |
0.5994709 |
83.65998 |
|
| Deaths/1 M/month 1 log(Total) |
BCG Policy |
1.9249627 |
2 |
17 |
0.1846494 |
0.1763712 |
76.77891 |
|
| Deaths/1 M/month 1 log(median) |
BCG Policy |
5.2427191 |
2 |
14 |
0.4282316 |
0.0199775 |
58.60010 |
YES |
| Deaths/1 M/month 1 log(mean) |
BCG Policy |
1.9249627 |
2 |
17 |
0.1846494 |
0.1763712 |
76.77891 |
|
| Deaths/1 M/month 1 log(max) |
BCG Policy |
2.5992495 |
2 |
17 |
0.2341825 |
0.1035297 |
68.99978 |
|
T-test Filtered
df_filtered$BCG_TF <- 1
df_filtered[which(df_filtered$BCG_policy == "never"),]$BCG_TF <- 0
df_filtered[which(df_filtered$BCG_policy == "interrupted"),]$BCG_TF <- 0
df_filtered$BCG_TF_2 <- 1
df_filtered[which(df_filtered$BCG_policy == "never"),]$BCG_TF_2 <- 0
df_filtered[which(df_filtered$BCG_policy == "interrupted"),]$BCG_TF_2 <- NA
independent_variables_t_test <- names(df_filtered)[c(ncol(df_filtered)-1, ncol(df_filtered))] #BCG_TF
independent_variables_t_test
## [1] "BCG_TF" "BCG_TF_2"
model_results <- data.frame()
for(i in 1:length(independent_variables_t_test)){
for(j in 1:length(dependent_variables)){
t_test_model <- t.test(df_filtered[,dependent_variables[j]]~df_filtered[,independent_variables_t_test[i]], paired = FALSE, na.action = na.pass, alternative="greater", var.equal = TRUE)
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = independent_variables_t_test_labels[i],
t_statistic = glance(t_test_model)$statistic,
df = glance(t_test_model)$parameter,
p_value = glance(t_test_model)$p.value)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| t |
Deaths/1 M (Total) |
BCG Yes/No |
2.5857733 |
21 |
0.0086223 |
YES |
| t1 |
Days to 0.1 Death/1 M |
BCG Yes/No |
0.9109031 |
21 |
0.1863422 |
|
| t2 |
Days to 1 Death/1 M |
BCG Yes/No |
0.2661910 |
21 |
0.3963441 |
|
| t3 |
Deaths/day/1 M (mean) |
BCG Yes/No |
2.7181348 |
21 |
0.0064404 |
YES |
| t4 |
Deaths/day/1 M (median) |
BCG Yes/No |
2.0814867 |
21 |
0.0249060 |
YES |
| t5 |
Deaths/day/1 M (max) |
BCG Yes/No |
3.1224536 |
21 |
0.0025747 |
YES |
| t6 |
Deaths/1 M/week 3 (Total) |
BCG Yes/No |
1.6065653 |
20 |
0.0619118 |
|
| t7 |
Deaths/1 M/week 3 (median) |
BCG Yes/No |
1.9330375 |
20 |
0.0337576 |
YES |
| t8 |
Deaths/1 M/week 3 (mean) |
BCG Yes/No |
1.6065653 |
20 |
0.0619118 |
|
| t9 |
Deaths/1 M/week 3 (max) |
BCG Yes/No |
1.3076538 |
20 |
0.1029118 |
|
| t10 |
Deaths/1 M/month 1 (Total) |
BCG Yes/No |
1.9001319 |
18 |
0.0367781 |
YES |
| t11 |
Deaths/1 M/month 1 (median) |
BCG Yes/No |
1.8758008 |
18 |
0.0384985 |
YES |
| t12 |
Deaths/1 M/month 1 (mean) |
BCG Yes/No |
1.9001319 |
18 |
0.0367781 |
YES |
| t13 |
Deaths/1 M/month 1 (max) |
BCG Yes/No |
1.9622093 |
18 |
0.0326939 |
YES |
| t14 |
Deaths/1 M (Total) |
BCG Yes/No |
3.2189562 |
21 |
0.0020591 |
YES |
| t15 |
Deaths/day/1 M log(mean) |
BCG Yes/No |
3.0346632 |
21 |
0.0031508 |
YES |
| t16 |
Deaths/day/1 M log(median) |
BCG Yes/No |
3.1282507 |
19 |
0.0027675 |
YES |
| t17 |
Deaths/day/1 M loglog(max) |
BCG Yes/No |
3.1539555 |
21 |
0.0023940 |
YES |
| t18 |
Deaths/1 M/week 3 log(Total) |
BCG Yes/No |
1.0982842 |
20 |
0.1425635 |
|
| t19 |
Deaths/1 M/week 3 log(median) |
BCG Yes/No |
1.5011314 |
17 |
0.0758333 |
|
| t20 |
Deaths/1 M/week 3 log(mean) |
BCG Yes/No |
1.0982842 |
20 |
0.1425635 |
|
| t21 |
Deaths/1 M/week 3 log(max) |
BCG Yes/No |
1.0227095 |
20 |
0.1593286 |
|
| t22 |
Deaths/1 M/month 1 log(Total) |
BCG Yes/No |
2.0167052 |
18 |
0.0294479 |
YES |
| t23 |
Deaths/1 M/month 1 log(median) |
BCG Yes/No |
2.3878842 |
15 |
0.0152696 |
YES |
| t24 |
Deaths/1 M/month 1 log(mean) |
BCG Yes/No |
2.0167052 |
18 |
0.0294479 |
YES |
| t25 |
Deaths/1 M/month 1 log(max) |
BCG Yes/No |
2.3048966 |
18 |
0.0166482 |
YES |
| t26 |
Deaths/1 M (Total) |
BCG Yes/No 2 |
4.8082918 |
8 |
0.0006706 |
YES |
| t27 |
Days to 0.1 Death/1 M |
BCG Yes/No 2 |
1.3253436 |
8 |
0.1108277 |
|
| t28 |
Days to 1 Death/1 M |
BCG Yes/No 2 |
0.7191757 |
8 |
0.2462513 |
|
| t29 |
Deaths/day/1 M (mean) |
BCG Yes/No 2 |
4.9972556 |
8 |
0.0005282 |
YES |
| t30 |
Deaths/day/1 M (median) |
BCG Yes/No 2 |
2.9116612 |
8 |
0.0097696 |
YES |
| t31 |
Deaths/day/1 M (max) |
BCG Yes/No 2 |
12.5358423 |
8 |
0.0000008 |
YES |
| t32 |
Deaths/1 M/week 3 (Total) |
BCG Yes/No 2 |
1.0764244 |
7 |
0.1587155 |
|
| t33 |
Deaths/1 M/week 3 (median) |
BCG Yes/No 2 |
1.3021756 |
7 |
0.1170317 |
|
| t34 |
Deaths/1 M/week 3 (mean) |
BCG Yes/No 2 |
1.0764244 |
7 |
0.1587155 |
|
| t35 |
Deaths/1 M/week 3 (max) |
BCG Yes/No 2 |
0.8870599 |
7 |
0.2022459 |
|
| t36 |
Deaths/1 M/month 1 (Total) |
BCG Yes/No 2 |
2.1196461 |
6 |
0.0391609 |
YES |
| t37 |
Deaths/1 M/month 1 (median) |
BCG Yes/No 2 |
1.1000912 |
6 |
0.1567297 |
|
| t38 |
Deaths/1 M/month 1 (mean) |
BCG Yes/No 2 |
2.1196461 |
6 |
0.0391609 |
YES |
| t39 |
Deaths/1 M/month 1 (max) |
BCG Yes/No 2 |
2.2081792 |
6 |
0.0346584 |
YES |
| t40 |
Deaths/1 M (Total) |
BCG Yes/No 2 |
5.2840271 |
8 |
0.0003713 |
YES |
| t41 |
Deaths/day/1 M log(mean) |
BCG Yes/No 2 |
4.2938492 |
8 |
0.0013188 |
YES |
| t42 |
Deaths/day/1 M log(median) |
BCG Yes/No 2 |
3.3055750 |
7 |
0.0065103 |
YES |
| t43 |
Deaths/day/1 M loglog(max) |
BCG Yes/No 2 |
3.8036082 |
8 |
0.0026049 |
YES |
| t44 |
Deaths/1 M/week 3 log(Total) |
BCG Yes/No 2 |
0.4121970 |
7 |
0.3462628 |
|
| t45 |
Deaths/1 M/week 3 log(median) |
BCG Yes/No 2 |
0.3161754 |
6 |
0.3812898 |
|
| t46 |
Deaths/1 M/week 3 log(mean) |
BCG Yes/No 2 |
0.4121970 |
7 |
0.3462628 |
|
| t47 |
Deaths/1 M/week 3 log(max) |
BCG Yes/No 2 |
0.4384424 |
7 |
0.3371390 |
|
| t48 |
Deaths/1 M/month 1 log(Total) |
BCG Yes/No 2 |
1.8432899 |
6 |
0.0574266 |
|
| t49 |
Deaths/1 M/month 1 log(median) |
BCG Yes/No 2 |
0.1319640 |
5 |
0.4500793 |
|
| t50 |
Deaths/1 M/month 1 log(mean) |
BCG Yes/No 2 |
1.8432899 |
6 |
0.0574266 |
|
| t51 |
Deaths/1 M/month 1 log(max) |
BCG Yes/No 2 |
2.1317797 |
6 |
0.0385099 |
YES |
Models with Confounding varibales
confounding_varibales <- names(df_unfiltered)[c(7,51,6,10)]
confounding_varibales
## [1] "population_density_2018" "urban_percentage_2018"
## [3] "HDI_2018" "ages_65_up"
df_confounding_models_stats <- data.frame()
Linear Models (with UNFILTERED data, including USA states)
model_results <- data.frame()
for(i in 1:length(confounding_varibales)){
for(j in 1:length(dependent_variables)){
linear_model <- lm(df_unfiltered[,dependent_variables[j]]~df_unfiltered[,confounding_varibales[i]])
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = confounding_varibales_labels$V2[i],
df = glance(linear_model)$df-1,
r_squared = summary(linear_model)$r.squared,
p_value = glance(linear_model)$p.value,
AIC = glance(linear_model)$AIC)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| Deaths/1 M (Total) |
Pop Dens |
1 |
0.0012826 |
0.5881310 |
2914.3202 |
|
| Days to 0.1 Death/1 M |
Pop Dens |
1 |
0.0012243 |
0.6254575 |
1279.1824 |
|
| Days to 1 Death/1 M |
Pop Dens |
1 |
0.0065920 |
0.3043795 |
1206.7222 |
|
| Deaths/day/1 M (mean) |
Pop Dens |
1 |
0.0037711 |
0.3852901 |
1056.2067 |
|
| Deaths/day/1 M (median) |
Pop Dens |
1 |
0.0000289 |
0.9394696 |
915.7692 |
|
| Deaths/day/1 M (max) |
Pop Dens |
1 |
0.0290726 |
0.0152616 |
1764.5744 |
YES |
| Deaths/1 M/week 3 (Total) |
Pop Dens |
1 |
0.0122200 |
0.1418436 |
1756.0897 |
|
| Deaths/1 M/week 3 (median) |
Pop Dens |
1 |
0.0000457 |
0.9286466 |
787.6383 |
|
| Deaths/1 M/week 3 (mean) |
Pop Dens |
1 |
0.0122185 |
0.1418689 |
1063.3398 |
|
| Deaths/1 M/week 3 (max) |
Pop Dens |
1 |
0.0602869 |
0.0009550 |
1451.1537 |
YES |
| Deaths/1 M/month 1 (Total) |
Pop Dens |
1 |
0.0023094 |
0.5960968 |
1499.3819 |
|
| Deaths/1 M/month 1 (median) |
Pop Dens |
1 |
0.0009423 |
0.7350231 |
511.8853 |
|
| Deaths/1 M/month 1 (mean) |
Pop Dens |
1 |
0.0023016 |
0.5967231 |
655.8468 |
|
| Deaths/1 M/month 1 (max) |
Pop Dens |
1 |
0.0032974 |
0.5264177 |
1075.9317 |
|
| Deaths/1 M (Total) |
Pop Dens |
1 |
0.0051273 |
0.3112114 |
898.9853 |
|
| Deaths/day/1 M log(mean) |
Pop Dens |
1 |
0.0066454 |
0.2487730 |
872.6668 |
|
| Deaths/day/1 M log(median) |
Pop Dens |
1 |
0.0060058 |
0.4021833 |
472.2958 |
|
| Deaths/day/1 M loglog(max) |
Pop Dens |
1 |
0.0159402 |
0.0733813 |
836.2330 |
|
| Deaths/1 M/week 3 log(Total) |
Pop Dens |
1 |
0.0115343 |
0.1764563 |
678.0033 |
|
| Deaths/1 M/week 3 log(median) |
Pop Dens |
1 |
0.0089428 |
0.3126177 |
456.2426 |
|
| Deaths/1 M/week 3 log(mean) |
Pop Dens |
1 |
0.0115017 |
0.1770712 |
676.9950 |
|
| Deaths/1 M/week 3 log(max) |
Pop Dens |
1 |
0.0257704 |
0.0425772 |
646.0196 |
YES |
| Deaths/1 M/month 1 log(Total) |
Pop Dens |
1 |
0.0005947 |
0.7880514 |
532.0551 |
|
| Deaths/1 M/month 1 log(median) |
Pop Dens |
1 |
0.0095882 |
0.3477729 |
368.5844 |
|
| Deaths/1 M/month 1 log(mean) |
Pop Dens |
1 |
0.0006419 |
0.7800000 |
531.6820 |
|
| Deaths/1 M/month 1 log(max) |
Pop Dens |
1 |
0.0003752 |
0.8309074 |
507.4020 |
|
| Deaths/1 M (Total) |
Urban (%) |
1 |
0.1038580 |
0.0000006 |
2889.6267 |
YES |
| Days to 0.1 Death/1 M |
Urban (%) |
1 |
0.0727658 |
0.0001316 |
1298.3850 |
YES |
| Days to 1 Death/1 M |
Urban (%) |
1 |
0.0000003 |
0.9947058 |
1185.4248 |
|
| Deaths/day/1 M (mean) |
Urban (%) |
1 |
0.1024288 |
0.0000036 |
1031.3771 |
YES |
| Deaths/day/1 M (median) |
Urban (%) |
1 |
0.0810039 |
0.0000422 |
895.1341 |
YES |
| Deaths/day/1 M (max) |
Urban (%) |
1 |
0.0720169 |
0.0001172 |
1747.6361 |
YES |
| Deaths/1 M/week 3 (Total) |
Urban (%) |
1 |
0.0670075 |
0.0004850 |
1746.0101 |
YES |
| Deaths/1 M/week 3 (median) |
Urban (%) |
1 |
0.0711937 |
0.0003179 |
774.5003 |
YES |
| Deaths/1 M/week 3 (mean) |
Urban (%) |
1 |
0.0670202 |
0.0004843 |
1053.2575 |
YES |
| Deaths/1 M/week 3 (max) |
Urban (%) |
1 |
0.0547293 |
0.0016727 |
1452.2338 |
YES |
| Deaths/1 M/month 1 (Total) |
Urban (%) |
1 |
0.1051652 |
0.0002247 |
1497.1887 |
YES |
| Deaths/1 M/month 1 (median) |
Urban (%) |
1 |
0.0671013 |
0.0035340 |
506.5842 |
YES |
| Deaths/1 M/month 1 (mean) |
Urban (%) |
1 |
0.1052619 |
0.0002231 |
646.8371 |
YES |
| Deaths/1 M/month 1 (max) |
Urban (%) |
1 |
0.0884788 |
0.0007549 |
1072.6410 |
YES |
| Deaths/1 M (Total) |
Urban (%) |
1 |
0.2553527 |
0.0000000 |
840.4204 |
YES |
| Deaths/day/1 M log(mean) |
Urban (%) |
1 |
0.2311372 |
0.0000000 |
821.5424 |
YES |
| Deaths/day/1 M log(median) |
Urban (%) |
1 |
0.1582105 |
0.0000075 |
452.5178 |
YES |
| Deaths/day/1 M loglog(max) |
Urban (%) |
1 |
0.2172510 |
0.0000000 |
787.0326 |
YES |
| Deaths/1 M/week 3 log(Total) |
Urban (%) |
1 |
0.2309684 |
0.0000000 |
650.4444 |
YES |
| Deaths/1 M/week 3 log(median) |
Urban (%) |
1 |
0.1937220 |
0.0000008 |
432.3067 |
YES |
| Deaths/1 M/week 3 log(mean) |
Urban (%) |
1 |
0.2332719 |
0.0000000 |
649.0324 |
YES |
| Deaths/1 M/week 3 log(max) |
Urban (%) |
1 |
0.2232756 |
0.0000000 |
618.5531 |
YES |
| Deaths/1 M/month 1 log(Total) |
Urban (%) |
1 |
0.2423223 |
0.0000000 |
513.2619 |
YES |
| Deaths/1 M/month 1 log(median) |
Urban (%) |
1 |
0.2106434 |
0.0000033 |
347.2555 |
YES |
| Deaths/1 M/month 1 log(mean) |
Urban (%) |
1 |
0.2438350 |
0.0000000 |
512.7211 |
YES |
| Deaths/1 M/month 1 log(max) |
Urban (%) |
1 |
0.2486295 |
0.0000000 |
483.8969 |
YES |
| Deaths/1 M (Total) |
HDI |
1 |
0.1225412 |
0.0000001 |
2670.4135 |
YES |
| Days to 0.1 Death/1 M |
HDI |
1 |
0.1180112 |
0.0000017 |
1218.2600 |
YES |
| Days to 1 Death/1 M |
HDI |
1 |
0.0808761 |
0.0003671 |
1131.1507 |
YES |
| Deaths/day/1 M (mean) |
HDI |
1 |
0.1237036 |
0.0000007 |
925.3614 |
YES |
| Deaths/day/1 M (median) |
HDI |
1 |
0.1001064 |
0.0000092 |
848.4256 |
YES |
| Deaths/day/1 M (max) |
HDI |
1 |
0.0941681 |
0.0000175 |
1544.4640 |
YES |
| Deaths/1 M/week 3 (Total) |
HDI |
1 |
0.1062720 |
0.0000162 |
1431.5540 |
YES |
| Deaths/1 M/week 3 (median) |
HDI |
1 |
0.1056200 |
0.0000172 |
733.5421 |
YES |
| Deaths/1 M/week 3 (mean) |
HDI |
1 |
0.1063348 |
0.0000161 |
777.6996 |
YES |
| Deaths/1 M/week 3 (max) |
HDI |
1 |
0.1068488 |
0.0000153 |
1011.0336 |
YES |
| Deaths/1 M/month 1 (Total) |
HDI |
1 |
0.1117858 |
0.0002153 |
1352.7861 |
YES |
| Deaths/1 M/month 1 (median) |
HDI |
1 |
0.0781521 |
0.0021708 |
483.2223 |
YES |
| Deaths/1 M/month 1 (mean) |
HDI |
1 |
0.1120653 |
0.0002112 |
550.0093 |
YES |
| Deaths/1 M/month 1 (max) |
HDI |
1 |
0.1330962 |
0.0000487 |
860.9100 |
YES |
| Deaths/1 M (Total) |
HDI |
1 |
0.6243828 |
0.0000000 |
651.7074 |
YES |
| Deaths/day/1 M log(mean) |
HDI |
1 |
0.6065008 |
0.0000000 |
639.5277 |
YES |
| Deaths/day/1 M log(median) |
HDI |
1 |
0.4304673 |
0.0000000 |
384.8134 |
YES |
| Deaths/day/1 M loglog(max) |
HDI |
1 |
0.5469538 |
0.0000000 |
628.8042 |
YES |
| Deaths/1 M/week 3 log(Total) |
HDI |
1 |
0.5039806 |
0.0000000 |
530.0584 |
YES |
| Deaths/1 M/week 3 log(median) |
HDI |
1 |
0.5093705 |
0.0000000 |
347.4171 |
YES |
| Deaths/1 M/week 3 log(mean) |
HDI |
1 |
0.5105042 |
0.0000000 |
527.0622 |
YES |
| Deaths/1 M/week 3 log(max) |
HDI |
1 |
0.4837598 |
0.0000000 |
501.7570 |
YES |
| Deaths/1 M/month 1 log(Total) |
HDI |
1 |
0.5382291 |
0.0000000 |
425.0290 |
YES |
| Deaths/1 M/month 1 log(median) |
HDI |
1 |
0.5001284 |
0.0000000 |
287.5345 |
YES |
| Deaths/1 M/month 1 log(mean) |
HDI |
1 |
0.5433370 |
0.0000000 |
423.4222 |
YES |
| Deaths/1 M/month 1 log(max) |
HDI |
1 |
0.5367977 |
0.0000000 |
396.1802 |
YES |
| Deaths/1 M (Total) |
>65 yrs |
1 |
0.1279780 |
0.0000000 |
2708.6330 |
YES |
| Days to 0.1 Death/1 M |
>65 yrs |
1 |
0.0456386 |
0.0029274 |
1280.5698 |
YES |
| Days to 1 Death/1 M |
>65 yrs |
1 |
0.0284165 |
0.0360163 |
1150.9434 |
YES |
| Deaths/day/1 M (mean) |
>65 yrs |
1 |
0.1087013 |
0.0000022 |
935.3557 |
YES |
| Deaths/day/1 M (median) |
>65 yrs |
1 |
0.1060613 |
0.0000030 |
846.4015 |
YES |
| Deaths/day/1 M (max) |
>65 yrs |
1 |
0.0598786 |
0.0005292 |
1596.8299 |
YES |
| Deaths/1 M/week 3 (Total) |
>65 yrs |
1 |
0.0885068 |
0.0000638 |
1444.0942 |
YES |
| Deaths/1 M/week 3 (median) |
>65 yrs |
1 |
0.0827749 |
0.0001131 |
728.6481 |
YES |
| Deaths/1 M/week 3 (mean) |
>65 yrs |
1 |
0.0885257 |
0.0000637 |
763.0022 |
YES |
| Deaths/1 M/week 3 (max) |
>65 yrs |
1 |
0.0990977 |
0.0000221 |
983.3174 |
YES |
| Deaths/1 M/month 1 (Total) |
>65 yrs |
1 |
0.0715799 |
0.0027748 |
1370.9796 |
YES |
| Deaths/1 M/month 1 (median) |
>65 yrs |
1 |
0.0535412 |
0.0100217 |
449.5272 |
YES |
| Deaths/1 M/month 1 (mean) |
>65 yrs |
1 |
0.0715986 |
0.0027711 |
534.2129 |
YES |
| Deaths/1 M/month 1 (max) |
>65 yrs |
1 |
0.0683357 |
0.0034942 |
875.0408 |
YES |
| Deaths/1 M (Total) |
>65 yrs |
1 |
0.5198194 |
0.0000000 |
731.0145 |
YES |
| Deaths/day/1 M log(mean) |
>65 yrs |
1 |
0.4962101 |
0.0000000 |
714.7282 |
YES |
| Deaths/day/1 M log(median) |
>65 yrs |
1 |
0.2328582 |
0.0000000 |
434.9981 |
YES |
| Deaths/day/1 M loglog(max) |
>65 yrs |
1 |
0.4346149 |
0.0000000 |
693.5060 |
YES |
| Deaths/1 M/week 3 log(Total) |
>65 yrs |
1 |
0.3595892 |
0.0000000 |
598.9413 |
YES |
| Deaths/1 M/week 3 log(median) |
>65 yrs |
1 |
0.3373678 |
0.0000000 |
403.2550 |
YES |
| Deaths/1 M/week 3 log(mean) |
>65 yrs |
1 |
0.3618312 |
0.0000000 |
597.4358 |
YES |
| Deaths/1 M/week 3 log(max) |
>65 yrs |
1 |
0.3402736 |
0.0000000 |
564.4313 |
YES |
| Deaths/1 M/month 1 log(Total) |
>65 yrs |
1 |
0.3193619 |
0.0000000 |
485.5408 |
YES |
| Deaths/1 M/month 1 log(median) |
>65 yrs |
1 |
0.2899025 |
0.0000000 |
329.8553 |
YES |
| Deaths/1 M/month 1 log(mean) |
>65 yrs |
1 |
0.3197732 |
0.0000000 |
485.1937 |
YES |
| Deaths/1 M/month 1 log(max) |
>65 yrs |
1 |
0.3087627 |
0.0000000 |
457.2030 |
YES |
Linear Models (with UNFILTEREDish data, excluding USA states)
model_results <- data.frame()
for(i in 1:length(confounding_varibales)){
for(j in 1:length(dependent_variables)){
linear_model <- lm(df_world[,dependent_variables[j]]~df_world[,confounding_varibales[i]])
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = confounding_varibales_labels$V2[i],
df = glance(linear_model)$df-1,
r_squared = summary(linear_model)$r.squared,
p_value = glance(linear_model)$p.value,
AIC = glance(linear_model)$AIC)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| Deaths/1 M (Total) |
Pop Dens |
1 |
0.0011480 |
0.6552885 |
2187.5546 |
|
| Days to 0.1 Death/1 M |
Pop Dens |
1 |
0.0027777 |
0.5318725 |
964.3518 |
|
| Days to 1 Death/1 M |
Pop Dens |
1 |
0.0117844 |
0.2634260 |
828.4526 |
|
| Deaths/day/1 M (mean) |
Pop Dens |
1 |
0.0047670 |
0.4043781 |
727.1314 |
|
| Deaths/day/1 M (median) |
Pop Dens |
1 |
0.0008471 |
0.7254814 |
605.6779 |
|
| Deaths/day/1 M (max) |
Pop Dens |
1 |
0.0509724 |
0.0057970 |
1247.6014 |
YES |
| Deaths/1 M/week 3 (Total) |
Pop Dens |
1 |
0.0127465 |
0.2081375 |
1265.9456 |
|
| Deaths/1 M/week 3 (median) |
Pop Dens |
1 |
0.0014999 |
0.6667958 |
450.1467 |
|
| Deaths/1 M/week 3 (mean) |
Pop Dens |
1 |
0.0127465 |
0.2081375 |
775.5763 |
|
| Deaths/1 M/week 3 (max) |
Pop Dens |
1 |
0.0637288 |
0.0043473 |
1064.8793 |
YES |
| Deaths/1 M/month 1 (Total) |
Pop Dens |
1 |
0.0000810 |
0.9336853 |
1065.7884 |
|
| Deaths/1 M/month 1 (median) |
Pop Dens |
1 |
0.0010301 |
0.7665812 |
326.6968 |
|
| Deaths/1 M/month 1 (mean) |
Pop Dens |
1 |
0.0000810 |
0.9336853 |
467.1777 |
|
| Deaths/1 M/month 1 (max) |
Pop Dens |
1 |
0.0004802 |
0.8394024 |
781.6398 |
|
| Deaths/1 M (Total) |
Pop Dens |
1 |
0.0095672 |
0.2369341 |
656.6831 |
|
| Deaths/day/1 M log(mean) |
Pop Dens |
1 |
0.0126368 |
0.1737385 |
632.4162 |
|
| Deaths/day/1 M log(median) |
Pop Dens |
1 |
0.0243621 |
0.1841849 |
304.5043 |
|
| Deaths/day/1 M loglog(max) |
Pop Dens |
1 |
0.0278764 |
0.0425377 |
602.0916 |
YES |
| Deaths/1 M/week 3 log(Total) |
Pop Dens |
1 |
0.0220958 |
0.1211820 |
463.3588 |
|
| Deaths/1 M/week 3 log(median) |
Pop Dens |
1 |
0.0183798 |
0.2561719 |
287.3315 |
|
| Deaths/1 M/week 3 log(mean) |
Pop Dens |
1 |
0.0220958 |
0.1211820 |
463.3588 |
|
| Deaths/1 M/week 3 log(max) |
Pop Dens |
1 |
0.0467794 |
0.0232416 |
441.9745 |
YES |
| Deaths/1 M/month 1 log(Total) |
Pop Dens |
1 |
0.0044630 |
0.5362953 |
380.2796 |
|
| Deaths/1 M/month 1 log(median) |
Pop Dens |
1 |
0.0193912 |
0.2844749 |
242.9267 |
|
| Deaths/1 M/month 1 log(mean) |
Pop Dens |
1 |
0.0044630 |
0.5362953 |
380.2796 |
|
| Deaths/1 M/month 1 log(max) |
Pop Dens |
1 |
0.0043115 |
0.5433118 |
359.7105 |
|
| Deaths/1 M (Total) |
Urban (%) |
1 |
0.0853292 |
0.0000692 |
2217.5829 |
YES |
| Days to 0.1 Death/1 M |
Urban (%) |
1 |
0.0657615 |
0.0018491 |
995.9030 |
YES |
| Days to 1 Death/1 M |
Urban (%) |
1 |
0.0000161 |
0.9671671 |
829.7311 |
|
| Deaths/day/1 M (mean) |
Urban (%) |
1 |
0.0820361 |
0.0003804 |
722.9856 |
YES |
| Deaths/day/1 M (median) |
Urban (%) |
1 |
0.0632207 |
0.0019110 |
602.3101 |
YES |
| Deaths/day/1 M (max) |
Urban (%) |
1 |
0.0556056 |
0.0036729 |
1261.7902 |
YES |
| Deaths/1 M/week 3 (Total) |
Urban (%) |
1 |
0.0538204 |
0.0084138 |
1278.5809 |
YES |
| Deaths/1 M/week 3 (median) |
Urban (%) |
1 |
0.0519262 |
0.0096835 |
448.8019 |
YES |
| Deaths/1 M/week 3 (mean) |
Urban (%) |
1 |
0.0538204 |
0.0084138 |
780.4279 |
YES |
| Deaths/1 M/week 3 (max) |
Urban (%) |
1 |
0.0519901 |
0.0096377 |
1081.3356 |
YES |
| Deaths/1 M/month 1 (Total) |
Urban (%) |
1 |
0.0936797 |
0.0033483 |
1079.2267 |
YES |
| Deaths/1 M/month 1 (median) |
Urban (%) |
1 |
0.0531242 |
0.0288492 |
327.3560 |
YES |
| Deaths/1 M/month 1 (mean) |
Urban (%) |
1 |
0.0936797 |
0.0033483 |
467.0111 |
YES |
| Deaths/1 M/month 1 (max) |
Urban (%) |
1 |
0.0726142 |
0.0102175 |
790.6374 |
YES |
| Deaths/1 M (Total) |
Urban (%) |
1 |
0.2271102 |
0.0000000 |
629.2237 |
YES |
| Deaths/day/1 M log(mean) |
Urban (%) |
1 |
0.2005993 |
0.0000000 |
611.4268 |
YES |
| Deaths/day/1 M log(median) |
Urban (%) |
1 |
0.1673835 |
0.0002954 |
292.7739 |
YES |
| Deaths/day/1 M loglog(max) |
Urban (%) |
1 |
0.1838463 |
0.0000000 |
584.3602 |
YES |
| Deaths/1 M/week 3 log(Total) |
Urban (%) |
1 |
0.2552129 |
0.0000000 |
446.7262 |
YES |
| Deaths/1 M/week 3 log(median) |
Urban (%) |
1 |
0.2232255 |
0.0000279 |
270.4795 |
YES |
| Deaths/1 M/week 3 log(mean) |
Urban (%) |
1 |
0.2552129 |
0.0000000 |
446.7262 |
YES |
| Deaths/1 M/week 3 log(max) |
Urban (%) |
1 |
0.2421337 |
0.0000000 |
427.3247 |
YES |
| Deaths/1 M/month 1 log(Total) |
Urban (%) |
1 |
0.2344023 |
0.0000013 |
373.2958 |
YES |
| Deaths/1 M/month 1 log(median) |
Urban (%) |
1 |
0.2299334 |
0.0000923 |
228.1832 |
YES |
| Deaths/1 M/month 1 log(mean) |
Urban (%) |
1 |
0.2344023 |
0.0000013 |
373.2958 |
YES |
| Deaths/1 M/month 1 log(max) |
Urban (%) |
1 |
0.2341700 |
0.0000014 |
349.5776 |
YES |
| Deaths/1 M (Total) |
HDI |
1 |
0.1405257 |
0.0000007 |
1910.6796 |
YES |
| Days to 0.1 Death/1 M |
HDI |
1 |
0.0586622 |
0.0053167 |
907.3821 |
YES |
| Days to 1 Death/1 M |
HDI |
1 |
0.0151554 |
0.2247596 |
763.1417 |
|
| Deaths/day/1 M (mean) |
HDI |
1 |
0.1354480 |
0.0000113 |
572.9072 |
YES |
| Deaths/day/1 M (median) |
HDI |
1 |
0.1058122 |
0.0001183 |
549.4594 |
YES |
| Deaths/day/1 M (max) |
HDI |
1 |
0.1536850 |
0.0000026 |
912.6502 |
YES |
| Deaths/1 M/week 3 (Total) |
HDI |
1 |
0.0856054 |
0.0014368 |
916.4944 |
YES |
| Deaths/1 M/week 3 (median) |
HDI |
1 |
0.0954405 |
0.0007402 |
412.0146 |
YES |
| Deaths/1 M/week 3 (mean) |
HDI |
1 |
0.0856054 |
0.0014368 |
465.0433 |
YES |
| Deaths/1 M/week 3 (max) |
HDI |
1 |
0.0714125 |
0.0037324 |
657.1093 |
YES |
| Deaths/1 M/month 1 (Total) |
HDI |
1 |
0.0894234 |
0.0063512 |
910.8626 |
YES |
| Deaths/1 M/month 1 (median) |
HDI |
1 |
0.0529740 |
0.0375058 |
306.0163 |
YES |
| Deaths/1 M/month 1 (mean) |
HDI |
1 |
0.0894234 |
0.0063512 |
353.0662 |
YES |
| Deaths/1 M/month 1 (max) |
HDI |
1 |
0.1047204 |
0.0030207 |
560.2606 |
YES |
| Deaths/1 M (Total) |
HDI |
1 |
0.5662770 |
0.0000000 |
481.6867 |
YES |
| Deaths/day/1 M log(mean) |
HDI |
1 |
0.5297392 |
0.0000000 |
473.0943 |
YES |
| Deaths/day/1 M log(median) |
HDI |
1 |
0.3794444 |
0.0000000 |
249.8007 |
YES |
| Deaths/day/1 M loglog(max) |
HDI |
1 |
0.4620395 |
0.0000000 |
460.3211 |
YES |
| Deaths/1 M/week 3 log(Total) |
HDI |
1 |
0.4300768 |
0.0000000 |
361.3481 |
YES |
| Deaths/1 M/week 3 log(median) |
HDI |
1 |
0.4377653 |
0.0000000 |
221.6089 |
YES |
| Deaths/1 M/week 3 log(mean) |
HDI |
1 |
0.4300768 |
0.0000000 |
361.3481 |
YES |
| Deaths/1 M/week 3 log(max) |
HDI |
1 |
0.3864858 |
0.0000000 |
345.4028 |
YES |
| Deaths/1 M/month 1 log(Total) |
HDI |
1 |
0.4693786 |
0.0000000 |
308.9053 |
YES |
| Deaths/1 M/month 1 log(median) |
HDI |
1 |
0.4565029 |
0.0000000 |
190.3747 |
YES |
| Deaths/1 M/month 1 log(mean) |
HDI |
1 |
0.4693786 |
0.0000000 |
308.9053 |
YES |
| Deaths/1 M/month 1 log(max) |
HDI |
1 |
0.4477385 |
0.0000000 |
287.5034 |
YES |
| Deaths/1 M (Total) |
>65 yrs |
1 |
0.2141009 |
0.0000000 |
1956.8134 |
YES |
| Days to 0.1 Death/1 M |
>65 yrs |
1 |
0.0159982 |
0.1350306 |
978.5320 |
|
| Days to 1 Death/1 M |
>65 yrs |
1 |
0.0057871 |
0.4427651 |
797.3250 |
|
| Deaths/day/1 M (mean) |
>65 yrs |
1 |
0.2165571 |
0.0000000 |
530.5210 |
YES |
| Deaths/day/1 M (median) |
>65 yrs |
1 |
0.1765938 |
0.0000001 |
517.0416 |
YES |
| Deaths/day/1 M (max) |
>65 yrs |
1 |
0.2025607 |
0.0000000 |
898.5790 |
YES |
| Deaths/1 M/week 3 (Total) |
>65 yrs |
1 |
0.2131513 |
0.0000001 |
822.4299 |
YES |
| Deaths/1 M/week 3 (median) |
>65 yrs |
1 |
0.2378441 |
0.0000000 |
290.8471 |
YES |
| Deaths/1 M/week 3 (mean) |
>65 yrs |
1 |
0.2131513 |
0.0000001 |
335.9524 |
YES |
| Deaths/1 M/week 3 (max) |
>65 yrs |
1 |
0.1724767 |
0.0000015 |
530.3502 |
YES |
| Deaths/1 M/month 1 (Total) |
>65 yrs |
1 |
0.1721879 |
0.0000583 |
872.8241 |
YES |
| Deaths/1 M/month 1 (median) |
>65 yrs |
1 |
0.1780683 |
0.0000422 |
167.8466 |
YES |
| Deaths/1 M/month 1 (mean) |
>65 yrs |
1 |
0.1721879 |
0.0000583 |
274.2133 |
YES |
| Deaths/1 M/month 1 (max) |
>65 yrs |
1 |
0.1422840 |
0.0002915 |
527.0995 |
YES |
| Deaths/1 M (Total) |
>65 yrs |
1 |
0.5129491 |
0.0000000 |
534.5202 |
YES |
| Deaths/day/1 M log(mean) |
>65 yrs |
1 |
0.4780123 |
0.0000000 |
520.3650 |
YES |
| Deaths/day/1 M log(median) |
>65 yrs |
1 |
0.2789231 |
0.0000016 |
274.8591 |
YES |
| Deaths/day/1 M loglog(max) |
>65 yrs |
1 |
0.4124758 |
0.0000000 |
499.2423 |
YES |
| Deaths/1 M/week 3 log(Total) |
>65 yrs |
1 |
0.3513346 |
0.0000000 |
403.3858 |
YES |
| Deaths/1 M/week 3 log(median) |
>65 yrs |
1 |
0.3861803 |
0.0000000 |
245.6643 |
YES |
| Deaths/1 M/week 3 log(mean) |
>65 yrs |
1 |
0.3513346 |
0.0000000 |
403.3858 |
YES |
| Deaths/1 M/week 3 log(max) |
>65 yrs |
1 |
0.3103516 |
0.0000000 |
381.3821 |
YES |
| Deaths/1 M/month 1 log(Total) |
>65 yrs |
1 |
0.3315835 |
0.0000000 |
344.1489 |
YES |
| Deaths/1 M/month 1 log(median) |
>65 yrs |
1 |
0.3707648 |
0.0000002 |
206.9585 |
YES |
| Deaths/1 M/month 1 log(mean) |
>65 yrs |
1 |
0.3315835 |
0.0000000 |
344.1489 |
YES |
| Deaths/1 M/month 1 log(max) |
>65 yrs |
1 |
0.3212595 |
0.0000000 |
318.6506 |
YES |
Linear Models (with FILTERED data)
model_results <- data.frame()
for(i in 1:length(confounding_varibales)){
for(j in 1:length(dependent_variables)){
linear_model <- lm(df_filtered[,dependent_variables[j]]~df_filtered[,confounding_varibales[i]])
new_row <- data.frame(dependent_variable = dependent_variables_labels$V2[j],
independent_variable = confounding_varibales_labels$V2[i],
df = glance(linear_model)$df-1,
r_squared = summary(linear_model)$r.squared,
p_value = glance(linear_model)$p.value,
AIC = glance(linear_model)$AIC)
model_results <- rbind(model_results, new_row)
}
}
model_results$significant <- ifelse(model_results$p_value < 0.05, "YES", "")
| Deaths/1 M (Total) |
Pop Dens |
1 |
0.2234335 |
0.0227421 |
289.97743 |
YES |
| Days to 0.1 Death/1 M |
Pop Dens |
1 |
0.0077975 |
0.6886736 |
144.63486 |
|
| Days to 1 Death/1 M |
Pop Dens |
1 |
0.0044023 |
0.7635746 |
167.64872 |
|
| Deaths/day/1 M (mean) |
Pop Dens |
1 |
0.2174525 |
0.0249032 |
105.67987 |
YES |
| Deaths/day/1 M (median) |
Pop Dens |
1 |
0.1948731 |
0.0349675 |
107.87064 |
YES |
| Deaths/day/1 M (max) |
Pop Dens |
1 |
0.0879740 |
0.1693494 |
157.38489 |
|
| Deaths/1 M/week 3 (Total) |
Pop Dens |
1 |
0.0352501 |
0.4027611 |
165.62417 |
|
| Deaths/1 M/week 3 (median) |
Pop Dens |
1 |
0.0525821 |
0.3046428 |
73.38761 |
|
| Deaths/1 M/week 3 (mean) |
Pop Dens |
1 |
0.0352501 |
0.4027611 |
80.00412 |
|
| Deaths/1 M/week 3 (max) |
Pop Dens |
1 |
0.0206925 |
0.5230424 |
107.09338 |
|
| Deaths/1 M/month 1 (Total) |
Pop Dens |
1 |
0.0677091 |
0.2678673 |
214.61378 |
|
| Deaths/1 M/month 1 (median) |
Pop Dens |
1 |
0.0553493 |
0.3180395 |
52.22690 |
|
| Deaths/1 M/month 1 (mean) |
Pop Dens |
1 |
0.0677091 |
0.2678673 |
78.56588 |
|
| Deaths/1 M/month 1 (max) |
Pop Dens |
1 |
0.1353197 |
0.1105504 |
125.94849 |
|
| Deaths/1 M (Total) |
Pop Dens |
1 |
0.2679180 |
0.0114176 |
85.76845 |
YES |
| Deaths/day/1 M log(mean) |
Pop Dens |
1 |
0.2395510 |
0.0177705 |
82.13698 |
YES |
| Deaths/day/1 M log(median) |
Pop Dens |
1 |
0.2693613 |
0.0159156 |
73.78349 |
YES |
| Deaths/day/1 M loglog(max) |
Pop Dens |
1 |
0.1173600 |
0.1095580 |
82.66348 |
|
| Deaths/1 M/week 3 log(Total) |
Pop Dens |
1 |
0.0829842 |
0.1935794 |
86.44088 |
|
| Deaths/1 M/week 3 log(median) |
Pop Dens |
1 |
0.0301752 |
0.4769506 |
76.21532 |
|
| Deaths/1 M/week 3 log(mean) |
Pop Dens |
1 |
0.0829842 |
0.1935794 |
86.44088 |
|
| Deaths/1 M/week 3 log(max) |
Pop Dens |
1 |
0.0494529 |
0.3198832 |
81.72920 |
|
| Deaths/1 M/month 1 log(Total) |
Pop Dens |
1 |
0.1576447 |
0.0830269 |
75.43058 |
|
| Deaths/1 M/month 1 log(median) |
Pop Dens |
1 |
0.0969490 |
0.2237801 |
64.36987 |
|
| Deaths/1 M/month 1 log(mean) |
Pop Dens |
1 |
0.1576447 |
0.0830269 |
75.43058 |
|
| Deaths/1 M/month 1 log(max) |
Pop Dens |
1 |
0.1923848 |
0.0530406 |
68.06262 |
|
| Deaths/1 M (Total) |
Urban (%) |
1 |
0.0210892 |
0.5085246 |
295.30327 |
|
| Days to 0.1 Death/1 M |
Urban (%) |
1 |
0.0187160 |
0.5336460 |
144.38036 |
|
| Days to 1 Death/1 M |
Urban (%) |
1 |
0.0208280 |
0.5111901 |
167.26609 |
|
| Deaths/day/1 M (mean) |
Urban (%) |
1 |
0.0291560 |
0.4359951 |
110.63893 |
|
| Deaths/day/1 M (median) |
Urban (%) |
1 |
0.0005150 |
0.9181378 |
112.84417 |
|
| Deaths/day/1 M (max) |
Urban (%) |
1 |
0.1078515 |
0.1260287 |
156.87806 |
|
| Deaths/1 M/week 3 (Total) |
Urban (%) |
1 |
0.0039207 |
0.7819172 |
166.32724 |
|
| Deaths/1 M/week 3 (median) |
Urban (%) |
1 |
0.0107779 |
0.6456844 |
74.33754 |
|
| Deaths/1 M/week 3 (mean) |
Urban (%) |
1 |
0.0039207 |
0.7819172 |
80.70719 |
|
| Deaths/1 M/week 3 (max) |
Urban (%) |
1 |
0.0011815 |
0.8793002 |
107.52738 |
|
| Deaths/1 M/month 1 (Total) |
Urban (%) |
1 |
0.0128226 |
0.6345460 |
215.75787 |
|
| Deaths/1 M/month 1 (median) |
Urban (%) |
1 |
0.0015975 |
0.8671323 |
53.33372 |
|
| Deaths/1 M/month 1 (mean) |
Urban (%) |
1 |
0.0128226 |
0.6345460 |
79.70998 |
|
| Deaths/1 M/month 1 (max) |
Urban (%) |
1 |
0.0188331 |
0.5639718 |
128.47615 |
|
| Deaths/1 M (Total) |
Urban (%) |
1 |
0.0292497 |
0.4352474 |
92.25852 |
|
| Deaths/day/1 M log(mean) |
Urban (%) |
1 |
0.0220120 |
0.4992911 |
87.92351 |
|
| Deaths/day/1 M log(median) |
Urban (%) |
1 |
0.0119435 |
0.6372384 |
80.12173 |
|
| Deaths/day/1 M loglog(max) |
Urban (%) |
1 |
0.0594129 |
0.2623762 |
84.12598 |
|
| Deaths/1 M/week 3 log(Total) |
Urban (%) |
1 |
0.0000960 |
0.9654785 |
88.34464 |
|
| Deaths/1 M/week 3 log(median) |
Urban (%) |
1 |
0.0381293 |
0.4230607 |
76.05885 |
|
| Deaths/1 M/week 3 log(mean) |
Urban (%) |
1 |
0.0000960 |
0.9654785 |
88.34464 |
|
| Deaths/1 M/week 3 log(max) |
Urban (%) |
1 |
0.0000564 |
0.9735288 |
82.84374 |
|
| Deaths/1 M/month 1 log(Total) |
Urban (%) |
1 |
0.0064736 |
0.7359661 |
78.73175 |
|
| Deaths/1 M/month 1 log(median) |
Urban (%) |
1 |
0.0552392 |
0.3638491 |
65.13747 |
|
| Deaths/1 M/month 1 log(mean) |
Urban (%) |
1 |
0.0064736 |
0.7359661 |
78.73175 |
|
| Deaths/1 M/month 1 log(max) |
Urban (%) |
1 |
0.0138611 |
0.6210655 |
72.05685 |
|
| Deaths/1 M (Total) |
HDI |
1 |
0.0355103 |
0.3891885 |
294.96192 |
|
| Days to 0.1 Death/1 M |
HDI |
1 |
0.0123456 |
0.6137551 |
144.52919 |
|
| Days to 1 Death/1 M |
HDI |
1 |
0.0209127 |
0.5103232 |
167.26410 |
|
| Deaths/day/1 M (mean) |
HDI |
1 |
0.0519757 |
0.2954470 |
110.09186 |
|
| Deaths/day/1 M (median) |
HDI |
1 |
0.0199101 |
0.5207464 |
112.39346 |
|
| Deaths/day/1 M (max) |
HDI |
1 |
0.1100131 |
0.1220730 |
156.82227 |
|
| Deaths/1 M/week 3 (Total) |
HDI |
1 |
0.0260200 |
0.4732807 |
165.83365 |
|
| Deaths/1 M/week 3 (median) |
HDI |
1 |
0.0593675 |
0.2745237 |
73.22948 |
|
| Deaths/1 M/week 3 (mean) |
HDI |
1 |
0.0260200 |
0.4732807 |
80.21360 |
|
| Deaths/1 M/week 3 (max) |
HDI |
1 |
0.0164286 |
0.5697286 |
107.18896 |
|
| Deaths/1 M/month 1 (Total) |
HDI |
1 |
0.0356434 |
0.4253593 |
215.29010 |
|
| Deaths/1 M/month 1 (median) |
HDI |
1 |
0.0301139 |
0.4643671 |
52.75416 |
|
| Deaths/1 M/month 1 (mean) |
HDI |
1 |
0.0356434 |
0.4253593 |
79.24221 |
|
| Deaths/1 M/month 1 (max) |
HDI |
1 |
0.0556718 |
0.3165927 |
127.71077 |
|
| Deaths/1 M (Total) |
HDI |
1 |
0.1490655 |
0.0688101 |
89.22863 |
|
| Deaths/day/1 M log(mean) |
HDI |
1 |
0.1538929 |
0.0641028 |
84.59193 |
|
| Deaths/day/1 M log(median) |
HDI |
1 |
0.1492920 |
0.0836058 |
76.97864 |
|
| Deaths/day/1 M loglog(max) |
HDI |
1 |
0.2225340 |
0.0230553 |
79.74530 |
YES |
| Deaths/1 M/week 3 log(Total) |
HDI |
1 |
0.0777593 |
0.2088619 |
86.56588 |
|
| Deaths/1 M/week 3 log(median) |
HDI |
1 |
0.1387693 |
0.1162568 |
73.95902 |
|
| Deaths/1 M/week 3 log(mean) |
HDI |
1 |
0.0777593 |
0.2088619 |
86.56588 |
|
| Deaths/1 M/week 3 log(max) |
HDI |
1 |
0.0788529 |
0.2055565 |
81.03800 |
|
| Deaths/1 M/month 1 log(Total) |
HDI |
1 |
0.1289717 |
0.1199333 |
76.10003 |
|
| Deaths/1 M/month 1 log(median) |
HDI |
1 |
0.1847851 |
0.0850376 |
62.63031 |
|
| Deaths/1 M/month 1 log(mean) |
HDI |
1 |
0.1289717 |
0.1199333 |
76.10003 |
|
| Deaths/1 M/month 1 log(max) |
HDI |
1 |
0.1682877 |
0.0724144 |
68.65063 |
|
| Deaths/1 M (Total) |
>65 yrs |
1 |
0.0419849 |
0.3483063 |
294.80700 |
|
| Days to 0.1 Death/1 M |
>65 yrs |
1 |
0.0993130 |
0.1430033 |
142.40917 |
|
| Days to 1 Death/1 M |
>65 yrs |
1 |
0.2745283 |
0.0102821 |
160.36873 |
YES |
| Deaths/day/1 M (mean) |
>65 yrs |
1 |
0.0390157 |
0.3663080 |
110.40415 |
|
| Deaths/day/1 M (median) |
>65 yrs |
1 |
0.0747764 |
0.2067582 |
111.06846 |
|
| Deaths/day/1 M (max) |
>65 yrs |
1 |
0.0211304 |
0.5081068 |
159.01168 |
|
| Deaths/1 M/week 3 (Total) |
>65 yrs |
1 |
0.0652192 |
0.2513538 |
164.92991 |
|
| Deaths/1 M/week 3 (median) |
>65 yrs |
1 |
0.0955818 |
0.1615026 |
72.36574 |
|
| Deaths/1 M/week 3 (mean) |
>65 yrs |
1 |
0.0652192 |
0.2513538 |
79.30987 |
|
| Deaths/1 M/week 3 (max) |
>65 yrs |
1 |
0.0544502 |
0.2959691 |
106.32164 |
|
| Deaths/1 M/month 1 (Total) |
>65 yrs |
1 |
0.0403471 |
0.3957908 |
215.19231 |
|
| Deaths/1 M/month 1 (median) |
>65 yrs |
1 |
0.0505340 |
0.3406577 |
52.32858 |
|
| Deaths/1 M/month 1 (mean) |
>65 yrs |
1 |
0.0403471 |
0.3957908 |
79.14442 |
|
| Deaths/1 M/month 1 (max) |
>65 yrs |
1 |
0.0369466 |
0.4168637 |
128.10347 |
|
| Deaths/1 M (Total) |
>65 yrs |
1 |
0.0895061 |
0.1655063 |
90.78463 |
|
| Deaths/day/1 M log(mean) |
>65 yrs |
1 |
0.1106745 |
0.1208885 |
85.73773 |
|
| Deaths/day/1 M log(median) |
>65 yrs |
1 |
0.1346590 |
0.1017734 |
77.33679 |
|
| Deaths/day/1 M loglog(max) |
>65 yrs |
1 |
0.0942064 |
0.1542857 |
83.25905 |
|
| Deaths/1 M/week 3 log(Total) |
>65 yrs |
1 |
0.2111992 |
0.0314163 |
83.12744 |
YES |
| Deaths/1 M/week 3 log(median) |
>65 yrs |
1 |
0.1951387 |
0.0582856 |
72.67286 |
|
| Deaths/1 M/week 3 log(mean) |
>65 yrs |
1 |
0.2111992 |
0.0314163 |
83.12744 |
YES |
| Deaths/1 M/week 3 log(max) |
>65 yrs |
1 |
0.1997742 |
0.0370244 |
77.94203 |
YES |
| Deaths/1 M/month 1 log(Total) |
>65 yrs |
1 |
0.1587214 |
0.0818872 |
75.40500 |
|
| Deaths/1 M/month 1 log(median) |
>65 yrs |
1 |
0.2825526 |
0.0280949 |
60.45852 |
YES |
| Deaths/1 M/month 1 log(mean) |
>65 yrs |
1 |
0.1587214 |
0.0818872 |
75.40500 |
|
| Deaths/1 M/month 1 log(max) |
>65 yrs |
1 |
0.1061196 |
0.1610295 |
70.09234 |
|
—————-